Online Self-Supervised Deep Learning for Intrusion Detection Systems
This paper proposes a novel Self-Supervised Intrusion Detection (SSID) framework, which
enables a fully online Deep Learning (DL) based Intrusion Detection System (IDS) that …
enables a fully online Deep Learning (DL) based Intrusion Detection System (IDS) that …
Improving the Detection of Unknown DDoS Attacks through Continual Learning
B Nugraha, K Yadav, P Patil… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Artificial Intelligence (AI)-based Intrusion Detection Systems (IDS) are popular with network
security researchers due to their good detection capability and low false alarm rate …
security researchers due to their good detection capability and low false alarm rate …
Tackling Okiru Attacks in IoT with AI-Driven Detection and Mitigation Strategies
Mirai botnet variations and their influence on IoT device security suggest that unreal Okiru
attacks would likely have similar traits. Mirai is known for compromising IoT devices and …
attacks would likely have similar traits. Mirai is known for compromising IoT devices and …
Automated Neural Network Structure Design for Efficient
E Holasova, R Fujdiak, P Blazek… - Proceedings of the 2023 …, 2023 - dl.acm.org
The creation of suitable and efficient tools for anomaly detection constitutes a crucial aspect
of security, applicable not only to industrial networks but also to cyber-physical systems. This …
of security, applicable not only to industrial networks but also to cyber-physical systems. This …
Hybrid deep architecture for intrusion detection in cyber‐physical system: An optimization‐based approach
SR Arumugam, PM Paul, BJJ Issac… - International Journal of … - Wiley Online Library
Summary Intrustion Detection System (IDS) refers to the gear or software that monitors a
network or system for malicious activity or policy violations. Periodically, the system records …
network or system for malicious activity or policy violations. Periodically, the system records …
A novel CNN‐based approach for detection and classification of DDoS attacks
Among the recent network security issues, Distributed Denial of Service (DDoS) attack is
one of the most dangerous threats in today's cyberspace that can disrupt essential services …
one of the most dangerous threats in today's cyberspace that can disrupt essential services …
Machine Learning-Based Attack Detection for the Internet of Things
DD Bikila, J Čapek - Available at SSRN 4785042 - papers.ssrn.com
The number of Internet of Things (IoT) device connections is increasing rapidly as IoT
applications are vital in any operation. IoT must maintain safe internet access that withstands …
applications are vital in any operation. IoT must maintain safe internet access that withstands …
[PDF][PDF] INTERPRETABILITY AND COMPLEXITY REDUCTION IN IOT NETWORK ANOMALY DETECTION VIA XAI
Due to their versatility and effectiveness, Deep Learning (DL) approaches are increasingly
used in designing Network Intrusion Detection Systems (NIDSs). Specifically, Anomaly …
used in designing Network Intrusion Detection Systems (NIDSs). Specifically, Anomaly …