34 citations · 83 across the 8 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…
Bug Searching in Smart Contract
Xiaotao Feng, Qin Wang, Xiaogang Zhu +1
With the frantic development of smart contracts on the Ethereum platform, its market value has also climbed. In 2016, people were shocked by the loss of nearly $50 million in crypt…
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…