3 citations · 3 across the 5 of their papers we have counts for
5 papers
AdaDoS: Adaptive DoS Attack via Deep Adversarial Reinforcement Learning in SDN
Wei Shao, Yuhao Wang, Rongguang He +2
Existing defence mechanisms have demonstrated significant effectiveness in mitigating rule-based Denial-of-Service (DoS) attacks, leveraging predefined signatures and static heuris…
TELSAFE: Security Gap Quantitative Risk Assessment Framework
Sarah Ali Siddiqui, Chandra Thapa, Derui Wang +5
Gaps between established security standards and their practical implementation have the potential to introduce vulnerabilities, possibly exposing them to security risks. To effecti…
Attacking Slicing Network via Side-channel Reinforcement Learning Attack
Wei Shao, Chandra Thapa, Rayne Holland +2
Network slicing in 5G and the future 6G networks will enable the creation of multiple virtualized networks on a shared physical infrastructure. This innovative approach enables the…
One-Shot Collaborative Data Distillation
William Holland, Chandra Thapa, Sarah Ali Siddiqui +2
Large machine-learning training datasets can be distilled into small collections of informative synthetic data samples. These synthetic sets support efficient model learning and re…
Elevating Software Trust: Unveiling and Quantifying the Risk Landscape
Sarah Ali Siddiqui, Chandra Thapa, Rayne Holland +2
Considering the ever-evolving threat landscape and rapid changes in software development, we propose a risk assessment framework called SAFER (Software Analysis Framework for Evalu…