Recent progress in machine learning has led to promising results in behavioral malware
detection. Behavioral modeling identifies malicious processes via features derived by their …

The threat from ransomware continues to grow both in the number of affected victims as well
as the cost incurred by the people and organisations impacted in a successful attack. In the …

Machine learning has brought significant advances in cybersecurity, particularly in the
development of Intrusion Detection Systems (IDS). These improvements are mainly …

It was found when reviewing the ransomware detection research literature that almost no
proposal provided enough detail on how the test data set was created, or sufficient …

Economic incentives encourage malware authors to constantly develop new, increasingly
complex malware to steal sensitive data or blackmail individuals and companies into paying …

Ransomware has evolved from an economic nuisance to a national security threat
nowadays, which poses a significant risk to users. To address this problem, we propose …

Several cybersecurity domains, such as ransomware detection, forensics and data analysis,
require methods to reliably identify encrypted data fragments. Typically, current approaches …

Recent advances in generative machine learning models rekindled research interest in the
area of password guessing. Data-driven password guessing approaches based on GANs …

Review of Current Ransomware Detection Techniques Skip to main content Edinburgh
Napier Research Repository Home Research Outputs People Faculties, Schools & Groups …

The proliferation of deep learning applications in several areas has led to the rapid adoption
of such solutions from an ever-growing number of institutions and companies. These entities' …