A survey on malware detection using data mining techniques

Y Ye, T Li, D Adjeroh, SS Iyengar - ACM Computing Surveys (CSUR), 2017 - dl.acm.org
In the Internet age, malware (such as viruses, trojans, ransomware, and bots) has posed
serious and evolving security threats to Internet users. To protect legitimate users from these …

Classification of malware based on integrated static and dynamic features

R Islam, R Tian, LM Batten, S Versteeg - Journal of Network and Computer …, 2013 - Elsevier
Collection of dynamic information requires that malware be executed in a controlled
environment; the malware unpacks itself as a preliminary to the execution process. On the …

Malware classification with deep convolutional neural networks

M Kalash, M Rochan, N Mohammed… - 2018 9th IFIP …, 2018 - ieeexplore.ieee.org
In this paper, we propose a deep learning framework for malware classification. There has
been a huge increase in the volume of malware in recent years which poses a serious …

{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 …

Advanced persistent threats (apt): evolution, anatomy, attribution and countermeasures

A Sharma, BB Gupta, AK Singh… - Journal of Ambient …, 2023 - Springer
In today's cyber warfare realm, every stakeholder in cyberspace is becoming more potent by
develo** advanced cyber weapons. They have equipped with the most advanced …

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 …

[PDF][PDF] DL4MD: A deep learning framework for intelligent malware detection

W Hardy, L Chen, S Hou, Y Ye, X Li - Proceedings of the International …, 2016 - covert.io
In the Internet-age, malware poses a serious and evolving threat to security, making the
detection of malware of utmost concern. Many research efforts have been conducted on …

Opcode sequences as representation of executables for data-mining-based unknown malware detection

I Santos, F Brezo, X Ugarte-Pedrero, PG Bringas - information Sciences, 2013 - Elsevier
Malware can be defined as any type of malicious code that has the potential to harm a
computer or network. The volume of malware is growing faster every year and poses a …

A survey on heuristic malware detection techniques

Z Bazrafshan, H Hashemi, SMH Fard… - The 5th conference on …, 2013 - ieeexplore.ieee.org
Malware is a malicious code which is developed to harm a computer or network. The
number of malwares is growing so fast and this amount of growth makes the computer …

[PDF][PDF] A survey of malware detection techniques

N Idika, AP Mathur - Purdue University, 2007 - profsandhu.com
Malware is a worldwide epidemic. Studies suggest that the impact of malware is getting
worse. Malware detectors are the primary tools in defense against malware. The quality of …