With the rise of the Internet of Things (IoT), which envisions a connected network of
intelligent devices communicating autonomously through the Internet, the need to deal with …

Attackers often use Tor to launch cyberattacks and conduct illegal transactions, threatening
cyberspace's security and people's daily lives. Existing methods for malware traffic detection …

Summary The Internet of Battlefield Things (IoBTs) operate in an adversarial rapidly‐
evolving environment, necessitating fast, robust and resilient decision‐making. The success …

Machine learning (ML) requires both quantity and variety of examples in order to learn
generalizable patterns. In cybersecurity, labeling network packets is a tedious and difficult …

The domain of cybersecurity is growing as part of broader military and security applications,
and the capabilities and processes in this realm have qualities and characteristics that …

This paper studies adversarial attacks on network intrusion detection systems (IDSs) based
on deep or machine learning algorithms. Adversarial attacks on network IDSs must maintain …

Dalam pembelajaran diskriminatif, masalah manipulasi dirumuskan dengan jaringan saraf
yang mengukur perbedaan statistik antara fitur data pelatihan dan fitur data lawan. Jaringan …

Networks have an important role to play in modern life, and cyber security is an active
research area. An Intrusion Detection System (IDS) becomes a crucial cyber security method …

The security of IoT, particularly intrusion detection system (IDS) based on machine learning
(ML) and deep learning (DL) techniques. We systematically study and analyze different …

The attackers are using different techniques to intrude themselves into the network or system
to steal our data. The intruding techniques are increasing day by day and it is very difficult to …