Intrusions constitute one of the main issues in computer network security. Through malicious
actions, hackers can have unauthorised access that compromises the integrity, the …

The problem of network intrusion detection poses innumerable challenges to the research
community, industry, and commercial sectors. Moreover, the persistent attacks occurring on …

Botnet is regarded as one of the most sophisticated vulnerability threats nowadays. A large
portion of network traffic is dominated by Botnets. Botnets are conglomeration of trade PCs …

Intrusions in computer networks have increased significantly in the last decade, due in part
to a profitable underground cyber-crime economy and the availability of sophisticated tools …

In recent years, the widespread deployment of the Internet of Things (IoT) applications has
contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies …

Due to the widespread use of the internet, computer systems are prone to information theft
that has led to the emergence of Intrusion Detection Systems (IDSs). Various approaches …

In this paper, Big Data and Deep Learning Techniques are integrated to improve the
performance of intrusion detection systems. Three classifiers are used to classify network …

Adversarial examples are inputs to a machine learning system intentionally crafted by an
attacker to fool the model into producing an incorrect output. These examples have achieved …

Abstract Internet of Things (IoT) as a paradigm comes with a range of benefits to humanity.
Domains of research for the IoT range from healthcare automation to energy and transport …

Internet of Things (IoT) has an immense potential for a plethora of applications ranging from
healthcare automation to defence networks and the power grid. The security of an IoT …