Acing the ioc game: Toward automatic discovery and analysis of open-source cyber threat intelligence

X Liao, K Yuan, XF Wang, Z Li, L Xing… - Proceedings of the 2016 …, 2016 - dl.acm.org
To adapt to the rapidly evolving landscape of cyber threats, security professionals are
actively exchanging Indicators of Compromise (IOC)(eg, malware signatures, botnet IPs) …

Big data in cybersecurity: a survey of applications and future trends

MM Alani - Journal of Reliable Intelligent Environments, 2021 - Springer
With over 4.57 billion people using the Internet in 2020, the amount of data being generated
has exceeded 2.5 quintillion bytes per day. This rapid increase in the generation of data has …

Why should adversarial perturbations be imperceptible? rethink the research paradigm in adversarial nlp

Y Chen, H Gao, G Cui, F Qi, L Huang, Z Liu… - arXiv preprint arXiv …, 2022 - arxiv.org
Textual adversarial samples play important roles in multiple subfields of NLP research,
including security, evaluation, explainability, and data augmentation. However, most work …

A survey on dynamic mobile malware detection

P Yan, Z Yan - Software Quality Journal, 2018 - Springer
The outstanding advances of mobile devices stimulate their wide usage. Since mobile
devices are coupled with third-party applications, lots of security and privacy problems are …

Chainsmith: Automatically learning the semantics of malicious campaigns by mining threat intelligence reports

Z Zhu, T Dumitras - … IEEE European symposium on security and …, 2018 - ieeexplore.ieee.org
Modern cyber attacks consist of a series of steps and are generally part of larger campaigns.
Large-scale field data provides a quantitative measurement of these campaigns. On the …

Order-disorder: Imitation adversarial attacks for black-box neural ranking models

J Liu, Y Kang, D Tang, K Song, C Sun, X Wang… - Proceedings of the …, 2022 - dl.acm.org
Neural text ranking models have witnessed significant advancement and are increasingly
being deployed in practice. Unfortunately, they also inherit adversarial vulnerabilities of …

" Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security Conferences

D Olszewski, A Lu, C Stillman, K Warren… - Proceedings of the …, 2023 - dl.acm.org
Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …

Resident evil: Understanding residential ip proxy as a dark service

X Mi, X Feng, X Liao, B Liu, XF Wang… - … IEEE symposium on …, 2019 - ieeexplore.ieee.org
An emerging Internet business is residential proxy (RESIP) as a service, in which a provider
utilizes the hosts within residential networks (in contrast to those running in a datacenter) to …

Understanding malicious cross-library data harvesting on android

J Wang, Y Xiao, X Wang, Y Nan, L Xing, X Liao… - 30th USENIX Security …, 2021 - usenix.org
Recent years have witnessed the rise of security risks of libraries integrated in mobile apps,
which are reported to steal private user data from the host apps and the app backend …

Reading thieves' cant: automatically identifying and understanding dark jargons from cybercrime marketplaces

K Yuan, H Lu, X Liao, XF Wang - 27th USENIX Security Symposium …, 2018 - usenix.org
Underground communication is invaluable for understanding cybercrimes. However, it is
often obfuscated by the extensive use of dark jargons, innocently-looking terms like …