Journals Menu
Follow SCIRP
Contact us
customer@scirp.org
WhatsApp +86 18163351462(WhatsApp)
Click here to send a message to me 1655362766
Paper Publishing WeChat

Journal of Information Security

Journal of Information Security

Journal of Information Security

ISSN Print: 2153-1234
ISSN Online: 2153-1242
www.scirp.org/journal/jis
E-mail: jis@scirp.org
"Malware Analysis and Classification: A Survey"
written by Ekta Gandotra, Divya Bansal, Sanjeev Sofat,
published by Journal of Information Security, Vol.5 No.2, 2014
has been cited by the following article(s):
  • Google Scholar
  • CrossRef
[1] A comparison of graph neural networks for malware classification
Journal of Computer Virology and …, 2024
[2] MalDetect: A classifier fusion approach for detection of android malware
Expert Systems with Applications, 2024
[3] Androidgyny: Reviewing clustering techniques for Android malware family classification
Digital Threats: Research and …, 2024
[4] Ransomware Classification Using Hardware Performance Counters on a Non-Virtualized System
IEEE …, 2024
[5] Real-time system call-based ransomware detection
International Journal of …, 2024
[6] Toward more generalized malicious url detection models
… of the AAAI Conference on Artificial …, 2024
[7] Enhanced capsule network‐based executable files malware detection and classification—deep learning approach
Concurrency and Computation: Practice …, 2024
[8] DEEP LEARNING FOR MALWARE DETECTION: LITERATURE REVIEW
Journal of Theoretical and Applied …, 2024
[9] Discovering and exploring cases of educational source code plagiarism with Dolos
arXiv preprint arXiv …, 2024
[10] Revolutionizing Malware Detection: A Paradigm Shift Through Optimized Convolutional Neural Networks
Innovations, Securities, and Case Studies Across …, 2024
[11] Harnessing GPT-2 for Feature Extraction in Malware Detection: A Novel Approach to Cybersecurity
Land Forces Academy Review, 2024
[12] A Comprehensive Study for Malware Detection through Machine Learning in Executable Files
International Journal for …, 2024
[13] MALWARE ANALYSIS SANDBOX
2024
[14] Malware Analysis: An Experimental Approach
Software Engineering Approaches to …, 2024
[15] Enhancing Malware Classification Through LSTM Algorithm Integration in Binary Classification Models
2024
[16] and S. Muthulakshmi Vellore Institute of Technology, Chennai, India subhashini. n@ vit. ac. in
… Systems Design and …, 2023
[17] Deep Convolutional Neural Networks Network with Transfer Learning for Image-Based Malware Analysis
International Conference On …, 2023
[18] Analysing the Malware by using Checksum and Signature-Based Detection Techniques.
… of Engineering & …, 2023
[19] MALWARE CLASSIFICATION WITH MACHINE LEARNING USING MULTI VIEW FEATURE SELECTION AND FUSION APPROACH
RES MILITARIS, 2023
[20] Malware detection using machine learning
2023
[21] ADVANCES IN MALWARE DETECTION APPROACHES USING MACHINE AND DEEP LEARNING
RES MILITARIS, 2023
[22] Mechanisms for analysis and detection of ransomware in desktop operating systems
2023
[23] Dynamic Detection and Classification of Persistence Techniques in Windows Malware
2023
[24] A malicious programs detection method incorporating transformer and co-occurrence matrix
Third International Conference …, 2023
[25] An Efficient and Resilient Technique for Malware Detection
… Conference on the …, 2023
[26] A taxonomy of encryption and encoding algorithms used by advanced persistent threats with emphasis on bespoke encryption algorithms
2023
[27] Malware beaconing detection with Jupyter Notebooks
2023
[28] Android Sistemlerde Derin öğrenme tabanlı kötü amaçlı yazılım Tespit Sistemi
2023
[29] SQL injekcija kao vrsta kibernetičkog napada
2023
[30] Graph representation learning for cyberattack detection and forensics
2023
[31] Malware Detection System using Machine Learning & Deep Learning Technique
2023
[32] A Comparative Analysis of Malware Written in the C and Rust Programming Languages
2023
[33] Interpretable Machine Learning for malware characterization and identification
2023
[34] Novel Methods for Multi-view Learning with Applications in Cyber Security
2023
[35] Most Recent Malicious Software Datasets and Machine Learning Detection Techniques: A Review
Journal of University of Babylon for Pure and Applied …, 2023
[36] Black-box code analysis for reverse engineering through constraint acquisition and program synthesis
2023
[37] Malware classification using deep learning
2023
[38] GRASE: Granulometry Analysis With Semi Eager Classifier to Detect Malware
2023
[39] AntiXcavator: Automated Host-Based Detection and Prevention Tool for Crypto-Mining Malware Using Static and Dynamic Analysis
… on Advancements in …, 2023
[40] Dynamic Analysis of a Malware Sample: Recognizing its Behavior using Forensic Application
2023 4th IEEE Global …, 2023
[41] Static malware detection of Ember windows-PE API call using machine learning
AIP Conference Proceedings, 2023
[42] Data Collection with Honeypot Server for Reverse Engineering of Malware
EAI International Conference on …, 2023
[43] Efficient Graph-Based Malware Detection Using Minimized Kernel and SVM
Cyber Malware: Offensive and Defensive …, 2023
[44] Comparative Analysis of Feature Selection Methods for Detection of Android Malware
… of Deep Learning and Internet of …, 2023
[45] Family Classification based on Tree Representations for Malware
Proceedings of the 14th ACM SIGOPS Asia-Pacific …, 2023
[46] Malware Analysis in Cyber Security based on Deep Learning; Recognition and Classification
… IEEE 3rd International Maghreb Meeting of …, 2023
[47] A Comparative Analysis of VirLock and Bacteriophage ϕ6 through the Lens of Game Theory
Analytics, 2023
[48] Analyzing WhisperGate and BlackCat Malware: Methodology and Threat Perspective
International Journal of …, 2023
[49] Success and failure rate prediction of Android Application using Machine Learning
2022 OPJU …, 2023
[50] Binary and multi-class classification of Android applications using static features
International Journal of Applied …, 2023
[51] Detection and Classification of Malware using File System Dimensions for MTD on IoT
2023
[52] Familial Graph Classification of Malware based on Structured API Call Sequences
2023 IEEE 23rd International Conference on …, 2023
[53] Analysis of Ensemble Methods for Phishing Detection
Intelligent Multimedia Signal …, 2023
[54] Malware Analysis on AI Technique
arXiv preprint arXiv:2311.14501, 2023
[55] Multi-class Malware Detection via Deep Graph Convolutional Networks Using TF-IDF-Based Attributed Call Graphs
International Conference on Information Security …, 2023
[56] A Survey on Malware Attacks Analysis and Detected
… Journal of Innovations in Engineering and …, 2023
[57] Hybrid Malware Variant Detection Model with Extreme Gradient Boosting and Artificial Neural Network Classifiers.
… Materials & Continua, 2023
[58] Recognition of tor malware and onion services
Journal of Computer Virology and Hacking …, 2023
[59] Android Malware Detection Based on Hypergraph Neural Networks
Applied Sciences, 2023
[60] HyperIO: A Hypervisor-Based Framework for Secure IO
Applied Sciences, 2023
[61] A pyramid stripe pooling-based convolutional neural network for malware detection and classification
Journal of Ambient Intelligence and Humanized …, 2023
[62] Kernel-level rootkit detection, prevention and behavior profiling: a taxonomy and survey
arXiv preprint arXiv:2304.00473, 2023
[63] Comparative study of prognosis of malware with PE headers based machine leaning techniques
… Conference on Smart …, 2023
[64] Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection
2023 IEEE 47th …, 2023
[65] Efficient Windows malware identification and classification scheme for plant protection information systems
Frontiers in Plant Science, 2023
[66] Malware resistant data protection in hyper-connected networks: A survey
arXiv preprint arXiv …, 2023
[67] The Anatomy of Hardware Reverse Engineering: An Exploration of Human Factors During Problem Solving
ACM Transactions on …, 2023
[68] Interpreting gnn-based ids detections using provenance graph structural features
arXiv preprint arXiv …, 2023
[69] Similarity-based hybrid malware detection model using api calls
Mathematics, 2023
[70] A comprehensive survey on deep learning based malware detection techniques
Computer Science Review, 2023
[71] Developing resilient cyber-physical systems: A review of state-of-the-art malware detection approaches, gaps, and future directions
Computers, 2023
[72] A Machine Learning based Malware Classification Framework
… on Smart Systems …, 2023
[73] Threats Detection in the Internet of Things Using Convolutional neural networks, long short-term memory, and gated recurrent units
Mesopotamian journal of cybersecurity, 2023
[74] Fast & Furious: On the modelling of malware detection as an evolving data stream
Expert Systems with …, 2023
[75] Review on Android Malware Detection System
… Conference on Data Management, Analytics & …, 2023
[76] Graph Neural Network-based Android Malware Classification with Jumping Knowledge
CoRR, 2022
[77] Risk Detection of Android Applications Using Static Permissions
… in Data Computing, Communication and Security, 2022
[78] Leveraging Classification and Detection of Malware: A Robust Machine Learning-Based Framework
Proceedings of Second International Conference on …, 2022
[79] Malware detection and classification in IoT network using ANN
Mehran University Research …, 2022
[80] APMWMM: Approach to Probe Malware on Windows Machine using Machine Learning
… on Applied Artificial …, 2022
[81] Cyber security for federated learning environment using AI technique
Expert Systems, 2022
[82] GNN-based Android Malware Detection with Jumping Knowledge
arXiv preprint arXiv …, 2022
[83] A New Malware Detection Method Based on VMCADR in Cloud Environments
Security and Communication Networks, 2022
[84] : Hide and Seek with Malware Through Lightweight Multi-feature Based Lenient Hybrid Approach
… on Information and …, 2022
[85] A Novel Neural Network-Based Malware Severity Classification System
International Conference on Software Technologies, 2022
[86] Deep Learning Methods for Malware and Intrusion Detection: A Systematic Literature Review
Security and …, 2022
[87] A Survey on Threat-Modeling Techniques: Protected Objects and Classification of Threats
Symmetry, 2022
[88] Towards Explainable Quantum Machine Learning for Mobile Malware Detection and Classification
Applied Sciences, 2022
[89] DEMD-IoT: a deep ensemble model for IoT malware detection using CNNs and network traffic
Evolving Systems, 2022
[90] DGA-based botnets detection using DNS traffic mining
Journal of King Saud University …, 2022
[91] Embedding vector generation based on function call graph for effective malware detection and classification
Neural Computing and Applications, 2022
[92] Classification of Web Phishing Kits for early detection by platform providers
arXiv preprint arXiv …, 2022
[93] Malware Classification Based on Semi-Supervised Learning
… Conference on Science …, 2022
[94] CFGExplainer: Explaining Graph Neural Network-Based Malware Classification from Control Flow Graphs
2022 52nd Annual IEEE …, 2022
[95] PROUD-MAL: static analysis-based progressive framework for deep unsupervised malware classification of windows portable executable
Complex & Intelligent …, 2022
[96] DEEPSEL: a novel feature selection for early identification of malware in mobile applications
Future Generation …, 2022
[97] On the Effectiveness of Binary Emulation in Malware Classification
arXiv preprint arXiv:2204.04084, 2022
[98] Malware classification using word embeddings algorithms and long‐short term memory networks
Computational …, 2022
[99] Using static and dynamic malware features to perform malware ascription
ECS Transactions, 2022
[100] PSU-CNN: Prediction of student understanding in the classroom through student facial images using convolutional neural network
Materials Today: Proceedings, 2022
[101] Methods for automatic malware analysis and classification: a survey
International Journal of Information …, 2022
[102] Integrating Comparison of Malware Detection Classification using LGBM and XGB Machine Learning Algorithms
… on Blockchain and …, 2022
[103] Detecting Android Malicious Applications using Dynamic Malware Analysis and Machine Learning
Proceedings of the 2022 Fourteenth …, 2022
[104] Malware Analysis Using Machine Learning Techniques
2022 2nd …, 2022
[105] Empowering Artificial Intelligence for Cybersecurity Applications
2022
[106] Computer and Information Sciences
2022
[107] NeuroYara: Learning to Rank for Yara Rules Generation through Deep Language Modeling & Discriminative N-gram Encoding
2022
[108] Hybrid Malware Detection and Classification in Real-Time by Deep Learning Techniques
2022
[109] Countering Anti-Forensics with Virtualization Technology
2022
[110] XLCNN: pre-trained transformer model for malware detection
2022
[111] Usage Patterns and Implementation of Machine Learning for Malware Detection and Predictive Evaluation
… and Smart Energy …, 2022
[112] Malware Classification Using Feature Reduction Method and Autoscaling
SSRN Electronic Journal, 2022
[113] Design and Implementation of a Virtual File System for Hostbased Moving Target Defence in IoT Devices
Master Thesis, 2022
[114] Técnicas de aprendizaje automático para la detección de dominios maliciosos generados algorítmicamente
2022
[115] Protection against remote desktop attacks
Production Systems and Information Engineering, 2022
[116] Introducing Quantum Computing in Mobile Malware Detection
Proceedings of the 17th …, 2022
[117] Android Malware Detection Using Hybrid Meta-heuristic Feature Selection and Ensemble Learning Techniques
… Conference on Advances in Computing and Data …, 2022
[118] TagSeq: Malicious behavior discovery using dynamic analysis
Plos one, 2022
[119] Mdfrcnn: Malware detection using faster region proposals convolution neural network
2022
[120] Optimization of code caves in malware binaries to evade machine learning detectors
Computers & Security, 2022
[121] Malware Classification Using Automated Transmutation and CNN
2022
[122] A hybrid streaming analytic model for detection and classification of malware using Artificial Intelligence techniques
… Architectures, Platforms, Use …, 2022
[123] An unsupervised malware detection system for windows based system call sequences
Malaysian Journal of …, 2022
[124] A Review on malware analysis for IoT and android system
SN Computer Science, 2022
[125] Building cybersecurity ontology for understanding and reasoning adversary tactics and techniques
… Conference on Big …, 2022
[126] Machine learning-based malware detection using stacking of opcodes and bytecode sequences
2022 Seventh International …, 2022
[127] A comparative study of machine learning models for malware detection
2022 19th International …, 2022
[128] Android Malware Risk Evaluation Using Fuzzy Logic
2022 Seventh International …, 2022
[129] Ransomware Detection Technique by using Network Packet Analysis and Machine Learning
Communications of the …, 2022
[130] Machine Learning Models Interpretability for Malware Detection Using Model Agnostic Language for Exploration and Explanation
2022
[131] A Survey on Artificial Intelligence Techniques for Malware Detection
CS & IT Conference …, 2022
[132] Analysis of Machine learning classifiers for Android Malware Detection
2022 6th …, 2022
[133] Malware Analysis Using Machine Learning
… on Intelligent Systems …, 2022
[134] Deep Learning for Android Malware Defenses: a Systematic Literature
2022
[135] Távoli asztal kapcsolat feltörésének elemzése: Investigation of an RDC attack
Energetika-Elektrotechnika–Számítástechnika és …, 2022
[136] MALWARE DETECTION AND SUPPRESSION USING BLOCKCHAIN TECHNOLOGY
2022
[137] ENHANCING MALWARE CLASSIFICATION THROUGH FEATURE INTEGRATION IN MACHINE AND DEEP LEARNING TECHNIQUES
RES MILITARIS, 2022
[138] Evaluating Malware Classifiers on Unknown Malware Families
2022
[139] Malware Recognition Using Machine Learning Methods Based on Semantic Behaviors
International Journal of …, 2022
[140] A Fast Multicore-based Window Entropy Algorithm
International Journal of Advanced …, 2022
[141] Applications of AI and Ml Algorithms as Countermeasures for Internet of Things Cyber Attacks
2022
[142] Analyzing the Behavioral Artifacts for Malicious Software Detection Using Machine Learning Algorithms
2022 4th International Conference on …, 2022
[143] Android Malware Detection Classification and Threat Assessment using Computational Techniques
2022
[144] A Crypto-ransomware Detection Model For The Pre-encryption Stage Using Random Forest Algorithm
2022
[145] How do engineers analyze netlists?: Human problem-solving processes in hardware reverse engineering
2021
[146] Statistical Analysis in Cyberspace: Data veracity, completeness, and clustering
2021
[147] A hybrid approach for android malware detection and family classification
2021
[148] A learning-based static malware detection system with integrated feature
Intell. Autom. Soft Comput, 2021
[149] An Adversarial Training Based Machine Learning Approach to Malware Classification under Adversarial Conditions.
HICSS, 2021
[150] Machine Learning for Static Malware Analysis
Journal: Encyclopedia of Machine Learning and …, 2021
[151] Freki: Uma Ferramenta para Análise Automatizada de Malware
Anais Estendidos do XXI Simpósio Brasileiro …, 2021
[152] Aprendizado de máquina adversário contra Detectores de Malware
2021
[153] Использование машинного обучения для обнаружения вредоносного трафика
Актуальные проблемы развития …, 2021
[154] The cyber security body of knowledge
University of Bristol, ch. Formal Methods for, 2021
[155] Comparative Performance Analysis of Anti-virus Software
2021
[156] A Survey on Cross-Architectural IoT Malware Threat Hunting
2021
[157] DAEMON: Dataset/Platform-Agnostic Explainable Malware Classification Using Multi-Stage Feature Mining
2021
[158] A Hybrid Approach for Android Malware Detection and Family Classification.
2021
[159] Malware detection with sequence-based machine learning and deep learning
2021
[160] An Efficient Approach for Phishing Detection using Machine Learning
2021
[161] Android malware detection techniques: a literature review
2021
[162] Robust Malware Detection using Residual Attention Network
2021
[163] Feature analysis for data-driven APT-related malware discrimination
2021
[164] Malware Classification Using Deep Boosted Learning
2021
[165] Inimitable Approach to Detect & Quarantine Botnet Malware Infections in Network
2021
[166] KLASIFIKASI MALWARE BANKING PADA ANDROID MENGGUNAKAN ALGORITMA RANDOM FOREST
2021
[167] Measuring the level of cyber-security awareness for cybercrime in Saudi Arabia
2021
[168] Detection and robustness evaluation of android malware classifiers
2021
[169] Feature Selection on Permissions, Intents and APIs for Android Malware Detection
2021
[170] State of the art: The monero cryptocurrency mining malware detection using supervised machine learning algorithms
2021
[171] MMALE a methodology for malware analysis in linux environments
2021
[172] Vehicle Security: A Survey of Security Issues and Vulnerabilities, Malware Attacks and Defenses
IEEE …, 2021
[173] A study on malicious software behaviour analysis and detection techniques: Taxonomy, current trends and challenges
Future Generation Computer …, 2021
[174] Comprehensive review of malware detection techniques
2021 International …, 2021
[175] Comparative Performance Analysis of Anti-virus Software.
2021
[176] Security Assessment for Tay Services
2021
[177] Detection of exceptional malware variants using deep boosted feature spaces and machine learning
Applied Sciences, 2021
[178] Deep learning for android malware defenses: a systematic literature review
arXiv preprint arXiv:2103.05292, 2021
[179] Image-based malware classification using section distribution information
Computers & Security, 2021
[180] Malicious Behavior Detection Method Using API Sequence in Binary Execution Path.
2021
[181] Cluster Analysis of Malware Family Relationships
2021
[182] Hypervisor-assisted dynamic malware analysis
2021
[183] FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data
2021
[184] HyperPass: Secure Password Input Platform.
2021
[185] Malware homology determination using visualized images and feature fusion
2021
[186] The Spy Next Door: A Digital Computer Analysis Approach for Backdoor Trojan Attack
Avrupa Bilim ve Teknoloji Dergisi, 2021
[187] CSForest: an approach for imbalanced family classification of android malicious applications
2021
[188] Generative adversarial network to detect unseen Internet of Things malware
2021
[189] Hancitor malware recognition using swarm intelligent technique
2021
[190] Malicious Behavior Detection Method Using API Sequence in Binary Execution Path
2021
[191] Doctorado en Tecnologías de la Información, Comunicaciones y Computación
2021
[192] Racing demons: Malware detection in early execution
2021
[193] A survey paper on malware detection techniques
International Journal, 2021
[194] Ασφάλεια και προστασία ιδιωτικότητας οικιακών συσκευών που λειτουργούν σε περιβάλλον ΔτΠ
2021
[195] Büyük Veri Ortamlarında Zararlı Yazılım Tespiti Kapsamında Makine Öğrenmesi Algoritmalarının Performansının İncelenmesi
El-Cezeri, 2021
[196] Advanced methods for android malware detection
2021
[197] Image-based Malware Classification using Deep Convolutional Neural Network and Transfer Learning
2021 3rd International Conference on Advanced …, 2021
[198] Fine-grained Classification of Malicious Code Based on CNN and Multi-resolution Feature Fusion
2021 6th International …, 2021
[199] Malware Detection Using Transformers-based Model GPT-2
2021
[200] How do engineers analyze netlists?: Human problem-solving processes in hardware reverse engineering.
2021
[201] An Effective Feature Extraction Mechanism for Intrusion Detection System
IEICE Transactions on …, 2021
[202] Malware Classification by Learning Semantic and Structural Features of Control Flow Graphs
… Conference on Trust, Security and Privacy …, 2021
[203] Toward an Effective Black-Box Adversarial Attack on Functional JavaScript Malware against Commercial Anti-Virus
Proceedings of the 30th ACM International …, 2021
[204] Static Analysis of PE files Using Neural Network Techniques for a Pocket Tool
2021 International …, 2021
[205] Cyber-Espionage Malware Attacks Detection and Analysis: A Case Study
Journal of Computer Information Systems, 2021
[206] Python and Malware: Developing Stealth and Evasive Malware Without Obfuscation
arXiv preprint arXiv:2105.00565, 2021
[207] A survey on common threats in npm and PyPI registries
… Workshop on Deployable Machine Learning for …, 2021
[208] Collection of the Main Anti-Virus Detection and Bypass Techniques
International Conference on Network …, 2021
[209] Clustering based opcode graph generation for malware variant detection
… Conference on Privacy, Security and Trust …, 2021
[210] Transfer Learning and Smote Algorithm For Image-Based Malware Classification
… of the 4th International Conference on …, 2021
[211] Deep Learning Approach in Malware Hunting
Smart Computing and Self …, 2021
[212] A Survey on Malware Classification Using Machine Learning and Deep Learning
International Journal, 2021
[213] AI-HydRa: Advanced hybrid approach using random forest and deep learning for malware classification
2021
[214] Beyond Labeling: Using Clustering to Build Network Behavioral Profiles of Malware Families
2021
[215] Performance Comparison and Current Challenges of Using Machine Learning Techniques in Cybersecurity
2020
[216] Forenzní analýza v počítačové bezpečnosti
2020
[217] Sécurité par analyse comportementale de fonctions embarquées sur plateformes avioniques modulaires intégrées
2020
[218] Metody statické analýzy malware
2020
[219] Machine Learning (In) Security: A Stream of Problems
2020
[220] Imaging and evaluating the memory access for malware
2020
[221] FastText-Based Local Feature Visualization Algorithm for Merged Image-Based Malware Classification Framework for Cyber Security and Cyber Defense
2020
[222] Model checking and machine learning techniques for HummingBad mobile malware detection and mitigation
2020
[223] Machine Learning Framework to Analyze IoT Malware Using ELF and Opcode Features
2020
[224] Secure Mobile Computing by Using Convolutional and Capsule Deep Neural Networks
2020
[225] Contextual Identification of Windows Malware through Semantic Interpretation of API Call Sequence
2020
[226] LightGBM Algorithm for Malware Detection
2020
[227] A dynamic Windows malware detection and prediction method based on contextual understanding of API call sequence
2020
[228] Detection of malicious software by analyzing the behavioral artifacts using machine learning algorithms
2020
[229] CUSTOMER LOAN PREDICTION ANALYSIS
2020
[230] Malware Classification Using Simhash Encoding and PCA (MCSP)
2020
[231] A novel approach for early malware detection
2020
[232] Malware classification for the cloud via semi-supervised transfer learning
2020
[233] A survey on machine learning-based malware detection in executable files
2020
[234] Malware Detection on Virtual Environment Based on Behavioral Anomalies
2020
[235] Internet of Things Forensics HoneyNetCloud Investigation Model
2020
[236] Byte-level malware classification based on markov images and deep learning
2020
[237] A Review on Fileless Malware Analysis Techniques
2020
[238] Malware Classification by Using Deep Learning Framework
2020
[239] DAEMON: Dataset-Agnostic Explainable Malware Classification Using Multi-Stage Feature Mining
2020
[240] A Hybrid Deep Learning Model for Malicious Behavior Detection
2020
[241] A malware variants detection methodology with an opcode-based feature learning method and a fast density-based clustering algorithm
2020
[242] Early Detection of Smart Ponzi Scheme Contracts Based on Behavior Forest Similarity
2020
[243] Machine learning approach for detection of fileless cryptocurrency mining malware
2020
[244] Generative Adversarial Network for Global Image-Based Local Image to Improve Malware Classification Using Convolutional Neural Network
2020
[245] CLEMENT: Machine Learning Methods for Malware Recognition Based on Semantic Behaviours
2020
[246] Malware detection in industrial internet of things based on hybrid image visualization and deep learning model
2020
[247] Malware Elimination Impact on Dynamic Analysis: An Experimental Machine Learning Approach
2020
[248] Realising Honeypot-as-a-Service for Smart Home Solutions
2020
[249] Detection of Malicious Vbscript Using Static and Dynamic Analysis with Recurrent Deep Learning
2020
[250] Android Malware Family Classification and Analysis: Current Status and Future Directions
2020
[251] Improving Spoofed Website Detection Using Machine Learning
2020
[252] Protocol Deployment for Employing Honeypot-as-a-Service
2020
[253] SoK: exploring the state of the art and the future potential of artificial intelligence in digital forensic investigation
2020
[254] Systematic Approach to Malware Analysis (SAMA)
2020
[255] A Review of Computer Vision Methods in Network Security
2020
[256] Malicious Software Threats
2020
[257] From Image to Code: Executable Adversarial Examples of Android Applications
2020
[258] Proposed Framework to Improving Performance of Familial Classification in Android Malware
2020
[259] A Systematic Literature Review and Quality Analysis of Javascript Malware Detection
2020
[260] Adapting to Concept Drift in Malware Detection
2020
[261] Identifying meaningful clusters in malware data
2020
[262] Computer Network Information Security Protection Strategy Based on Clustering Algorithms
2020
[263] ConvProtoNet: Deep Prototype Induction towards Better Class Representation for Few-Shot Malware Classification
2020
[264] GRAMAC: A Graph Based Android Malware Classification Mechanism
2020
[265] Hardware-Assisted MMU Redirection for In-Guest Monitoring and API Profiling
2020
[266] A Deep Learning Approach to Image-Based Malware Analysis
2020
[267] Detection and fine-grained classification of malicious code using convolutional neural networks and swarm intelligence algorithms
2020
[268] A novel method for malware detection on ML-based visualization technique
2020
[269] A comprehensive review on malware detection approaches
2020
[270] Deep learning for image-based mobile malware detection
2020
[271] A survey on mobile malware detection techniques
2020
[272] Efficient algorithm for malware classification: N-gram MCSC
2020
[273] Classification of malware for self-driving systems
2020
[274] Impact Analysis of Malware Based on Call Network API with Heuristic Detection Method
2020
[275] Distance Metric Learning using Particle Swarm Optimization to Improve Static Malware Detection.
ICISSP, 2020
[276] Malware Classification with Gaussian Mixture Model-Hidden Markov Models
2020
[277] Studi Literatur Analisis Malware Menggunakan Metode Analisis Dinamis dan Statis
Jurnal Jaringan Komputer dan Keamanan, 2020
[278] A compensatory approach to anti-virus shortfalls
2020
[279] Nuevos espacios de seguridad nacional: Cómo proteger la información en el ciberespacio
2020
[280] Analisis Karakteristik Malware Joker Berdasarkan Fitur Menggunakan Metode Statik Pada Platform Android
2020
[281] Android Malware Detection using Chi-Square Feature Selection and Ensemble Learning Method
2020
[282] A Solution for Early Detection and Negation of Code and DLL Injection Attacks of Malwares
2020
[283] A Framework for Detection of Android Malware using Static Features
2020
[284] Approaches to Analysing Malware Received from a Reactive Network Telescope
2020
[285] Automated analysis approach for the detection of high survivable ransomware
rimy - KSII Transactions on Internet …, 2020
[286] A Feature-Based Detection System of Adversarial Sample Attack
2020
[287] Explorando o uso de análise estática e aprendizagem supervisionada de máquina para a identificação de códigos maliciosos em arquivos executáveis do sistema …
2020
[288] How Many Phish Can Tweet?
2020
[289] Human enhancement making use of technological incorporations in their biology-Ethical perspective
2020
[290] Loan Approval Prediction System Using Machine Learning
Journal of Innovation in Information Technology, 2020
[291] A Comparative Analysis of Machine Learning Techniques for Classification and Detection of Malware
2020
[292] An In-depth Survey on Malware Detection Techniques
2020
[293] Robust intelligent malware detection using lightgbm algorithm
International Journal of Innovative Technology and Exploring Engineering, 2020
[294] Malware Analysis using Machine Learning and Deep Learning techniques
2020
[295] Malware Threat Analysis of IoT Devices Using Deep Learning Neural Network Methodologies
2020
[296] ESCAPADE: Encryption-type-ransomware: System call based pattern detection
2020
[297] Evaluation to Classify Ransomware Variants based on Correlations between APIs.
2020
[298] A survey on machine learning techniques for cyber security in the last decade
2020
[299] Malware Family Classification Model Using User Defined Features and Representation Learning
2020
[300] No Need to Teach New Tricks to Old Malware: Winning an Evasion Challenge with XOR-based Adversarial Samples
2020
[301] Detection of Anomalous In-Memory Process based on DLL Sequence
International Journal of Advanced Computer Science and Applications, 2020
[302] Weighted N-gram MCSC
2020
[303] Automated analysis approach for the detection of high survivable ransomwares
2020
[304] 基于行为路径树的恶意软件分类方法.
Journal of Computer …, 2020
[305] 回避型マルウェア解析のための回避コード抽出に関する研究
2020
[306] 具可解釋性的集成式深度學習惡意程式分類模型
交通大學數據科學與工程研究所學位論文, 2020
[307] API グループ間の相関性とフォルダ操作頻度に基づくマルウェア分類手法の提案
情報処理学会論文 …, 2020
[308] Evaluation of modern detection techniques on evasive malware
2019
[309] Neural Malware Detection
2019
[310] Research on malicious code evolution and traceability technology
Journal of software, 2019
[311] Convolutional Neural Network for Classification of Android Applications Represented as Grayscale Images
2019
[312] Methodology for Malware Scripting Analysis in Controlled Environments Based on Open Source Tools
2019
[313] An Automated Tool for Malware Analysis and Classification
2019
[314] Malware Classification Using Machine Learning and Portable Executable Features
2019
[315] Dynamic API call sequence visualisation for malware classification
2019
[316] Optimal remote access Trojans detection based on network behavior.
2019
[317] Machine Learning-Based Malware Detection using Recurrent Neural Networks
Castrillo, NB Agostini… - 2019 IEEE MIT …, 2019
[318] Minicursos do XIX Simpósio Brasileiro de Segurança da Informação e de Sistemas Computacionais
2019
[319] Aprendizado de Máquina para Segurança: Algoritmos e Aplicações
Sociedade Brasileira de …, 2019
[320] Attack Patterns on IoT devices using Honey Net Cloud
International Journal of Innovative Technology and Exploring Engineering, 2019
[321] Identifying Ransomware-Specific Properties using Static Analysis of Executables
IJARCCE, 2019
[322] Topic Modeling of Significant Concepts and Terminologies in Cybersecurity and Data Science and Their Potential Guidance to Seed Future Research Direction
2019
[323] AN ENSEMBLE-BASED ANOMALY-BEHAVIOURAL CRYPTO-RANSOMWARE PRE-ENCRYPTION DETECTION MODEL
2019
[324] 车联网安全综述
… of Cyber Security 信息安全学报, 2019
[325] Multimodal approach for malware detection
2019
[326] Hiding a fault enabled virus through code construction
2019
[327] Malware Classification Using Machine Learning Algorithms and Tools
2019
[328] Learning Malware Representation based on Execution Sequences
2019
[329] Permission based Android Malicious Application Detection using Machine Learning
2019
[330] Security Operations & Incident Management Knowledge Area Issue.
2019
[331] Survey of machine learning techniques for malware analysis
2019
[332] Intelligent Behavior-based Ransomware Detection System for Android Platform
2019
[333] Malware Detection on Highly Imbalanced Data through Sequence Modeling
2019
[334] Dampak Malware Berdasarkan Api Call Network Dengan Metode Heuristic Detection
2019
[335] 恶意代码演化与溯源技术研究
2019
[336] Теорія та практика створення розподілених систем виявлення зловмисного програмного забезпечення в локальних комп'ютерних мережах
2019
[337] Malware Classification using Deep Learning based Feature Extraction and Wrapper based Feature Selection Technique
2019
[338] An Ensemble-Based Malware Detection Model Using Minimum Feature Set
2019
[339] K-Means Clustering Analysis Based on Adaptive Weights for Malicious Code Detection
2019
[340] Intelligent Windows Malware Type Detection based on Multiple Sources of Dynamic Characteristics
2019
[341] Analisis Malware Berdasarkan Api Call Memory Dengan Metode Deteksi Signature-based
2019
[342] Behavioral Malware Detection Using Deep Graph Convolutional Neural Networks
2019
[343] Effective and Light-Weight Deobfuscation and Semantic-Aware Attack Detection for PowerShell Scripts
2019
[344] Homology analysis of malware based on ensemble learning and multifeatures
2019
[345] Metamorphic malicious code behavior detection using probabilistic inference methods
2019
[346] ATMPA: Attacking Machine Learning-based Malware Visualization Detection Methods via Adversarial Examples
2019
[347] An Improved Method for Packed Malware Detection using PE Header and Section Table Information
2019
[348] Intelligent Malware Detection Using File-to-file Relations and Enhancing its Security against Adversarial Attacks
2019
[349] ScriptNet: Neural Static Analysis for Malicious JavaScript Detection
2019
[350] Comparative Analysis of Ensemble Methods for Classification of Android Malicious Applications
2019
[351] Revisão Sistemática da Literatura das Técnicas baseadas em Texturas para Classificação de Malware
2019
[352] Building a Scalable Simulation Platform for Prototyping Distributed Machine Learning Solutions
2019
[353] Tietoverkkouhat ja niiltä suojautuminen yritysverkossa
2019
[354] 18 Displacing big data
2019
[355] Malware attack and Malware Analysis: A Research
2019
[356] Mimicking Anti-Viruses with Machine Learning and Entropy Profiles
2019
[357] Dynamic Malware Analysis in the Modern Era—A State of the Art Survey
2019
[358] Current State and Modeling of Research Topics in Cybersecurity and Data Science
SYSTEMICS, CYBERNETICS AND INFORMATICS, 2019
[359] Understanding Fileless Attacks on Linux-based IoT Devices with HoneyCloud
2019
[360] AN EMPIRICAL STUDY ON CYBER SECURITY THREATS AND ATTACKS
International Journal of Scientific Research and Review, 2019
[361] Application of subspace clustering to scalable malware clustering
2019
[362] A Semi-supervised Learning Methodology for Malware Categorization using Weighted Word Embeddings
2019
[363] MDBA: Detecting Malware based on Bytes N-Gram with Association Mining
2019
[364] A robust and secure backup system for protecting malware
2019
[365] Optimal remote access trojans detection based on network behavior
2019
[366] Similarity-based Intelligent Malware Type Detection through Multiple Sources of Dynamic Characteristics
2019
[367] Tagging Malware Intentions by Using Attention-Based Sequence-to-Sequence Neural Network
2019
[368] Cyber Security Threats Detection in Internet of Things Using Deep Learning Approach
2019
[369] Investigating IoT malware characteristics to improve network security
2019
[370] Detection of Malicious Activities in Internet of Things Environment Based on Binary Visualization and Machine Intelligence
2019
[371] Malware Squid: A Novel IoT Malware Traffic Analysis Framework Using Convolutional Neural Network and Binary Visualisation
2019
[372] CapJack: Capture In-Browser Crypto-jacking by Deep Capsule Network through Behavioral Analysis
2019
[373] Generalized Learning Models for Structured Data
2019
[374] An Efficient Botnet Detection Methodology using Hyper-parameter Optimization Trough Grid-Search Techniques
2019
[375] Discovering Future Malware Variants By Generating New Malware Samples Using Generative Adversarial Network
2019
[376] A Survey on Preventing Crypto Ransomware Using Machine Learning
2019
[377] An Intelligent Behavior-Based Ransomware Detection System For Android Platform
2019
[378] Effective Malicious Features Extraction and Classification for Incident Handling Systems
2019
[379] A contempory Taxonomy of Banking Malware
2019
[380] Applications of data analytics and machine learning tools to the enhanced design of modern communication networks and security applications
2019
[381] Discovering Programmer Intention Behind Written Source Code
2019
[382] Network Behavioral Analysis for Detection of Remote Access Trojans
2019
[383] Malware detection in security operation centres
2019
[384] A Digital Forensic Readiness Approach for Ransomware Forensics
2019
[385] Malwares: Creation and Avoidance
2019
[386] Behavioral Entropy Towards Detection of Metamorphic Malwares
2019
[387] Behavioral-based malware clustering and classification
2019
[388] DEEP LEARNING FOR MALWARE DETECTION IN NETWORK TRAFFIC
2019
[389] Embedding Advanced Persistent Threat in Steganographic Images
2019
[390] An Improved Method for Packed Malware Detection using PE Header and Section Table Information.
2019
[391] Detection of Algorithmically Generated Malicious Domain Names using Masked N-Grams
2019
[392] Mal-Flux: Rendering hidden code of packed binary executable
2019
[393] A Close Look at a Daily Dataset of Malware Samples
2019
[394] Malware Capability Assessment using Fuzzy Logic
2019
[395] Detecting indicators of deception in emulated monitoring systems
2019
[396] Malicious code detection based on CNNs and multi-objective algorithm
2019
[397] Malware intelligence: beyond malware analysis
2019
[398] Accelerating convolutional neural network-based malware traffic detection through ant-colony clustering
Journal of Intelligent & Fuzzy Systems, 2019
[399] Byte Label Malware Classification Using Image Entropy
2019
[400] 程序逆向分析在软件供应链污染检测中的应用
2019
[401] Classi cation and static detection of obfuscated web application backdoors
2018
[402] Automatic Malware Signature Generation
2018
[403] Challenges of Malware Analysis: Obfuscation Techniques
2018
[404] Malware Detection: An Investigation Into the Deployment ofArtificial Intelligence for Antimalware Solutions
2018
[405] DLGraph: Malware Detection Using Deep Learning and Graph Embedding
2018
[406] Dynamic API call Sequence Visualization for Malware classification
2018
[407] Methodology for Malware Classification using a Random Forest Classifier
2018
[408] Malware-Detection Model Using Learning-Based Discovery of Static Features
2018
[409] Analisis Klasterisasi Malware: Evaluasi Data Training Dalam Proses Klasifikasi Malware
2018
[410] The Effect on Network Flows-Based Features and Training Set Size on Malware Detection
2018
[411] DeepMal4J: Java Malware Detection Employing Deep Learning
2018
[412] Deep Learning and Visualization for Identifying Malware Families
2018
[413] Large scale machine learning for the detection and classification of malware
2018
[414] Malware identification using visualization images and deep learning
Computers & Security, 2018
[415] MalClassifier: Malware family classification using network flow sequence behaviour
2018
[416] Need for Speed: Analysis of Brazilian Malware Classifiers' Expiration Date
Thesis, 2018
[417] Feature Engineering for Machine Learning and Data Analytics
Feature Engineering for Machine Learning and Data Analytics, 2018
[418] Критерії класифікації методів виявлення шкідливого програмного забезпечення
2018
[419] KOSIGN: 정보보호제품 관점의 사이버위협정보 공유 체계
REVIEW OF KIISC, 2018
[420] Ransomware threat success factors, taxonomy, and countermeasures: A survey and research directions
Computers & Security, 2018
[421] Can Ternary Computing Improve Information Assurance?
Cryptography, 2018
[422] Analisis dan Deteksi Malware Menggunakan Metode Malware Analisis Dinamis dan Malware Analisis Statis
2018
[423] Clustering Morphed Malware using Opcode Sequence Pattern Matching
Recent Patents on Engineering, 2018
[424] Preliminaries and overview
2018
[425] MALWARE DETECTION AND CLASSIFICATION USING MACHINE LEARNING TECHNIQUES
2018
[426] Dynamic Detection Methods
The Huawei and Snowden Questions, 2018
[427] Evaluation of Cisco's Virtual Internet Routing Lab (VIRL) as a Cyber Security Research Tool
2018
[428] Adversarial Examples: Attacks on Machine Learning-based Malware Visualization Detection Methods
2018
[429] Evaluation and Design of Robust Neural Network Defenses
2018
[430] Adaptive flow abnormity identification based on information entropy
Concurrency and computation: practice and experience, 2018
[431] Deep learning at the shallow end: Malware classification for non-domain experts
Digital Investigation, 2018
[432] 가중치 그래프 변환을 통한 네트워크 행위 추상화 기반의 랜섬웨어 분류 모델 제안
Korea Computer Congress 2018, 2018
[433] Zloraba kombinacije obratnega inženirstva, prikrivanja, ukan in varnostnih ranljivosti
2018
[434] Multinomial malware classification via low-level features
Digital Investigation, 2018
[435] Modeling Malware as a Language
2018
[436] The Rough Set Analysis for Malicious Web Campaigns Identification
Image Processing and Communications Challenges 10, 2018
[437] Deep Learning in Information Security
2018
[438] 사이버 위협 정보의 공유 활성화 방안
The Journal of The Korean Institute of Communication Sciences, 2018
[439] Challenge of Malware Analysis: Malware obfuscation Techniques
2018
[440] Malware classification using byte sequence information
RACS 2018 Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems, 2018
[441] A Survey on Malware Analysis Techniques: Static, Dynamic, Hybrid and Memory Analysis
2018
[442] Behavioral-Based Classification and Identification of Ransomware Variants Using Machine Learning
2018
[443] MINING PATTERNS OF SEQUENTIAL MALICIOUS APIS TO DETECT MALWARE
International Journal of Network Security & Its Applications, 2018
[444] Using convolutional neural networks for classification of malware represented as images
Journal of Computer Virology and Hacking Techniques, 2018
[445] Picking on the family: Disrupting android malware triage by forcing misclassification
Expert Systems with Applications, 2018
[446] Malware classification using self organising feature maps and machine activity data
Computers & Security, 2018
[447] A Theoretical Feature-wise Study of Malware Detection Techniques≫
2018
[448] “L'EXTINCTION EST LA RÈGLE, LA SURVIE EST L'EXCEPTION”: REGROUPEMENT DE MALICIELS SELON LEURS COMPORTEMENTS
2018
[449] A Theoretical Feature-wise Study of Malware Detection Techniques
2018
[450] Survey on mobile malware analysis and detection
2018
[451] Oliveira
2018
[452] An Integrated Architecture for IoT Malware Analysis and Detection
2018
[453] First Line Defense Against Spreading New Malware in the Network
2018
[454] ULBP-RF: A Hybrid Approach for Malware Image Classification
2018
[455] Opcode and Gray Scale Techniques for Classification of Malware Binaries
2018
[456] Displacing big data: How criminals cheat the system
2018
[457] MACHINE LEARNING METHODS FOR MALWARE DETECTION AND CLASSIFICATION
2018
[458] 2-Dimension 정적 Feature Set 이 적용된 Convolutional Neural Network 기반의 악성코드 패킹 분석
2018
[459] CLUSTERING MALWARE’S NETWORK BEHAVIOR USING SIMPLE SEQUENTIAL FEATURES
Thesis, 2018
[460] An Android Malware Detection Technique Using Optimized Permission and API with PCA
2018
[461] Feature extraction for enhanced malware detection using genetic algorithm
2018
[462] Are we protected yet? developing a machine learning detection system to combat zero-day malware attacks
2018
[463] Advancing neuro-fuzzy algorithm for automated classification in largescale forensic and cybercrime investigations: adaptive machine learning for big data …
2018
[464] Analysis and improvements of behaviour-based malware detection mechanisms
2018
[465] A malware risk analysis and detection system for mobile devices using permission-based features/Mohd Faizal Ab Razak
2018
[466] Malware Detection: An Investigation Into the Deployment of Artificial Intelligence for Antimalware Solutions
2018
[467] Malware Detection via Machine Learning
2018
[468] A Malware Risk Analysis and Detection System for Mobile Devices Using Permissionbased Features
2018
[469] Crypto-Ransomware Detection through the Use of k-Nearest Neighbor Machine Learning Algorithm
2018
[470] Rule Creation in a Knowledge-assisted Visual Analytics Prototype for Malware Analysis.
Forum Media …, 2017
[471] 基于机器学习的自动化恶意代码分类与新恶意代码检测技术
Frontiers, 2017
[472] Malware Classification into Families Based on File Contents and Characteristics
2017
[473] Avaliação da Eficácia de Classificadores de Malware ao Longo do Tempo
2017
[474] Hidden-Code Extraction From Packed Malware Using Memory Based Dynamic Analysis
2017
[475] Survey on representation techniques for malware detection system
2017
[476] A semi supervised hybrid protection for network and host based attacks
2017
[477] The effect of code obfuscation on authorship attribution of binary computer files
2017
[478] A Brief Survey on Sandboxing Techniques and It's vulnerabilities
2017
[479] The goods, the bads and the uglies: Supporting decisions in malware detection through visual analytics
2017
[480] Low-Complexity Signature-Based Malware Detection for IoT Devices
Applications and Techniques in Information Security, 2017
[481] Feature Engineering for Twitter-based Applications
2017
[482] Feature Selection and Improving Classification Performance for Malware Detection
2017
[483] A Framework for Generating Malware Threat Intelligence
2017
[484] Malware Fingerprinting under Uncertainty
2017
[485] A Survey on Malware Detection Using Data Mining Techniques
ACM Computing Surveys (CSUR), 2017
[486] A Planner for Supporting Countermeasures in Large Scale Cyber Attacks
Complex, Intelligent, and Software Intensive Systems, 2017
[487] A Framework for Recognition and Confronting of Obfuscated Malwares Based on Memory Dumping and Filter Drivers
Wireless Personal Communications, 2017
[488] Pattern Extraction Algorithm for Netflow-Based Botnet Activities Detection
Hindawi Security and Communication Networks, 2017
[489] Supporting knowledge-assisted rule creation in a behavior-based malware analysis prototype
2017
[490] A Malware Detection Method Based on Sandbox, Binary Instrumentation and Multidimensional Feature Extraction
Advances on Broad-Band Wireless Computing, Communication and Applications, 2017
[491] Survey on the Usage of Machine Learning Techniques for Malware Analysis
2017
[492] Rule Creation in a Knowledge-assisted Visual Analytics Prototype for Malware Analysis
2017
[493] Malware Detection by HTTPS Traffic Analysis
2017
[494] Data Mining Classification Approaches for Malicious Executable File Detection
2017
[495] Investigation into the Risks Facing Mobile Banking: A Case of Commercial Banks in Kenya
2017
[496] Virtual Machine Introspection Based Malware Behavior Profiling and Family Grouping
2017
[497] A Comparative Overview of Malware Analysis across Operating Systems
ProQuest Dissertations Publishing, 2017
[498] Statistical Evaluation of Malware Classification Algorithms
2017
[499] Malware Detection and Analysis
International Journal of Advanced Research in Computer Science, 2017
[500] Predicting SMT solver performance for software verification
2017
[501] Classification of Malware programs using autoencoders based deep learning architecture and its application to the microsoft malware Classification challenge (BIG …
2017
[502] A Cloud-Based Intelligent and Energy Efficient Malware Detection Framework. A Framework for Cloud-Based, Energy Efficient, and Reliable Malware Detection in …
2017
[503] The Rise of Ransomware
ICSEB 2017 Proceedings of the 2017 International Conference on Software and e-Business, 2017
[504] Analisis Malware Botnet Proteus Pendekatan Static dan Dinamic
2017
[505] Deep Learning Approach to Malware Multi-class Classification Using Image Processing Techniques
2017
[506] A cloud-based intelligent and energy efficient malware detection framework: a framework for cloud-based, energy efficient, and reliable malware detection in real-time …
2017
[507] COMPUTER IMPLEMENTED METHOD FOR CLASSIFYING MOBILE APPLICATIONS AND COMPUTER PROGRAMS THEREOF
2016/01/21/
[508] Análisis digital de una infección de malware en sistemas windows
2016
[509] Malware Characterization Using Windows API Call Sequences
Security, Privacy, and Applied Cryptography Engineering, 2016
[510] Automatic malware classification and new malware detection using machine learning
2016
[511] A three-way decision making approach to malware analysis using probabilistic rough sets
Information Sciences, 2016
[512] Introduction to Malware and Malware Analysis: A brief overview
2016
[513] ClusterMal: Automated Malware Analysis with clustering, anomaly detection and classification of existing and new behavioral analysis
2016
[514] A software classification scheme using binary-level characteristics for efficient software filtering
Soft Computing, 2016
[515] Improving the detection accuracy of unknown malware by partitioning the executables in groups
Advanced Computing and Communication Technologies, 2016
[516] Malware Analysis and Classification Using Sequence Alignments
Intelligent Automation & Soft Computing, 2016
[517] An Effective Approach for Classification of Advanced Malware with High Accuracy
International Journal of Security and Its Applications, 2016
[518] MOBİL KÖTÜCÜL YAZILIMLAR VE GÜVENLİK ÇÖZÜMLERİ ÜZERİNE BİR İNCELEME
Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 2016
[519] Identifying malicious activities from system execution traces
2016
[520] A Data Mining Classification Approach for Behavioral Malware Detection
Journal of Computer Networks and Communications, 2016
[521] On the impact of warning interfaces for enabling the detection of Potentially Unwanted Applications
2016
[522] The rise of “malware”: Bibliometric analysis of malware study
Journal of Network and Computer Applications, 2016
[523] Scalable malware classification with multifaceted content features and threat intelligence
2016
[524] A Spatio-Temporal malware and country clustering algorithm: 2012 IIJ MITF case study
International Journal of Information Security, 2016
[525] Equitable Machine Learning Algorithms to Probe Over P2P Botnets
Proceedings of the 4th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA) 2015, 2016
[526] Tools & Techniques for Malware Analysis and Classification.
International Journal of Next-Generation Computing, 2016
[527] A mining approach for detecting unknown malware using N-Gram and SVM
Advances in Natural and Applied Sciences, 2016
[528] Malware Threat Assessment Using Fuzzy Logic Paradigm
Journal of Adhesion Science and Technology, 2016
[529] Malware Variant Detection Using Opcode Image Recognition with Small Training Sets
2016
[530] A malware variants detection methodology with an opcode based feature method and a fast density based clustering algorithm
2016
[531] Automated intelligent multinomial classification of malware species using dynamic behavioural analysis
2016
[532] IRMD: Malware Variant Detection Using Opcode Image Recognition
2016
[533] Flow-Graph and Markovian Methods for Cyber Security Analysis
International Journal of Enterprise Information Systems (IJEIS), 2016
[534] Convolutional neural networks for malware classification
2016
[535] Pattern Recognition for Computer Security:Discriminative Models for Email Spam Campaign andMalware Detection
2016
[536] A resource management system design for malware behavior detection
2016
[537] Taxonomy of malware detection techniques
2016
[538] Review of Data Mining Techniques for Malicious Detection
2016
[539] Zero-day malware detection
2016
[540] Σύγχρονα εργαλεία, τεχνικές και μεθοδολογίες για τον χαρακτηρισμό κυβερνοεπιθέσεων και κακόβουλου λογισμικού
2016
[541] An android malware detection system based on cloud computing
2016
[542] Analysis of Rank Distance for Malware Classification
Dissertation, University of Cincinnati, 2016
[543] Taxonomy of malware detection techniques: A systematic literature review
2016
[544] An Approach for Malware Detection and Predictive Analysis Using Artificial Neural Networks
2016
[545] Towards an effective and efficient malware detection system
2016
[546] Pattern recognition for computer security: discriminative models for email spam campaign and malware detection
2016
[547] Pattern recognition for computer security
2016
[548] Weary Giants of Flesh and Steel: Three Articles on the State and Information Security
2016
[549] Loan Approval Prediction based on Machine Learning Approach
2016
[550] Review of data mining techniques for malicious detetion
2016
[551] Tools & techniques for malware analysis and classification
… Journal of Next …, 2016
[552] Research Article A Data Mining Classification Approach for Behavioral Malware Detection
2016
[553] A Study on Selecting Key Opcodes for Malware Classification and Its Usefulness
2015
[554] Online Manuscript Access
2015
[555] Enhanced Analysis of Kippo-honeypot in Cloud
Thesis, 2015
[556] Efficient Detection of Zero-day Android Malware Using Normalized Bernoulli Naive Bayes
2015
[557] Détection des rootkits niveau noyau basée sur LTTng
2015
[558] VISO: Characterizing Malicious Behaviors of Virtual Machines with Unsupervised Clustering
2015
[559] Improved Naive Bayes Classifier for Android Malware Classification
2015
[560] Detecting and Classifying Morphed Malwares: A Survey
International Journal of Computer Applications, 2015
[561] A Three-Way Decision Making Approach to Malware Analysis
Rough Sets and Knowledge Technology, 2015
[562] A Novel Approach to Malware Detection using Static Classification
International Journal of Computer Science and Information Security, 2015
[563] 악성코드 분류를 위한 중요 연산부호 선택 및 그 유용성에 관한 연구
정보과학회논문지, 2015
[564] Measuring Malware Evolution
2015
[565] Deep Neural Network Based Malware Detection Using Two Dimensional Binary Program Features
arXiv preprint arXiv:1508.03096, 2015
[566] Comparative Analysis of Feature Extraction Methods of Malware Detection
International Journal of Computer Applications, 2015
[567] A Dynamic Malware Analysis for Windows Platform-A Survey
Indian Journal of Science and Technology, 2015
[568] Computational Techniques for Predicting Cyber Threats
Intelligent Computing, Communication and Devices. Springer India, 2015
[569] Malicious Behavior Detection using Windows Audit Logs
arXiv preprint arXiv:1506.04200, 2015
[570] Spectral Malware Behavior Clustering
2015
[571] Malware analysis and classification using Artificial Neural Network
2015
[572] Reverse Engineering For Malware Analysis: Dissecting The Novel Banking Trojan ZeusVM
2015
[573] Quantifying Malware Evolution through Archaeology
Journal of Information Security, 2015
[574] Milware: Identification and Implications of State Authored Malicious Software
Proceedings of the 2015 New Security Paradigms Workshop, 2015
[575] روش تشخیص بدافزار مبتنی بر تحلیل ایستای ساختار PE‎
علوم و فناوريهاي پدافند نوین, 2014
[576] 효율적인 악성코드 분류를 위한 최적의 API 시퀀스 길이 및 조합 도출에 관한 연구
정보보호학회논문지, 2014
[577] 以決策樹偵測殭屍網路之研究
2014
[578] Integrated Framework for Classification of Malwares
Proceedings of the 7th International Conference on Security of Information and Networks, 2014
[579] Classification of PE Files using Static Analysis
Proceedings of the 7th International Conference on Security of Information and Networks, 2014
[580] Agent-based trace learning in a recommendation-verification system for cybersecurity
Malicious and Unwanted Software: The Americas (MALWARE), 2014 9th International Conference on, 2014
[581] A study on extraction of optimized API sequence length and combination for efficient malware classification
2014
[582] 효율적인 악성코드 분류를 위한최적의 API 시퀀스 길이 및 조합 도출에 관한 연구
2014
[583] Understanding IoT Security with HoneyCloud
Content Distribution for Mobile Internet: A …, 2012
[584] Survey of Malware Detection Techniques
2007
[585] Modern Loan Approval Prediction System Based on Machine Learning
MS KASAR, S BVCOEW, VP MULIK
[586] ISSN MEDIA
TA Cahyanto, V Wahanggara
[587] SIMULASI SISTEM MULTIPLE HONEYPOT DAN STANDARISASI MALWARE ANALYSIS DENGAN DYNAMIC ANALYSIS MENGGUNAKAN LAYANAN …
A Wicaksono
[588] MINISTÉRIO DA DEFESA EXÉRCITO BRASILEIRO DEPARTAMENTO DE CIÊNCIA E TECNOLOGIA INSTITUTO MILITAR DE ENGENHARIA PROGRAMA DE …
[589] Jurnal Jaringan Komputer dan Keamanan
[590] ESTUDO COMPARATIVO ENTRE MODELOS BASEADOS EM BERT NA CLASSIFICAÇÃO ESTÁTICA DE MALWARE
[591] A Technique for Dynamic Malware Detection through Application Programming Interface (API) Calls
[592] Hancitor malware recognition using swarm intelligent
[593] MACHINE LEARNING FOR CYBERSECURITY: IMPLEMENTATION OF MALWARE DETECTION USING PE FILE, N-GRAMS AND DEEP LEARNING ON …
[594] Malexlnet: A Semantic Analysis and Detection Method of Malware Api Sequence Based on Exlnet Model
[595] Identificación de" malware" perteneciente a ataques APT mediante la selección de características altamente discriminatorias usando técnicas de" Machine Learning"
[596] Detection of Malware by Static Analysis Using Machine Learning Methods
[597] EXTENDED A
Follow SCIRP
Twitter Facebook Linkedin Weibo
Contact us
customer@scirp.org
WhatsApp +86 18163351462(WhatsApp)
Click here to send a message to me 1655362766
Paper Publishing WeChat
Free SCIRP Newsletters
Copyright © 2006-2025 Scientific Research Publishing Inc. All Rights Reserved.
Top