The major contribution of the article is the proposition of machine learning approach to model normal behaviour of application and to detect cyber attacks. The model consists of patterns (in form of ...

Citation: Aziz S, Irshad M, Haider SA, Wu J, Deng DN and Ahmad S (2022) Protection of a smart grid with the detection of cyber- malware attacks using efficient and novel machine learning models. Front ...

With increasingly more uses such as surveillance, delivery, and environmental monitoring, UAVs operating in these applications are increasingly targeted by cyber attacks which compromise functionality ...

Catch is the unsupervised version of Webhawk which is a supervised machine learning based cyber-attack detection tool. In contrary to the supervised Webhawk, Catch can be used without manually ...

By Dr. May Wang, CTO of IoT Security at Palo Alto Networks and the Co-founder, Chief Technology Officer (CTO), and board member of Zingbox - Why has machine learning become so vital in cybersecurity?

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System. The deployed project link is as follows. - MohdS ...

If a machine learning system mistakes a fraudulent data packet for a legitimate one that leads to an attack against a hospital and its devices, the impact of the mis-categorization can be severe.

Thankfully, artificial intelligence (AI) and machine learning (ML) have emerged as formidable allies in this ongoing battle, offering innovative approaches to detect and prevent cyber threats ...