Machine learning techniques are widely used in addition to signatures and heuristics to increase the detection rate of anti-malware software, as they automate the creation of …
Illicit crypto-mining leverages resources stolen from victims to mine cryptocurrencies on behalf of criminals. While recent works have analyzed one side of this threat, ie: web …
Smartphones are becoming more and more popular and, as a consequence, malware writers are increasingly engaged to develop new threats and propagate them through official …
An open research problem on malware analysis is how to statically distinguish between packed and non-packed executables. This has an impact on antivirus software and malware …
F Mbol, JM Robert, A Sadighian - … , CANS 2016, Milan, Italy, November 14 …, 2016 - Springer
TorrentLocker is a ransomware that encrypts sensitive data located on infected computer systems. Its creators aim to ransom the victims, if they want to retrieve their data …
B Cheng, J Ming, J Fu, G Peng, T Chen… - Proceedings of the …, 2018 - dl.acm.org
Binary packing, encoding binary code prior to execution and decoding them at run time, is the most common obfuscation adopted by malware authors to camouflage malicious code …
SS Lad, AC Adamuthe - International Journal of Computer …, 2022 - search.proquest.com
Static analysis and detection of malware is a crucial phase for handling security threats. Most researchers stated that the problem with the static analysis is an imbalance in the …
Packing algorithms are broadly used to avoid anti-malware systems, and the proportion of packed malware has been growing rapidly. However, just a few studies have been …
Malware detection is in a coevolutionary arms race where the attackers and defenders are constantly seeking advantage. This arms race is asymmetric: detection is harder and more …