activity
20192022
most citedAdversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective

54 citations · 119 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CR2022★ 54 cited

Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective

Mark Huasong Meng, Guangdong Bai, Sin Gee Teo +4

Neural networks have been widely applied in security applications such as spam and phishing detection, intrusion prevention, and malware detection. This black-box method, however,…

cs.CL2022★ 4 cited

A Prompting-based Approach for Adversarial Example Generation and Robustness Enhancement

Yuting Yang, Pei Huang, Juan Cao +5

Recent years have seen the wide application of NLP models in crucial areas such as finance, medical treatment, and news media, raising concerns of the model robustness and vulnerab…

cs.LG2021

Generalizing Neural Networks by Reflecting Deviating Data in Production

Yan Xiao, Yun Lin, Ivan Beschastnikh +3

Trained with a sufficiently large training and testing dataset, Deep Neural Networks (DNNs) are expected to generalize. However, inputs may deviate from the training dataset distri…

cs.SE2021

RegMiner: Towards Constructing a Large Regression Dataset from Code Evolution History

Xuezhi Song, Yun Lin, Siang Hwee Ng +4

Bug datasets consisting of real-world bugs are important artifacts for researchers and programmers, which lay empirical and experimental foundation for various SE/PL research such…

cs.SE2021

Self-Checking Deep Neural Networks in Deployment

Yan Xiao, Ivan Beschastnikh, David S. Rosenblum +4

The widespread adoption of Deep Neural Networks (DNNs) in important domains raises questions about the trustworthiness of DNN outputs. Even a highly accurate DNN will make mistakes…

cs.CR2020★ 2 cited

CoinWatch: A Clone-Based Approach For Detecting Vulnerabilities in Cryptocurrencies

Qingze Hum, Wei Jin Tan, Shi Ying Tey +4

Cryptocurrencies have become very popular in recent years. Thousands of new cryptocurrencies have emerged, proposing new and novel techniques that improve on Bitcoin's core innovat…

cs.SE2020★ 43 cited

sFuzz: An Efficient Adaptive Fuzzer for Solidity Smart Contracts

Tai D. Nguyen, Long H. Pham, Jun Sun +2

Smart contracts are Turing-complete programs that execute on the infrastructure of the blockchain, which often manage valuable digital assets. Solidity is one of the most popular p…

cs.SE2019★ 16 cited

Vulpedia: Detecting Vulnerable Ethereum Smart Contracts via Abstracted Vulnerability Signatures

Jiaming Ye, Mingliang Ma, Yun Lin +3

Recent years have seen smart contracts are getting increasingly popular in building trustworthy decentralized applications. Previous research has proposed static and dynamic techni…