As the Internet has transformed into a critical infrastructure, society has become more
vulnerable to its security flaws. Despite substantial efforts to address many of these …

Cyber-security systems, which protect networks and computers against cyber attacks, are
becoming common due to increasing threats and government regulation. At the same time …

Machine learning (ML) based malicious traffic detection is an emerging security paradigm,
particularly for zero-day attack detection, which is complementary to existing rule based …

In 2012 we presented the first systematic study of the costs of cybercrime. In this paper, we
report what has changed in the seven years since. The period has seen major platform …

In this paper, we propose HyperVision, a realtime unsupervised machine learning (ML)
based malicious traffic detection system. Particularly, HyperVision is able to detect unknown …

New and unseen polymorphic malware, zero-day attacks, or other types of advanced
persistent threats are usually not detected by signature-based security devices, firewalls, or …

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 …

In-browser cryptojacking is a form of resource abuse that leverages end-users' machines to
mine cryptocurrency without obtaining the users' consent. In this paper, we design …

Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …

The rise of large language models (LLMs) has had a significant impact on various domains,
including natural language processing and artificial intelligence. While LLMs such as …