V. S. Subrahmanian, et al, “Types of Malware and Malware Distribution Strategies,” The Global Cyber-Vulnerability Report, Springer International Publishing, pp. 33-46, 2015.##
|
A. Moser, K. Christopher, and K. Engin, “Exploring multiple execution paths for malware analysis,” Security and Privacy, 2007. SP’07. IEEE Symposium on. IEEE, 2007.##
|
D. Brumley, et al, “Automatically identifying trigger-based behavior in malware,” Botnet Detection, pp. 65-88, 2008.##
|
B. Kang, J. YANG, J. So, and C. Y. Kim, “Detecting Trigger-based Behaviors in Botnet Malware,” In Proceedings of the 2015 Conference on research in adaptive and convergent systems, ACM, 2015.##
|
S. Bahtiyar, “Anatomy of targeted attacks with smart malware,” Security and Communication Networks 9.18, pp. 6215-6226, 2016.##
|
G. Hăjmăşan, M .Alexandra, and C. Octavian, “Dynamic behavior evaluation for malware detection,” Digital Forensic and Security (ISDFS), 2017 5th International Symposium on. IEEE, 2017.##
|
R. de Tangil and S.Guillermo, “Mining structural and behavioral patterns in smart malware,” Diss. Universidad Carlos III de Madrid, 2014.##
|
C. Matthew, T. Liston, and E. Skoudis, “Hiding virtualization from attackers and malware,” IEEE Security & Privacy, vol. 5, no. 3, 2007.##
|
M. Mehra and P. Dhawal, “Event triggered malware: A new challenge to sandboxing,” India Conference (INDICON), 2015 Annual IEEE. IEEE, 2015.##
|
S. N. Alsagoff, “Malware self protection mechanism,” Information Technology, 2008. ITSim 2008. International Symposium on. vol. 3, IEEE, 2008.##
|
K. Navroop, A. K. Bindal, and A. PhD, “A Complete Dynamic Malware Analysis,” International Journal of Computer Applications, vol. 135, no. 4, pp. 20-25, 2016.##
|
D. Keragala, “Detecting malware and sandbox evasion techniques,” SANS Institute InfoSec Reading Room, vol. 16, 2016.##
|
C. Ravi and R. Manoharan, “Malware detection using windows api sequence and machine learning,” International Journal of Computer Applications, vol. 43, no. 17, pp. 12-16, 2012.##
|
L. Desmond, P. Watters, and X. Wu, “Rbacs: Rootkit behavioral analysis and classification system,” Knowledge Discovery and Data Mining, WKDD'10. Third International Conference on, 2010.##
|
D. Vidyarthi, S. P. Choudhary, S. Rakshit, and C. Kumar, “Malware Detection by Static Checking and Dynamic Analysis of Executables,” International Journal of Information Security and Privacy, 2017.##
|
P. Xie, et al., “An automatic approach to detect anti-debugging in malware analysis,” International Conference on Trustworthy Computing and Services, Springer, Berlin, Heidelberg, 2012.##
|
B. Kang, J. Yang, J. So, and C. Y. Kim, “Detecting Trigger-based Behaviors in Botnet Malware,” In Proceedings of the 2015 Conference on research in adaptive and convergent systems, 2015.##
|
M. Lindorfer, C. Kolbitsch, and P. M. Comparetti, “Detecting environment-sensitive malware,” In International Workshop on Recent Advances in Intrusion Detection, 2011.##
|
D. Brumley, C. Hartwig, Z. Liang, J. Newsome, D. Song, and H. Yin, “Automatically Identifying Trigger-based Behavior in Malware,” In Botnet Detection, Springer, pp. 65-88, 2008.##
|
Suarez-Tangil, M. Conti, J. E. Tapiador, and P. Peris-Lopez, “Detecting targeted smartphone malware with behavior-triggering stochastic models,” In In European Symposium on Research in Computer Security, 2014.##
|
A. Moser, C. Kruegel, and E. Kirda, “Exploring multiple execution paths for malware analysis,” in Proceedings- IEEE Symposium on Security and Privacy, 2007.##
|
D. Fleck, A. Tokhtabayev, A. Alarif, A. Stavrou, and T. Nykodym, “PyTrigger: A system to trigger & extract user-activated malware behavior,” in International Conference on Availability, Reliability and Security, 2013.##
|
S. Ranu and A. K. Singh, “GraphSig: a scalable approach to mining significant subgraphs in large graph databases,” In IEEE 25th International Conference on Data Engineering, 2009.##
|
R. Majumdar and S. Koushik, “Hybrid concolic testing,” Software Engineering, 2007. ICSE 2007. 29th International Conference on. IEEE, 2007.##
|
X. Xu, et al., “Software backdoor analysis based on sensitive flow tracking and concolic execution,” Wuhan University Journal of Natural Sciences vol. 21, no. 5, pp. 421-427, 2016.##
|
H. Yin and S. Dawn, “Hooking Behavior Analysis,” Automatic Malware Analysis, Springer, New York, pp. 43-58, 2013.##
|
K. Youngjoon, E. Kim, and H. Kang Kim, “A novel approach to detect malware based on API call sequence analysis,” International Journal of Distributed Sensor Networks, vol. 11, no. 6, 2015.##
|
J. Berdajs and Z. Bosnić, “Extending applications using an advanced approach to dll injection and api hooking,” Software: Practice and Experience, vol. 40, no. 7, pp. 567-584, 2010.##
|
J. M. Ceron, C. B. Margi, and L. Zambenedetti, “MARS: An SDN-based malware analysis solution,” In IEEE Symposium on Computers and Communication (ISCC), 2016.##
|
D. Oktavianto and M. Iqbal, “Cuckoo Malware Analysis,” Packt Publishing Ltd, 2013.##
|
C. Annachhatre, T. H. Austin, and M. Stamp, “Hidden Markov models for malware classification,” Journal of Computer Virology and Hacking Techniques 11.2, pp. 59-73, 2015.##
|
N. Nissim, et al., “Novel active learning methods for enhanced PC malware detection in windows OS,” Expert Systems with Applications 41.13, pp. 5843-5857, 2014.##
|
I. Rafiqul, et al., “Classification of malware based on integrated static and dynamic features,” Journal of Network and Computer Applications, vol. 36, no. 2, pp. 646-656, 2013.##
|
I. Santos, et al., “Opem: A static-dynamic approach for machine-learning-based malware detection,” International Joint Conference CISIS’12-ICEUTE 12-SOCO 12 Special Sessions, Springer, Berlin, Heidelberg, 2013.##
|
S. Silnov and T. O. Vladimirovich, “Analysis of Modern Attacks on Antiviruses,” Journal of Theoretical & Applied Information Technology, vol. 76, no. 1, 2015.##
|
M. Lindorfer, K.Clemens, and P. Milani Comparetti, “Detecting environment-sensitive malware,” Recent Advances in Intrusion Detection. Springer Berlin/Heidelberg, 2011.##
|
S.T. King and P. M. Chen, “implementing malware with virtual machines,” Security and Privacy, IEEE, 2006.##
|
D. Keragala, “Detecting Malware and Sandbox Evasion Techniques,” SANS Institute InfoSec Reading Room, 2016.##
|
A. Lakhani, “Malware Sandbox and Breach Detection Evasion Techniques,” Doctor Chaos, 18 February 2016. [Online]. Available: http://www.drchaos.com/malware-sandbox-and-breach-detection-evasion-techniques/. [Accessed 2016].##
|
A. B. Cesar and D. Andrade, “Malware Automatic Analysis,” Computational Intelligence and 11th Brazilian Congress on Computational Intelligence, 2013.##
|
U. Bayer, K. Christopher, and K. Engin, “TTAnalyze: A tool for analyzing malware,” na, 2006.##
|
T. Smith and M. Waterman, “Identification of common molecular subsequences,” Journal of molecular biology, pp. 195-197, 1987.##
|
B. Yadegari and S. Debray, “Symbolic Execution of Obfuscated Code,” In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, 2015.##
|
X. Chen, et al., “Towards an understanding of anti-virtualization and anti-debugging behavior in modern malware." Dependable Systems and Networks With FTCS and DCC, 2008. DSN 2008. IEEE International Conference on. IEEE, 2008.##
|
|