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Explainable intrusion detection systems (x-ids): A survey of current methods, challenges, and opportunities
The application of Artificial Intelligence (AI) and Machine Learning (ML) to cybersecurity
challenges has gained traction in industry and academia, partially as a result of widespread …
challenges has gained traction in industry and academia, partially as a result of widespread …
Automated machine learning for deep learning based malware detection
Deep learning (DL) has proven to be effective in detecting sophisticated malware that is
constantly evolving. Even though deep learning has alleviated the feature engineering …
constantly evolving. Even though deep learning has alleviated the feature engineering …
A survey on adversarial attacks for malware analysis
Machine learning-based malware analysis approaches are widely researched and
deployed in critical infrastructures for detecting and classifying evasive and growing …
deployed in critical infrastructures for detecting and classifying evasive and growing …
Creating cybersecurity knowledge graphs from malware after action reports
After Action Reports (AARs) provide incisive analysis of cyber-incidents. Extracting cyber-
knowledge from these sources would provide security analysts with credible information …
knowledge from these sources would provide security analysts with credible information …
RWArmor: a static-informed dynamic analysis approach for early detection of cryptographic windows ransomware
Ransomware attacks have captured news headlines worldwide for the last few years due to
their criticality and intensity. Ransomware-as-a-service (RaaS) kits are aiding adversaries to …
their criticality and intensity. Ransomware-as-a-service (RaaS) kits are aiding adversaries to …
Recurrent neural networks based online behavioural malware detection techniques for cloud infrastructure
Several organizations are utilizing cloud technologies and resources to run a range of
applications. These services help businesses save on hardware management, scalability …
applications. These services help businesses save on hardware management, scalability …
Analyzing machine learning approaches for online malware detection in cloud
The variety of services and functionality offered by various cloud service providers (CSP)
have exploded lately. Utilizing such services has created numerous opportunities for …
have exploded lately. Utilizing such services has created numerous opportunities for …
Analyzing and explaining black-box models for online malware detection
In recent years, a significant amount of research has focused on analyzing the effectiveness
of machine learning (ML) models for malware detection. These approaches have ranged …
of machine learning (ML) models for malware detection. These approaches have ranged …
Explainable Malware Analysis: Concepts, Approaches and Challenges
Machine learning (ML) has seen exponential growth in recent years, finding applications in
various domains such as finance, medicine, and cybersecurity. Malware remains a …
various domains such as finance, medicine, and cybersecurity. Malware remains a …
Creating an explainable intrusion detection system using self organizing maps
Modern Artificial Intelligence (AI) enabled Intrusion Detection Systems (IDS) are complex
black boxes. This means that a security analyst will have little to no explanation or …
black boxes. This means that a security analyst will have little to no explanation or …