Evolution and Detection of Polymorphic and Metamorphic Malwares: A Survey

Malwares are big threat to digital world and evolving with high complexity. It can penetrate networks, steal confidential information from computers, bring down servers and can cripple infrastructures etc. To combat the threat/attacks from the malwares, anti- malwares have been developed. The existing anti-malwares are mostly based on the assumption that the malware structure does not changes appreciably. But the recent advancement in second generation malwares can create variants and hence posed a challenge to anti-malwares developers. To combat the threat/attacks from the second generation malwares with low false alarm we present our survey on malwares and its detection techniques.

[1]  Guido Bertoni,et al.  Keccak sponge function family main document , 2009 .

[2]  Nhat-Phuong Tran,et al.  High performance string matching for security applications , 2013, International Conference on ICT for Smart Society.

[3]  Mark Stamp,et al.  Hunting for metamorphic engines , 2006, Journal in Computer Virology.

[4]  Subariah Ibrahim,et al.  Morphed Virus Family Classification Based on Opcodes Statistical Feature Using Decision Tree , 2011 .

[5]  Suhaimi Ibrahim,et al.  Evolution of Computer Virus Concealment and Anti-Virus Techniques: A Short Survey , 2011, ArXiv.

[6]  Sattar Hashemi,et al.  A General Paradigm for Normalizing Metamorphic Malwares , 2012, 2012 10th International Conference on Frontiers of Information Technology.

[7]  Abhishek Shah,et al.  Approximate Disassembly using Dynamic Programming , 2010 .

[8]  Philippe Beaucamps.  Advanced Polymorphic Techniques , 2007 .

[9]  Young H. Cho,et al.  High-Performance Context-Free Parser for Polymorphic Malware Detection , 2005 .

[10]  Nick Del Grosso.  Its Time to Rethink your Corporate Malware Strategy , 2015 .

[11]  Lior Rokach,et al.  Detection of unknown computer worms based on behavioral classification of the host , 2008, Comput. Stat. Data Anal..

[12]  Kangbin Yim,et al.  Malware Obfuscation Techniques: A Brief Survey , 2010, 2010 International Conference on Broadband, Wireless Computing, Communication and Applications.

[13]  John C. S. Lui,et al.  Droid Analytics: A Signature Based Analytic System to Collect, Extract, Analyze and Associate Android Malware , 2013, 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications.

[14]  Kirti Mathur,et al.  A Survey on Techniques in Detection and Analyzing Malware , 2013 .

[15]  Aditya Govindaraju.  Exhaustive Statistical Analysis for Detection of Metamorphic Malware , 2010 .

[16]  Peter Szor,et al.  HUNTING FOR METAMORPHIC , 2001 .

[17]  A.H. Sung,et al.  Polymorphic malicious executable scanner by API sequence analysis , 2004, Fourth International Conference on Hybrid Intelligent Systems (HIS'04).

[18]  Richard Stone.  A call to cyber arms. , 2013, Science.

[19]  Suhaimi Ibrahim,et al.  Camouflage in Malware: from Encryption to Metamorphism , 2012 .

[20]  Mark Stamp,et al.  Exploring Hidden Markov Models for Virus Analysis: A Semantic Approach , 2013, 2013 46th Hawaii International Conference on System Sciences.

[21]  Joohan Lee,et al.  A survey of data mining techniques for malware detection using file features , 2008, ACM-SE 46.

[22]  Levente Buttyán,et al.  Duqu: A Stuxnet-like malware found in the wild , 2011 .

[23]  Tzi-cker Chiueh,et al.  Automatic Generation of String Signatures for Malware Detection , 2009, RAID.

[24]  Mark Stamp,et al.  Chi-squared distance and metamorphic virus detection , 2013, Journal of Computer Virology and Hacking Techniques.

[25]  Thomas G. Dietterich.  What is machine learning? , 2020, Archives of Disease in Childhood.

[26]  S. Katzenbeisser,et al.  Malware Normalization , 2005 .

[27]  Jian Xu,et al.  A similarity metric method of obfuscated malware using function-call graph , 2012, Journal of Computer Virology and Hacking Techniques.

[28]  Paul A. Watters,et al.  Zero-day Malware Detection based on Supervised Learning Algorithms of API call Signatures , 2011, AusDM.