Distributed denial-of-service (DDoS) attacks have become a weapon of choice for hackers,
cyber extortionists, and cyber terrorists. These attacks can swiftly incapacitate a victim …

Information communications technology systems are facing an increasing number of cyber
security threats, the majority of which are originated by insiders. As insiders reside behind …

The demand for Internet security has escalated in the last two decades because the rapid
proliferation in the number of Internet users has presented attackers with new detrimental …

The Mirai botnet, composed primarily of embedded and IoT devices, took the Internet by
storm in late 2016 when it overwhelmed several high-profile targets with massive distributed …

In this work we apply machine learning algorithms on network traffic data for accurate
identification of IoT devices connected to a network. To train and evaluate the classifier, we …

Machine learning (ML) based malicious traffic detection is an emerging security paradigm,
particularly for zero-day attack detection, which is complementary to existing rule based …

The application of machine learning for the detection of malicious network traffic has been
well researched over the past several decades; it is particularly appealing when the traffic is …

The Botnets have become one of the most serious threats to cyber infrastructure. Most
existing work on detecting botnets is based on flow-based traffic analysis by mining their …

OpenFlow is an open standard that has gained tremendous interest in the last few years
within the network community. It is an embodiment of the software-defined networking …

IoT devices are notoriously vulnerable even to trivial attacks and can be easily
compromised. In addition, resource constraints and heterogeneity of IoT devices make it …