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PIDSMaker: Building and Evaluating Provenance-based Intrusion Detection Systems
Recent provenance-based intrusion detection systems (PIDSs) have demonstrated strong potential for detecting advanced persistent …
T Bilot, B Jiang, T Pasquier
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PIDSMaker: Building and Evaluating Provenance-based Intrusion Detection Systems
Inside Out: A Paradigm Shift In VM Introspection
We present GoodKit, a new framework for live virtual machine introspection (LVMI) designed for performance, scalability, and safe …
D Teguia, L Duval, T Pisenti, K Lazri, D Hagimont, T Pasquier, R Lachaize, A Tchana
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Inside Out: A Paradigm Shift In VM Introspection
RegTrack: Uncovering Global Disparities in Third-party Advertising and Tracking
Third-party advertising and tracking (A&T) are pervasive across the web, yet user exposure varies significantly with browser …
T Prasad, R Vora, SY Lim, NP Phong, T Pasquier
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RegTrack: Uncovering Global Disparities in Third-party Advertising and Tracking
Toward Practical and Usable Provenance-based Intrusion Detection Systems
In recent years, researchers have turned to provenance-based intrusion detection systems (PIDSs) as a promising way to spot attacks …
T Bilot, T Pasquier
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Toward Practical and Usable Provenance-based Intrusion Detection Systems
Sometimes Simpler is Better: A Comprehensive Analysis of State-of-the-Art Provenance-Based Intrusion Detection Systems
Provenance-based intrusion detection systems (PIDSs) have garnered significant attention from the research community over the past …
T Bilot, B Jiang, Z Li, N El Madhoun, K Al Agha, A Zouaoui, T Pasquier
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Sometimes Simpler is Better: A Comprehensive Analysis of State-of-the-Art Provenance-Based Intrusion Detection Systems
ORTHRUS: Achieving High Quality of Attribution in Provenance-based Intrusion Detection Systems
Past success in applying machine learning to data provenance graphs – a structured representation of the history of operating …
B Jiang, T Bilot, N El Madhoun, K Al Agha, A Zouaoui, S Iqbal, X Han, T Pasquier
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ORTHRUS: Achieving High Quality of Attribution in Provenance-based Intrusion Detection Systems
On the Reproducibility of Provenance-based Intrusion Detection that uses Deep Learning
As cyber-threats grow in scale and sophistication, intrusion detection systems that incorporate system provenance and deep learning …
T Abrar, A Shamail, M J Iqbal, M Iqbal, A Zouaoui, A Ahmed, M Abdullah, M Shayan, F Zaffar, T Pasquier, D Eyers, A Gehani
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SafeBPF: Hardware-assisted Defense-in-depth for eBPF Kernel Extensions
The eBPF framework enables execution of user-provided code in the Linux kernel. In the last few years, a large ecosystem of cloud …
SY Lim, T Prasad, X Han, T Pasquier
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SafeBPF: Hardware-assisted Defense-in-depth for eBPF Kernel Extensions
FetchBPF: Customizable Prefetching Policies in Linux with eBPF
Monolithic operating systems are infamously complex. Linux in particular has a tendency to intermingle policy and mechanisms in a …
X Cao, S Patel , SY Lim, X Han, T Pasquier
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FetchBPF: Customizable Prefetching Policies in Linux with eBPF
Computational Experiment Comprehension using Provenance Summarization
Scientists use complex multistep workflows to analyze data. However, reproducing computational experiments is often difficult as …
N Boufford, J Wonsil, A Pocock, J Sullivan, M Seltzer, T Pasquier
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Computational Experiment Comprehension using Provenance Summarization