Analysing system behaviour by automatic benchmarking of system-level provenance

Abstract

When referring to this work, full bibliographic details including the author, title, awarding institution and date of the thesis must be given. I am extremely grateful to many people for their help in completing my PhD. In particular, I would like to thank the following people: Thank you to my supervisors James Cheney, David Aspinall and Pramod Bhatotia for their advice, criticism, help, patience, and giving me the chance to work as a PhD under their supervision. Thank you to Ashish Gehani, Hassaan Irshad and researchers in SRI International for the helpful discussions in early PhD. Another thank you to Ashish Gehani and Hassaan Irshad, together with Thomas Pasquier, Margo Seltzer, Lucian Carata, Ripduman Sohan and researchers of SPADE, OPUS and CamFlow for helping me to test the ProvMark tools on their provenance systems and support me in the publication for ProvMark. Thank you to Myrto Arapinis and Ajitha Rajan for providing valuable opinions in the year review meeting. Thank you to Ajitha Rajan and Adam Bates, examiners of my viva, for providing valuable comments and suggestions on my PhD project and thesis.

ProvSec: Open Cybersecurity System Provenance Analysis Benchmark Dataset with Labels

“…Therefore, it takes manual effort to parse, curate, and extract useful information from the records. ProvMark [39] is a benchmarking system regarding provenance expressiveness, which evaluates three types of provenance recorders: OPUS [40], CamFlow [41], and SPADE [42], [43].…”