Unbalanced classification is an essential machine learning task, which has attracted
widespread attention from both the academic and industrial communities due mainly to its …

Using hundreds of thousands of compromised IoT devices, the Mirai botnet emerged in late
2016 as a game changing threat actor, capable of temporarily taking down major Internet …

Botnets constitute a primary threat to Internet security. The ability to accurately distinguish
botnet traffic from non-botnet traffic can help significantly in mitigating malicious botnets. We …

Botnets pose a significant challenge to network security, continually evolving and
threatening the integrity of digital infrastructure. Traditional botnet detection methodologies …

We introduce a new cybersecurity project named RIVALS. RIVALS will assist in developing
network defense strategies through modeling adversarial network attack and defense …

Many applications today are using an encrypted channel to secure their communication and
transactions. Though, their security is often challenged by adversaries such as Botnet …

Accurate traffic classification is a key requirement for different network and security
monitoring/planning tools. The evolution of Internet protocols and applications has caused …

Given that botnets represent one of the most aggressive threats against cybersecurity,
various detection approaches have been studied. However, whichever approach is used …

Botnet detection is one of the most imminent tasks for cyber security. Among popular botnet
countermeasures, an intrusion detection system is the prominent mechanism. In the past …

Different variations in deployment environments of machine learning techniques may affect
the performance of the implemented systems. The variations may cause changes in the data …