Reactive defense mechanisms, such as intrusion detection systems, have made significant
efforts to secure a system or network for the last several decades. However, the nature of …

Network defenses based on traditional tools, techniques, and procedures (TTP) fail to
account for the attacker's inherent advantage present due to the static nature of network …

Abstract Machine learning is being embraced by information security researchers and
organizations alike for its potential in detecting attacks that an organization faces …

Security Assessment of large networks is a challenging task. Penetration testing (pentesting)
is a method of analyzing the attack surface of a network to find security vulnerabilities …

The field of cybersecurity has mostly been a cat-and-mouse game with the discovery of new
attacks leading the way. To take away an attacker's advantage of reconnaissance …

The lack of effective defense resource allocation strategies and reliable multi-agent
collaboration mechanisms lead to the low stability of Deep Reinforcement Learning (DRL) …

In view of the differences and limitations of the cognitive abilities of both sides of network
security attack and defense, the current network defense decision-making methods using …

The processing and storage of critical data in large-scale cloud networks necessitate the
need for scalable security solutions. It has been shown that deploying all possible detection …

Internet of Things (IoT) is vulnerable to various cyber attacks due to the massive deployment
of IoT devices and the openness of wireless environments. In this article, taking IoT devices …

Currently, important privacy data of the Internet of Things (IoT) face extremely high risks of
leakage. Attackers persistently engage in continuous attacks on terminal devices to obtain …