Mobile Phishing Attacks and Mitigation Techniques

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Journal of Information Security

ISSN Print: 2153-1234
ISSN Online: 2153-1242
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Google-based Impact Factor: 3.79
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"Mobile Phishing Attacks and Mitigation Techniques"
written by Hossain Shahriar, Tulin Klintic, Victor Clincy,
published by Journal of Information Security, Vol.6 No.3, 2015

has been cited by the following article(s):

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CrossRef

[1]	In the Light and in the Shadows: Human-Centered Analysis in Cybercrime
	2022

[2]	Working from home users at risk of COVID-19 ransomware attacks
	Cybersecurity and Cognitive Science, 2022

[3]	Phishing and Advanced Persistent Threats
	Journal of Mathematical & …, 2022

[4]	Using Behavioral Profiling through Keystrokes Dynamics and Location Verification authentication as a Method of Securing Mobile Banking Transactions
	2021

[5]	An Analysis of Modern Password Manager Security and Usage on Desktop and Mobile Devices
	2021

[6]	Phishing prevention in mobile messaging platforms by the Dutch banking sector
	2021

[7]	Human Factors in Cybersecurity
	Journal: Research Anthology on Privatizing and …, 2021

[8]	The Current Phishing Techniques–Perspective of the Nigerian Environment
	World Journal of Innovative Research, 2021

[9]	Review on Mobile Attacks: Operating System, Threats and Solution
	2021

[10]	Preventing and Detecting State Inference Attacks on Android
	Network and Distributed Systems Security (NDSS) Symposium, 2021

[11]	DSmishSMS-A System to Detect Smishing SMS
	Neural Computing and Applications, 2021

[12]	The emperor's new autofill framework: a security analysis of autofill on iOS and Android
	Annual Computer Security Applications …, 2021

[13]	Let's go phishing: A phishing awareness campaign using smishing, email phishing, and social media phishing tools
	Proceedings of the …, 2021

[14]	A Study on the Digital Forensic Investigation Method of Clever Malware in IoT Devices
	2020

[15]	New hybrid framework to detect phishing web pages, based on rules and variant selection of features
	2020

[16]	The Human Attack Surface Framework for Phishing
	THESIS, 2020

[17]	Human Factors in Cybersecurity: Issues and Challenges in Big Data
	2020

[18]	Do not jail my app: Detecting the Android plugin environments by time lag contradiction
	2020

[19]	Smishing detector: A security model to detect smishing through SMS content analysis and url behavior analysis
	2020

[20]	Two-Factor Authentication Scheme for Mobile Money: A Review of Threat Models and Countermeasures
	2020

[21]	A Cost-Effective OCR Implementation to Prevent Phishing on Mobile Platforms
	2020

[22]	Characterizing Emerging Cybersecurity Threats: An Ecosystem Approach
	2020

[23]	Dangerous Skills: Understanding and Mitigating Security Risks of Voice-Controlled Third-Party Functions on Virtual Personal Assistant Systems
	2019 IEEE Symposium on Security and Privacy (SP), 2019

[24]	SMS Phishing and Mitigation Approaches
	2019

[25]	Mobile anti-phishing: Approaches and challenges
	2019

[26]	SuiT: Secure User Interface Based on TrustZone
	2019

[27]	A Study on the Use of Mobile-specific HTML5 WebAPI Calls on the Web
	2019

[28]	SMARTPHONE TRIGGERED SECURITY CHALLENGES-ISSUES, CASE STUDIES AND PREVENTION
	2019

[29]	A Content-Based Approach for Detecting Smishing in Mobile Environment
	2019

[30]	Mobile Phishing Websites Detection and Prevention Using Data Mining Techniques.
	2019

[31]	A Case-Based Reasoning Approach for Automatic Adaptation of Classifiers in Mobile Phishing Detection
	2019

[32]	Mobile Phishing Websites Detection and Prevention Using Data Mining Techniques
	2019

[33]	Non-invasive Privilege Escalation through Mobile and IoT System Interface: Threats and Mitigation
	ProQuest Dissertations Publishing, 2018

[34]	SmiDCA: An Anti-Smishing Model with Machine Learning Approach
	The Computer Journal, 2018

[35]	Understanding and Mitigating the Security Risks of Voice-Controlled Third-Party Skills on Amazon Alexa and Google Home
	2018

[36]	A survey about attack and defence phishing techniques
	2018

[37]	SNS Use, Risk, and Executive Behavior
	2018

[38]	Revealing the important features of mobile phishing
	2018

[39]	스미싱 공격 방지를 위한 클라우드 메시징 서비스
	2017

[40]	A Mobile-Based Phishing Detector App for E-Mails
	2017

[41]	Phishing Campaigns in Corporate Water
	2017

[42]	Cloud Messaging Service for Preventing Smishing Attack
	2017

[43]	A Mobile-Based Phishing Detector App for E-Mails.
	Computing & Information Systems, 2017

[44]	Unleashing the walking dead: Understanding cross-app remote infections on mobile webviews
	CCS 2017 Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, 2017

[45]	Comparative analysis of mobile phishing detection and prevention approaches
	Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 1, 2017

[46]	Mobile Phishing Detection using Naive Bayesian Algorithm
	2017

[47]	UnPhishMe: Phishing Attack Detection by Deceptive Login Simulation through an Android Mobile App
	2017

[48]	Analizando el nivel de seguridad del entorno de Android
	2016

[49]	Designing secure web and mobile-based information system for dissemination of students' examination results: the suitability of soft design science …
	International Journal of Computing and ICT Research, 2016

[50]	Phishing detection based on newly registered domains
	2016

[51]	CELLPOTS SEBAGAI ANTI-PHISING ATTACK PADA MOBILE CELLULAR NETWORK
	2016

[52]	Designing Secure Web and Mobile-Based Information System for Dissemination of Students' Examination Results: The Suitability of Soft Design Science …
	2016

[53]	MP-Shield: A Framework for Phishing Detection in Mobile Devices
	Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM), 2015 IEEE International Conference on, 2015

[1]	DSmishSMS-A System to Detect Smishing SMS Neural Computing and Applications, 2023 DOI:10.1007/s00521-021-06305-y

[2]	Phishing URL Detection Using Machine Learning: A Survey 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), 2022 DOI:10.1109/ICAC3N56670.2022.10074337

[3]	Cybersecurity and Cognitive Science 2022 DOI:10.1016/B978-0-323-90570-1.00001-2

[4]	The Emperor’s New Autofill Framework:A Security Analysis of Autofill on iOS and Android Annual Computer Security Applications Conference, 2021 DOI:10.1145/3485832.3485884

[5]	Research Anthology on Privatizing and Securing Data 2021 DOI:10.4018/978-1-7998-8954-0.ch082

[6]	DSmishSMS-A System to Detect Smishing SMS Neural Computing and Applications, 2021 DOI:10.1007/s00521-021-06305-y

[7]	The Emperor’s New Autofill Framework:A Security Analysis of Autofill on iOS and Android Annual Computer Security Applications Conference, 2021 DOI:10.1145/3485832.3485884

[8]	Two-Factor Authentication Scheme for Mobile Money: A Review of Threat Models and Countermeasures Future Internet, 2020 DOI:10.3390/fi12100160

[9]	A Study on the Digital Forensic Investigation Method of Clever Malware in IoT Devices IEEE Access, 2020 DOI:10.1109/ACCESS.2020.3043939

[10]	A PARALLEL AVERAGED NEURAL NETWORK APPROACH FOR DETECTING SMARTPHONE PHISHES JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES, 2020 DOI:10.26782/jmcms.2020.06.00008

[11]	Security, Privacy, and Forensics Issues in Big Data Advances in Information Security, Privacy, and Ethics, 2020 DOI:10.4018/978-1-5225-9742-1.ch003

[12]	Do not jail my app: Detecting the Android plugin environments by time lag contradiction Journal of Computer Security, 2020 DOI:10.3233/JCS-191325

[13]	Dangerous Skills: Understanding and Mitigating Security Risks of Voice-Controlled Third-Party Functions on Virtual Personal Assistant Systems 2019 IEEE Symposium on Security and Privacy (SP), 2019 DOI:10.1109/SP.2019.00016

[14]	SMS Phishing and Mitigation Approaches 2019 Twelfth International Conference on Contemporary Computing (IC3), 2019 DOI:10.1109/IC3.2019.8844920

[15]	Mobile anti-phishing: Approaches and challenges Information Security Journal: A Global Perspective, 2019 DOI:10.1080/19393555.2019.1691293

[16]	A Content-Based Approach for Detecting Smishing in Mobile Environment SSRN Electronic Journal , 2019 DOI:10.2139/ssrn.3356256

[17]	A Case-Based Reasoning Approach for Automatic Adaptation of Classifiers in Mobile Phishing Detection Journal of Computer Networks and Communications, 2019 DOI:10.1155/2019/7198435

[18]	SuiT: Secure User Interface Based on TrustZone ICC 2019 - 2019 IEEE International Conference on Communications (ICC), 2019 DOI:10.1109/ICC.2019.8761616

[19]	Cyber Security in Parallel and Distributed Computing 2019 DOI:10.1002/9781119488330.ch12

[20]	UnPhishMe: Phishing Attack Detection by Deceptive Login Simulation through an Android Mobile App 2017 12th Asia Joint Conference on Information Security (AsiaJCIS), 2017 DOI:10.1109/AsiaJCIS.2017.19

[21]	Unleashing the Walking Dead Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, 2017 DOI:10.1145/3133956.3134021

[22]	Unleashing the Walking Dead Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, 2017 DOI:10.1145/3133956.3134021

[23]	Phishing detection based on newly registered domains 2016 IEEE International Conference on Big Data (Big Data), 2016 DOI:10.1109/BigData.2016.7841036

[24]	MP-Shield: A Framework for Phishing Detection in Mobile Devices 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, 2015 DOI:10.1109/CIT/IUCC/DASC/PICOM.2015.293

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	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

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