34 citations · 119 across the 10 of their papers we have counts for
5 papers · 1 filter
Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models
Derui, Wang, Chaoran Li +3
Deep Neural Networks (DNNs) are vulnerable to deliberately crafted adversarial examples. In the past few years, many efforts have been spent on exploring query-optimisation attacks…
An Overview of Attacks and Defences on Intelligent Connected Vehicles
Mahdi Dibaei, Xi Zheng, Kun Jiang +9
Cyber security is one of the most significant challenges in connected vehicular systems and connected vehicles are prone to different cybersecurity attacks that endanger passengers…
A Feature-Oriented Corpus for Understanding, Evaluating and Improving Fuzz Testing
Xiaogang Zhu, Xiaotao Feng, Tengyun Jiao +4
Fuzzing is a promising technique for detecting security vulnerabilities. Newly developed fuzzers are typically evaluated in terms of the number of bugs found on vulnerable programs…
Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples
Derui Wang, Chaoran Li, Sheng Wen +4
This paper demonstrates that Non-Maximum Suppression (NMS), which is commonly used in Object Detection (OD) tasks to filter redundant detection results, is no longer secure. Consid…
A Truthful FPTAS Mechanism for Emergency Demand Response in Colocation Data Centers
Jianhai Chen, Deshi Ye, Shouling Ji +3
Demand response (DR) is not only a crucial solution to the demand side management but also a vital means of electricity market in maintaining power grid reliability, sustainability…