[HTML][HTML] Research communities in cyber security vulnerability assessments: A comprehensive literature review

F Heiding, S Katsikeas, R Lagerström - Computer Science Review, 2023 - Elsevier
Ethical hacking and vulnerability assessments are gaining rapid momentum as academic
fields of study. Still, it is sometimes unclear what research areas are included in the …

A systematic review of fuzzing based on machine learning techniques

Y Wang, P Jia, L Liu, C Huang, Z Liu - PloS one, 2020 - journals.plos.org
Security vulnerabilities play a vital role in network security system. Fuzzing technology is
widely used as a vulnerability discovery technology to reduce damage in advance …

{MOPT}: Optimized mutation scheduling for fuzzers

C Lyu, S Ji, C Zhang, Y Li, WH Lee, Y Song… - 28th USENIX security …, 2019 - usenix.org
Mutation-based fuzzing is one of the most popular vulnerability discovery solutions. Its
performance of generating interesting test cases highly depends on the mutation scheduling …

The ethics of advanced ai assistants

I Gabriel, A Manzini, G Keeling, LA Hendricks… - arxiv preprint arxiv …, 2024 - arxiv.org
This paper focuses on the opportunities and the ethical and societal risks posed by
advanced AI assistants. We define advanced AI assistants as artificial agents with natural …

Neuzz: Efficient fuzzing with neural program smoothing

D She, K Pei, D Epstein, J Yang… - 2019 IEEE Symposium …, 2019 - ieeexplore.ieee.org
Fuzzing has become the de facto standard technique for finding software vulnerabilities.
However, even state-of-the-art fuzzers are not very efficient at finding hard-to-trigger …

{GREYONE}: Data flow sensitive fuzzing

S Gan, C Zhang, P Chen, B Zhao, X Qin, D Wu… - 29th USENIX security …, 2020 - usenix.org
Data flow analysis (eg, dynamic taint analysis) has proven to be useful for guiding fuzzers to
explore hard-to-reach code and find vulnerabilities. However, traditional taint analysis is …

Wuji: Automatic online combat game testing using evolutionary deep reinforcement learning

Y Zheng, X **e, T Su, L Ma, J Hao… - 2019 34th IEEE/ACM …, 2019 - ieeexplore.ieee.org
Game testing has been long recognized as a notoriously challenging task, which mainly
relies on manual playing and scripting based testing in game industry. Even until recently …

Automatic web testing using curiosity-driven reinforcement learning

Y Zheng, Y Liu, X **e, Y Liu, L Ma… - 2021 IEEE/ACM 43rd …, 2021 - ieeexplore.ieee.org
Web testing has long been recognized as a notoriously difficult task. Even nowadays, web
testing still mainly relies on manual efforts in many cases while automated web testing is still …

Pangolin: Incremental hybrid fuzzing with polyhedral path abstraction

H Huang, P Yao, R Wu, Q Shi… - 2020 IEEE Symposium …, 2020 - ieeexplore.ieee.org
Hybrid fuzzing, which combines the merits of both fuzzing and concolic execution, has
become one of the most important trends in coverage-guided fuzzing techniques. Despite …

{SyzVegas}: Beating kernel fuzzing odds with reinforcement learning

D Wang, Z Zhang, H Zhang, Z Qian… - 30th USENIX Security …, 2021 - usenix.org
Fuzzing embeds a large number of decisions requiring finetuned and hard-coded
parameters to maximize its efficiency. This is especially true for kernel fuzzing due to (1) OS …