Malware detection issues, challenges, and future directions: A survey
The evolution of recent malicious software with the rising use of digital services has
increased the probability of corrupting data, stealing information, or other cybercrimes by …
increased the probability of corrupting data, stealing information, or other cybercrimes by …
A survey on machine learning-based malware detection in executable files
J Singh, J Singh - Journal of Systems Architecture, 2021 - Elsevier
In last decade, a proliferation growth in the development of computer malware has been
done. Nowadays, cybercriminals (attacker) use malware as a weapon to carry out the …
done. Nowadays, cybercriminals (attacker) use malware as a weapon to carry out the …
Security operations center: A systematic study and open challenges
Since the introduction of Security Operations Centers (SOCs) around 15 years ago, their
importance has grown significantly, especially over the last five years. This is mainly due to …
importance has grown significantly, especially over the last five years. This is mainly due to …
[HTML][HTML] Early-stage malware prediction using recurrent neural networks
Static malware analysis is well-suited to endpoint anti-virus systems as it can be conducted
quickly by examining the features of an executable piece of code and matching it to …
quickly by examining the features of an executable piece of code and matching it to …
A dynamic Windows malware detection and prediction method based on contextual understanding of API call sequence
E Amer, I Zelinka - Computers & Security, 2020 - Elsevier
Malware API call graph derived from API call sequences is considered as a representative
technique to understand the malware behavioral characteristics. However, it is troublesome …
technique to understand the malware behavioral characteristics. However, it is troublesome …
[PDF][PDF] Ransomware, threat and detection techniques: A review
The popularity of ransomware has created a unique ecosystem of cybercriminals. Therefore,
the objectives of this paper are to provide a thorough understanding of ransomware's threat …
the objectives of this paper are to provide a thorough understanding of ransomware's threat …
[HTML][HTML] Ransomware detection using random forest technique
BM Khammas - ICT Express, 2020 - Elsevier
Nowadays, the ransomware became a serious threat challenge the computing world that
requires an immediate consideration to avoid financial and moral blackmail. So, there is a …
requires an immediate consideration to avoid financial and moral blackmail. So, there is a …
Artificial intelligence in the cyber domain: Offense and defense
Artificial intelligence techniques have grown rapidly in recent years, and their applications in
practice can be seen in many fields, ranging from facial recognition to image analysis. In the …
practice can be seen in many fields, ranging from facial recognition to image analysis. In the …
Evaluation metric for crypto-ransomware detection using machine learning
Ransomware is a type of malware that blocks access to its victim's resources until a ransom
is paid. Crypto-ransomware is a type of ransomware that blocks access to its victim's files by …
is paid. Crypto-ransomware is a type of ransomware that blocks access to its victim's files by …
A multi-perspective malware detection approach through behavioral fusion of api call sequence
The widespread development of the malware industry is considered the main threat to our e-
society. Therefore, malware analysis should also be enriched with smart heuristic tools that …
society. Therefore, malware analysis should also be enriched with smart heuristic tools that …