Machine learning (ML) has become an important paradigm for cyberthreat detection (CTD)
in the recent years. A substantial research effort has been invested in the development of …

Academic probation at universities has become a matter of pressing concern in recent years,
as many students face severe consequences of academic probation. We carried out …

Machine learning (ML) techniques are being used to detect increasing amounts of malware
and variants. Despite successful applications of ML, we hypothesize that the full potential of …

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 …

Malicious binaries have caused data and monetary loss to people, and these binaries keep
evolving rapidly nowadays. With tons of new unknown attack binaries, one essential daily …

Malware or malicious software is an intrusive software that infects or performs harmful
activities on a computer under attack. Malware has been a threat to individuals and …

Many studies have been conducted to detect malware based on machine learning of
program features extracted using static analysis. In this study, we consider the task of …

The constant growth in the number of malware-software or code fragment potentially harmful
for computers and information networks-and the use of sophisticated evasion and …

In recent years there has been a shift from heuristics based malware detection towards
machine learning, which proves to be more robust in the current heavily adversarial threat …

National security is threatened by malware, which remains one of the most dangerous and
costly cyber threats. As of last year, researchers reported 1.3 billion known malware …