Publications

A Fekry, L Carata, T Pasquier, A Rice, A Hopper (2020). To Tune or Not to Tune? In Search of Optimal Configurations for Data Analytics. ACM KDD'20.
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X Han, T Pasquier, A Bates, J Mickens, M Seltzer (2020). UNICORN: Runtime Provenance-Based Detector for Advanced Persistent Threats. NDSS'20.
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M K Lau, T Pasquier, M Seltzer (2020). Rclean: A Tool for Writing Cleaner, More Transparent Code. In The Journal of Open Source Software.
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D O'Keeffe, A Vranaki, T Pasquier, D Eyers (2020). Facilitating plausible deniability for cloud providers regarding tenants' activities using trusted execution. IEEE IC2E'20.
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C Mistry, B Stelea, V Kumar, T Pasquier (2020). Demonstrating the Practicality of Unikernels to Build a Serverless Platform at the Edge. In IEEE CloudCom'20.
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S C Chan, J Cheney, P Bhatotia, T Pasquier, A Gehani, H Irshad, L Carata, M Seltzer (2019). ProvMark: A Provenance Expressiveness Benchmarking System. ACM/IFIP Middleware'19.
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T Pasquier, D Eyers, M Seltzer (2019). From Here to Provtopia. Springer Poly'19.
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A Fekry, L Carata, T Pasquier, Andrew Rice, Andy Hopper (2019). Towards Seamless Configuration Tuning of Big Data Analytics. IEEE ICDCS'19.
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T Pasquier, D Eyers, J Bacon (2019). Viewpoint | Personal Data and the Internet of Things: It is time to care about digital provenance. In Communications of the ACM.
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T Pasquier, X Han, T Moyer, A Bates, O Hermant, D Eyers, J Bacon, M Seltzer (2018). Runtime Analysis of Whole-System Provenance. In CCS ‘18.
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