Abstract Machine Learning (ML) techniques are becoming an invaluable support for network
intrusion detection, especially in revealing anomalous flows, which often hide cyber-threats …

Abstract Denial of Service and Distributed Denial of Service (DoS/DDoS) attacks have been
one of the biggest threats against communication networks and applications throughout the …

In wireless sensor networks, clustering is said to be the most noteworthy technique for
increasing the lifetime of network that directly leads a better routing mechanism. This …

This study presents a session-based P2P botnet clustering system implemented on
MapReduce for aggregating malicious hosts within NetFlow traffic logs. The proposed botnet …

In a Distributed Denial of Service (DDoS) attack, a network (botnet) of dispersed agents
(bots) sends requests to a website to saturate its resources. Since the requests are sent by …

This work examines propagation of cyber-threats over networks under an adversarial
formulation. Exploiting Kendall's birth-death-immigration model, we propose an analytical …

Clustering is the approach, which is utilized for aggregating the nodes as a group called
clusters, which is used for reducing the routing overheads. This is a fundamental approach …

Botnets have become one of the major intrusion threats to cybersecurity. P2P botnets have
high concealment and resilience because of their distributed structure, which are difficult to …

In WSN based real-time applications, the authentication scheme is not yet defined properly
under the consideration of user privacy. Even though lot of attempts have been made for …

In the dynamic landscape of network security, where cyberattacks continuously evolve,
robust and adaptive detection mechanisms are essential, particularly for safeguarding …