Machine learning in network anomaly detection: A survey
S Wang, JF Balarezo, S Kandeepan… - IEEE …, 2021 - ieeexplore.ieee.org
Anomalies could be the threats to the network that have ever/never happened. To protect
networks against malicious access is always challenging even though it has been studied …
networks against malicious access is always challenging even though it has been studied …
A systematic review on game-theoretic models and different types of security requirements in cloud environment: challenges and opportunities
The presented survey paper explores the application of game theoretic models for
addressing security challenges in cloud computing environments. It highlights the …
addressing security challenges in cloud computing environments. It highlights the …
Machine learning and deep learning based intrusion detection in cloud environment: a review
Due to its open and dispersed nature, cloud computing (CC) faces several security-related
difficulties. As a result, it is weak and open to breaches that compromise the security …
difficulties. As a result, it is weak and open to breaches that compromise the security …
Efficient approach for anomaly detection in internet of things traffic using deep learning
The network intrusion detection system (NIDs) is a significant research milestone in
information security. NIDs can scan and analyze the network to detect an attack or anomaly …
information security. NIDs can scan and analyze the network to detect an attack or anomaly …
A comprehensive survey on client selections in federated learning
Federated Learning (FL) is a rapidly growing field in machine learning that allows data to be
trained across multiple decentralized devices. The selection of clients to participate in the …
trained across multiple decentralized devices. The selection of clients to participate in the …
Enhancing industrial cyber security, focusing on formulating a practical strategy for making predictions through machine learning tools in cloud computing environment
Cloud computing has revolutionized how industries store, process, and access data.
However, the increasing adoption of cloud technology has also raised concerns regarding …
However, the increasing adoption of cloud technology has also raised concerns regarding …
Federated incremental learning based evolvable intrusion detection system for zero-day attacks
Smart community networks bring great comfort and convenience for people, but also
increase security risks of exposing system vulnerabilities and private data to network …
increase security risks of exposing system vulnerabilities and private data to network …
Service-based federated deep reinforcement learning for anomaly detection in fog ecosystems
With Digital transformation, the diversity of services and infrastructure in backhaul fog
network (s) is rising to unprecedented levels. This is causing a rising threat of a wider range …
network (s) is rising to unprecedented levels. This is causing a rising threat of a wider range …
On cooperative federated defense to secure multi-access edge computing
H Sedjelmaci, N Ansari - IEEE Consumer Electronics Magazine, 2022 - ieeexplore.ieee.org
The research of cyber security for multiaccess edge computing (MEC) has not yet received
great interest. Specifically, the attack detection issue is considered as a major concern since …
great interest. Specifically, the attack detection issue is considered as a major concern since …
Research trends in deep learning and machine learning for cloud computing security
YI Alzoubi, A Mishra, AE Topcu - Artificial Intelligence Review, 2024 - Springer
Deep learning and machine learning show effectiveness in identifying and addressing cloud
security threats. Despite the large number of articles published in this field, there remains a …
security threats. Despite the large number of articles published in this field, there remains a …