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The age of ransomware: A survey on the evolution, taxonomy, and research directions
The proliferation of ransomware has become a significant threat to cybersecurity in recent
years, causing significant financial, reputational, and operational damage to individuals and …
years, causing significant financial, reputational, and operational damage to individuals and …
A survey of android malware detection with deep neural models
Deep Learning (DL) is a disruptive technology that has changed the landscape of cyber
security research. Deep learning models have many advantages over traditional Machine …
security research. Deep learning models have many advantages over traditional Machine …
Deep learning based attack detection for cyber-physical system cybersecurity: A survey
With the booming of cyber attacks and cyber criminals against cyber-physical systems
(CPSs), detecting these attacks remains challenging. It might be the worst of times, but it …
(CPSs), detecting these attacks remains challenging. It might be the worst of times, but it …
Software vulnerability detection using deep neural networks: a survey
The constantly increasing number of disclosed security vulnerabilities have become an
important concern in the software industry and in the field of cybersecurity, suggesting that …
important concern in the software industry and in the field of cybersecurity, suggesting that …
[HTML][HTML] Security and privacy in 6G networks: New areas and new challenges
With the deployment of more and more 5g networks, the limitations of 5g networks have
been found, which undoubtedly promotes the exploratory research of 6G networks as the …
been found, which undoubtedly promotes the exploratory research of 6G networks as the …
Adversarial examples: A survey of attacks and defenses in deep learning-enabled cybersecurity systems
Over the last few years, the adoption of machine learning in a wide range of domains has
been remarkable. Deep learning, in particular, has been extensively used to drive …
been remarkable. Deep learning, in particular, has been extensively used to drive …
Adversarial deep ensemble: Evasion attacks and defenses for malware detection
Malware remains a big threat to cyber security, calling for machine learning based malware
detection. While promising, such detectors are known to be vulnerable to evasion attacks …
detection. While promising, such detectors are known to be vulnerable to evasion attacks …
Deep learning for android malware defenses: a systematic literature review
Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …
threat to developers and end-users. Numerous research efforts have been devoted to …
Adversarial machine learning: A multilayer review of the state-of-the-art and challenges for wireless and mobile systems
Machine Learning (ML) models are susceptible to adversarial samples that appear as
normal samples but have some imperceptible noise added to them with the intention of …
normal samples but have some imperceptible noise added to them with the intention of …
Event detection in online social network: Methodologies, state-of-art, and evolution
Online social network such as Twitter, Facebook and Instagram are increasingly becoming
the go-to medium for users to acquire information and discuss what is happening globally …
the go-to medium for users to acquire information and discuss what is happening globally …