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Realtime robust malicious traffic detection via frequency domain analysis
Machine learning (ML) based malicious traffic detection is an emerging security paradigm,
particularly for zero-day attack detection, which is complementary to existing rule based …
particularly for zero-day attack detection, which is complementary to existing rule based …
[PDF][PDF] Anomaly Detection in the Open World: Normality Shift Detection, Explanation, and Adaptation.
Concept drift is one of the most frustrating challenges for learning-based security
applications built on the closeworld assumption of identical distribution between training and …
applications built on the closeworld assumption of identical distribution between training and …
Deep learning for vulnerability and attack detection on web applications: A systematic literature review
RL Alaoui, EH Nfaoui - Future Internet, 2022 - mdpi.com
Web applications are the best Internet-based solution to provide online web services, but
they also bring serious security challenges. Thus, enhancing web applications security …
they also bring serious security challenges. Thus, enhancing web applications security …
Cognitive memory-guided autoencoder for effective intrusion detection in internet of things
With the development of the Internet of Things (IoT) technology, intrusion detection has
become a key technology that provides solid protection for IoT devices from network …
become a key technology that provides solid protection for IoT devices from network …