Efficient detection of intrusions in TON-IoT dataset using hybrid feature selection approach. [PDF]
Dharini N, Janani VS, Katiravan J.
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An intelligent deep representation learning with enhanced feature selection approach for cyberattack detection in internet of things enabled cloud environment. [PDF]
Alamro H +7 more
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Local And Network Ransomware Detection Comparison
Background. Ransomware is a malicious application encrypting important files on a victim's computer. The ransomware will ask the victim for a ransom to be paid through cryptocurrency. After the system is encrypted there is virtually no way to decrypt the files other than using the encryption key that is bought from the attacker. Objectives.
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Relational Framework of Cyberattacks: Empirical Evidence from Multistage Incidents. [PDF]
Ferrer-Oliva M +3 more
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Mitigating distributed denial of service-based cyberattack in federated computing framework using deep reinforcement learning with frilled lizard algorithm. [PDF]
Maghrabi LA +6 more
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Advances in IoT networks using privacy-preserving techniques with optimized multi-head self-attention model for intelligent threat detection based on plant rhizome growth optimization. [PDF]
Alkhonaini MA +7 more
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Leveraging hybrid deep learning with starfish optimization algorithm based secure mechanism for intelligent edge computing in smart cities environment. [PDF]
Alkhalifa AK +7 more
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Security Audit of IoT Device Networks: A Reproducible Machine Learning Framework for Threat Detection and Performance Benchmarking. [PDF]
Shaikhanova A +5 more
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BigFlow-NIDS: A large-scale dataset for network intrusion detection in big data environment. [PDF]
Uddin MB, Arefin MS, Hussain MMM.
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A Systematic Review of Cyber Threat Intelligence: The Effectiveness of Technologies, Strategies, and Collaborations in Combating Modern Threats. [PDF]
Santos P +4 more
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