A comprehensive review on malware detection approaches

ÖA Aslan, R Samet - IEEE access, 2020 - ieeexplore.ieee.org
According to the recent studies, malicious software (malware) is increasing at an alarming
rate, and some malware can hide in the system by using different obfuscation techniques. In …

Adversarial machine learning attacks and defense methods in the cyber security domain

I Rosenberg, A Shabtai, Y Elovici… - ACM Computing Surveys …, 2021 - dl.acm.org
In recent years, machine learning algorithms, and more specifically deep learning
algorithms, have been widely used in many fields, including cyber security. However …

A new malware classification framework based on deep learning algorithms

Ö Aslan, AA Yilmaz - Ieee Access, 2021 - ieeexplore.ieee.org
Recent technological developments in computer systems transfer human life from real to
virtual environments. Covid-19 disease has accelerated this process. Cyber criminals' …

{UNVEIL}: A {Large-Scale}, automated approach to detecting ransomware

A Kharaz, S Arshad, C Mulliner, W Robertson… - 25th USENIX security …, 2016 - usenix.org
Although the concept of ransomware is not new (ie, such attacks date back at least as far as
the 1980s), this type of malware has recently experienced a resurgence in popularity. In fact …

A comparison of static, dynamic, and hybrid analysis for malware detection

A Damodaran, FD Troia, CA Visaggio… - Journal of Computer …, 2017 - Springer
In this research, we compare malware detection techniques based on static, dynamic, and
hybrid analysis. Specifically, we train Hidden Markov Models (HMMs) on both static and …

Mamadroid: Detecting android malware by building markov chains of behavioral models (extended version)

L Onwuzurike, E Mariconti, P Andriotis… - ACM Transactions on …, 2019 - dl.acm.org
As Android has become increasingly popular, so has malware targeting it, thus motivating
the research community to propose different detection techniques. However, the constant …

Novel feature extraction, selection and fusion for effective malware family classification

M Ahmadi, D Ulyanov, S Semenov, M Trofimov… - Proceedings of the sixth …, 2016 - dl.acm.org
Modern malware is designed with mutation characteristics, namely polymorphism and
metamorphism, which causes an enormous growth in the number of variants of malware …

Poirot: Aligning attack behavior with kernel audit records for cyber threat hunting

SM Milajerdi, B Eshete, R Gjomemo… - Proceedings of the …, 2019 - dl.acm.org
Cyber threat intelligence (CTI) is being used to search for indicators of attacks that might
have compromised an enterprise network for a long time without being discovered. To have …