IBD: An Interpretable Backdoor-Detection Method via Multivariate Interactions.

Recent work has shown that deep neural networks are vulnerable to backdoor attacks. In comparison with the success of backdoor-attack methods, existing backdoor-defense methods face a lack of theoretical foundations and interpretable solutions. Most defense methods are based on experience with the characteristics of previous attacks, but fail to defend against new attacks.

Tracking the Insider Attacker: A Blockchain Traceability System for Insider Threats.

The insider threats have always been one of the most severe challenges to cybersecurity. It can lead to the destruction of the organisation's internal network system and information leakage, which seriously threaten the confidentiality, integrity and availability of data. To make matters worse, since the attacker has authorized access to the internal network, they can launch the attack from the inside and erase their attack trace, which makes it challenging to track and forensics.