49 citations · 102 across the 4 of their papers we have counts for
4 papers
Tools for Network Traffic Generation -- A Quantitative Comparison
Matthew Swann, Joseph Rose, Gueltoum Bendiab +2
Network traffic generators are invaluable tools that allow for applied experimentation to evaluate the performance of networks, infrastructure, and security controls, by modelling…
Intrusion Detection using Network Traffic Profiling and Machine Learning for IoT
Joseph Rose, Matthew Swann, Gueltoum Bendiab +2
The rapid increase in the use of IoT devices brings many benefits to the digital society, ranging from improved efficiency to higher productivity. However, the limited resources an…
Adversarial Machine Learning -- Industry Perspectives
Ram Shankar Siva Kumar, Magnus Nyström, John Lambert +5
Based on interviews with 28 organizations, we found that industry practitioners are not equipped with tactical and strategic tools to protect, detect and respond to attacks on thei…
Practical Machine Learning for Cloud Intrusion Detection: Challenges and the Way Forward
Ram Shankar Siva Kumar, Andrew Wicker, Matt Swann
Operationalizing machine learning based security detections is extremely challenging, especially in a continuously evolving cloud environment. Conventional anomaly detection does n…