Share This Article:

Design of Quantification Model for Ransom Ware Prevent

Full-Text HTML XML Download Download as PDF (Size:331KB) PP. 203-207
DOI: 10.4236/wjet.2015.33C030    6,147 Downloads   6,727 Views   Citations

ABSTRACT

The growth of ICT within the society has become increasingly digitized, thus, the overall activity has amounted to various researches for protecting any data from malicious threats. Recently, ransomware has been a rapidly propagated subject for social engineering techniques especially the ransomware. Users can delete a ransomeware code using an antivirus software code. However, the encrypted data would be impossible to recover. Therefore, ransomware must be prevented and must have early detection before it infects any data. In this paper, we are proposing a quantification model to prevent and detect any cryptographic operations in the local drive.

Cite this paper

Kim, D. and Kim, S. (2015) Design of Quantification Model for Ransom Ware Prevent. World Journal of Engineering and Technology, 3, 203-207. doi: 10.4236/wjet.2015.33C030.

References

[1] Han, B.J., Choi, Y.H. and Bae, B.C. (2013) Generating Malware DNA to Classify the Similar Malwares. Journal of the Korea Institute of Information Security & Cryptology, 23, 679-694. http://dx.doi.org/10.13089/JKIISC.2013.23.4.679
[2] Gazet, A. (2010) Comparative Analysis of Various Ransom-ware Virii. Journal in Computer Virology, 6, 77-90. http://dx.doi.org/10.1007/s11416-008-0092-2
[3] Dell Secure Works (2012) Anatomy of an Advanced Persistent Threat (APT).
[4] Smith, B. (2013) Cryptoviral Extortion.
[5] Shin, D., Kim, Y., Byun, K. and Lee, S. (2008) Data Hiding in Windows Executable Files. Australian Digital Forensics Conference, 51.
[6] Feguson, P. (2000) Network Ingress Filtering: Defeating Denial of Service Attacks Which Employ IP Source Address Spoofing. Ferguson 2000 Network.
[7] Nachenberg, C.S. (2012) Dynamic Heuristic Method for Detecting Computer Viruses Using Decryption Exploration and Evaluation Phases. U.S. Patent No. 6,357,008.
[8] Savage, S., Wetherall, D., Karlin, A. and Anderson, T. (2000) Practical Network Support for IP Traceback. ACM SIGCOMM Computer Communication Review, 30, 295-306. http://dx.doi.org/10.1145/347057.347560
[9] Aljifri, H. (2003) IP Traceback: A New Denial-of-Service Deterrent. IEEE Security & Privacy, 1, 24-31. http://dx.doi.org/10.1109/MSECP.2003.1203219
[10] Park, K. and Lee, H. (2001) On the Effectiveness of Probabil-istic Packet Marking for IP Traceback under Denial of Service Attack. Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies, 1, 338-347.

  
comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.