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[HTML][HTML] Cyber-attack prediction based on network intrusion detection systems for alert correlation techniques: a survey
Network Intrusion Detection Systems (NIDS) are designed to safeguard the security needs of
enterprise networks against cyber-attacks. However, NIDS networks suffer from several …
enterprise networks against cyber-attacks. However, NIDS networks suffer from several …
Predictive methods in cyber defense: Current experience and research challenges
Predictive analysis allows next-generation cyber defense that is more proactive than current
approaches based on intrusion detection. In this paper, we discuss various aspects of …
approaches based on intrusion detection. In this paper, we discuss various aspects of …
Intelligent dynamic malware detection using machine learning in IP reputation for forensics data analytics
In the near future, objects have to connect with each other which can result in gathering
private sensitive data and cause various security threats and cyber crimes. To prevent cyber …
private sensitive data and cause various security threats and cyber crimes. To prevent cyber …
GRU-based deep learning approach for network intrusion alert prediction
The exponential growth in the number of cyber attacks in the recent past has necessitated
active research on network intrusion detection, prediction and mitigation systems. While …
active research on network intrusion detection, prediction and mitigation systems. While …
CyberSecurity attack prediction: a deep learning approach
Cybersecurity attacks are exponentially increasing, making existing detection mechanisms
insufficient and enhancing the necessity to design more relevant prediction models and …
insufficient and enhancing the necessity to design more relevant prediction models and …
Transformer-based framework for alert aggregation and attack prediction in a multi-stage attack
W Wang, P Yi, J Jiang, P Zhang, X Chen - Computers & Security, 2024 - Elsevier
In recent years, the growing threat of cyber attacks has made more researchers focus on the
study of alert correlation and attack prediction. While numerous solutions have been …
study of alert correlation and attack prediction. While numerous solutions have been …
GDPR compliance in cybersecurity software: A case study of DPIA in information sharing platform
M Horák, V Stupka, M Husák - … of the 14th international conference on …, 2019 - dl.acm.org
In this article, we discuss the issues of GDPR's impact on cyber-security software and
operations, namely automated information sharing. We illustrate the topic on an example of …
operations, namely automated information sharing. We illustrate the topic on an example of …
SoK: Contemporary issues and challenges to enable cyber situational awareness for network security
Cyber situational awareness is an essential part of cyber defense that allows the
cybersecurity operators to cope with the complexity of today's networks and threat …
cybersecurity operators to cope with the complexity of today's networks and threat …
SoK: applications and challenges of using recommender systems in cybersecurity incident handling and response
M Husák, M Čermák - Proceedings of the 17th International Conference …, 2022 - dl.acm.org
Incident handling, a fundamental activity of a cybersecurity incident response team, is a
complex discipline that consumes a significant amount of personnel's time and costs. There …
complex discipline that consumes a significant amount of personnel's time and costs. There …
CL-AP2: A composite learning approach to attack prediction via attack portraying
Y Liu, Y Guo - Journal of Network and Computer Applications, 2024 - Elsevier
The capabilities of accurate prediction of cyberattacks have long been desired as detection
methods cannot avoid the damages caused by occurrences of cyberattack. Attack prediction …
methods cannot avoid the damages caused by occurrences of cyberattack. Attack prediction …