A State of the Art Survey on Polymorphic Malware Analysis and Detection Techniques

Nowadays, systems are under serious security threats caused by malicious software, commonly known as malware. Such malwares are sophisticatedly created with advanced techniques that make them hard to analyse and detect, thus causing a lot of damages. Polymorphism is one of the advanced techniques by which malware change their identity on each time they attack. This paper presents a detailed systematic and critical review that explores the available literature, and outlines the research efforts that have been made in relation to polymorphic malware analysis and their detection.

[1]  Dimitris Gritzalis,et al.  Practical Malware Analysis: The Hands-On Guide to Dissecting Malicious Software , 2012, Comput. Secur..

[2]  Fakariah Hani Mohd Ali,et al.  Polymorphic Malware Detection , 2016, 2016 6th International Conference on IT Convergence and Security (ICITCS).

[3]  Maninder Singh,et al.  Efficient hybrid technique for detecting zero-day polymorphic worms , 2014, 2014 IEEE International Advance Computing Conference (IACC).

[4]  Divya Bansal,et al.  A Novel Approach to Malware Detection using Static Classification , 2015 .

[5]  M. P. Wankhade,et al.  Malware and Malware Detection Techniques : A Survey , 2013 .

[6]  Ajit Narayanan,et al.  A Syntactic Approach for Detecting Viral Polymorphic Malware Variants , 2016, PAISI.

[7]  nbspParvinder Kaur,et al.  An Advanced Approach to Polymorphic/Metamorpic Malware Detection using Hybrid Clustering Approach , 2016 .

[8]  YUDI PRAYUDI,et al.  THE RECOGNIZE OF MALWARE CHARACTERISTICS THROUGH STATIC AND DYNAMIC ANALYSIS APPROACH AS AN EFFORT TO PREVENT CYBERCRIME ACTIVITIES , 2015 .

[9]  Guojun Wang,et al.  Event Detection Through Differential Pattern Mining in Cyber-Physical Systems , 2020, IEEE Transactions on Big Data.

[10]  Ali Selamat,et al.  A Survey on Malware and Malware Detection Systems , 2013 .

[11]  Incheol Shin,et al.  Efficient Methods to Trigger Adversarial Behaviors from Malware during Virtual Execution in SandBox , 2015 .

[12]  Md. Rafiqul Islam,et al.  A Hybrid Wrapper-Filter Approach for Malware Detection , 1969, J. Networks.

[13]  Yudi Prayudi,et al.  Implementation of Malware Analysis using Static and Dynamic Analysis Method , 2015 .

[14]  Swapnaja Hiray,et al.  Comparative Analysis of Feature Extraction Methods of Malware Detection , 2015 .

[15]  蒂默·哈莫宁.  Identifying polymorphic malware , 2011 .

[16]  Al-Sakib Khan Pathan,et al.  Detecting Zero-day Polymorphic Worms with Jaccard Similarity Algorithm , 2016, Int. J. Commun. Networks Inf. Secur..

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

[18]  Xing Li,et al.  Thwarting Zero-Day Polymorphic Worms With Network-Level Length-Based Signature Generation , 2010, IEEE/ACM Transactions on Networking.

[19]  Laura Gheorghe,et al.  Practical malware analysis based on sandboxing , 2014, 2014 RoEduNet Conference 13th Edition: Networking in Education and Research Joint Event RENAM 8th Conference.

[20]  Tyler Moore,et al.  Polymorphic Malware Detection Using Sequence Classification Methods , 2016, 2016 IEEE Security and Privacy Workshops (SPW).

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

[22]  Mansour Ahmadi,et al.  Malware detection by behavioural sequential patterns , 2013 .

[23]  James B. Fraley,et al.  Polymorphic malware detection using topological feature extraction with data mining , 2016, SoutheastCon 2016.

[24]  Bimal Kumar Mishra,et al.  PolyS: Network-based Signature Generation for Zero-day Polymorphic Worms , 2013 .

[25]  Guanghui Liang,et al.  A Behavior-Based Malware Variant Classification Technique , 2016 .

[26]  Bimal Kumar Mishra,et al.  Survey of Polymorphic Worm Signatures , 2014 .

[27]  Ajit Narayanan,et al.  Using different substitution matrices in a string-matching technique for identifying viral polymorphic malware variants , 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

[28]  B. M. Mehtre,et al.  Performance of malware detection tools: A comparison , 2014, 2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies.

[29]  Kaushal R. Bhavsar,et al.  Techniques for Malware Analysis , 2020 .

[30]  T. Vinay Kumar M. Tech.  Malwise-An Effective and Efficient Classification System for Packed and Polymorphic Malware , 2014 .

[31]  Sungjin Lee.  New Malware Analysis Method on Digital Forensics , 2015 .

[32]  Carsten Willems,et al.  Automatic analysis of malware behavior using machine learning , 2011, J. Comput. Secur..

[33]  Mehdi Shajari,et al.  Automatic signature generation for polymorphic worms by combination of token extraction and sequence alignment approaches , 2015, 2015 7th Conference on Information and Knowledge Technology (IKT).

[34]  Maninder Singh,et al.  Behavior analysis of malware using machine learning , 2015, 2015 Eighth International Conference on Contemporary Computing (IC3).

[35]  G. Aghila,et al.  A learning model to detect maliciousness of portable executable using integrated feature set , 2017, J. King Saud Univ. Comput. Inf. Sci..

[36]  Shi-Jinn Horng,et al.  A Static Malware Detection System Using Data Mining Methods , 2013, ArXiv.

[37]  Serge Chaumette,et al.  Automated extraction of polymorphic virus signatures using abstract interpretation , 2011, 2011 5th International Conference on Network and System Security.

[38]  Tyler Moore,et al.  Polymorphic malware detection using sequence classification methods and ensembles , 2017, EURASIP J. Inf. Secur..

[39]  Maninder Singh,et al.  A Survey on Zero-Day Polymorphic Worm Detection Techniques , 2014, IEEE Communications Surveys & Tutorials.

[40]  Wilson Jeberson,et al.  A LITERATURE REVIEW ON MALWARE AND ITS ANALYSIS , 2013 .

[41]  Ajit Narayanan,et al.  Needleman-Wunsch and Smith-Waterman Algorithms for Identifying Viral Polymorphic Malware Variants , 2016, 2016 IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech).

[42]  Dolly Uppal,et al.  Basic survey on Malware Analysis, Tools and Techniques , 2014 .