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Digging into big provenance (with SPADE)

Published: 19 November 2021 Publication History

Abstract

A user interface for querying provenance.

References

[1]
Ahmad, R., Jung, E., de Senne Garcia, C., Irshad, H., Gehani, A. Discrepancy detection in whole network provenance. In Proceedings of the 12th USENIX Workshop on the Theory and Practice of Provenance; https://www.usenix.org/conference/tapp2020/presentation/ahmad.
[2]
Fan, J., Gerald, A., Raj, S., Patel, J. The case against specialized graph analytics engines. In Proceedings of the 7th Biennial Conf. on Innovative Data Systems, 2015; http://cidrdb.org/cidr2015/Papers/CIDR15_Paper20.pdf.
[3]
Gehani, A. SPADE; http://spade.csl.sri.com.
[4]
Gehani, A., Kim, M., Zhang, J. Steps toward managing lineage metadata in grid clusters. In Proceedings of the 1st Usenix Workshop on Theory and Practice of Provenance, 2009, 1--9
[5]
Gehani, A., Kim, M. Mendel: Efficiently verifying the lineage of data modified in multiple trust domains, Proceedings of the 19th ACM Intern. Symp. High Performance Distributed Computing 2010; 227--239.
[6]
Gehani, A., Tariq, D. SPADE: Support for provenance auditing in distributed environments. In Proceedings of the 13th ACM/IFIP/Usenix Middleware Conf.; 2012
[7]
Gehani, A., Kazmi, H., Irshad, H. Scaling SPADE to "Big Provenance." In Proceedings of the 8th Usenix Workshop on Theory and Practice of Provenance, 2016, 26--33; https://www.usenix.org/conference/tapp16/workshop-program/presentation/gehani.
[8]
Ghosh, S., Das, A., Porras, P., Yegneswaran, V., Gehani, A. Automated categorization of onion sites for analyzing the dark web ecosystem. In Proceedings of the 23rd ACM Intern. Conf. Knowledge Discovery and Data Mining, 2017, 1793--1802
[9]
Glavic, B. Big data provenance: challenges and implications for benchmarking. Revised Selected Papers of the 1st Workshop on Specifying Big Data Benchmarks 8163, 2012, 72--80
[10]
Khoury, J., Upthegrove, T., Caro, A., Benyo, B., Kong, D. An event-based data model for granular information flow tracking. Proceedings of the 12th Usenix Workshop on the Theory and Practice of Provenance, 2020; https://www.usenix.org/biblio-4496.
[11]
Moreau, L. et al. The Open Provenance Model core specification. Future Generation Computer Systems 27, 6 (2011)
[12]
Patel, J., Deshmukh, H., Zhu, J., Potti, N., Zhang, Z., Spehlmann, M., Memisoglu, H., Saurabh, S. Quickstep: A data platform based on the scaling-up approach. In Proceedings of the VLDB Endowment 11, 6 (2018), 663--676
[13]
W3C Working Group. PROV-overview, 2013; https://www.w3.org/TR/prov-overview/.

Cited By

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  • (2023)TeSec: Accurate Server-side Attack Investigation for Web Applications2023 IEEE Symposium on Security and Privacy (SP)10.1109/SP46215.2023.10179402(2799-2816)Online publication date: May-2023
  • (2023)XFedGraph-Hunter: An Interpretable Federated Learning Framework for Hunting Advanced Persistent Threat in Provenance GraphInformation Security Practice and Experience10.1007/978-981-99-7032-2_32(546-561)Online publication date: 24-Aug-2023
  • (2022)PACED: Provenance-based Automated Container Escape Detection2022 IEEE International Conference on Cloud Engineering (IC2E)10.1109/IC2E55432.2022.00035(261-272)Online publication date: Sep-2022

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Published In

cover image Communications of the ACM
Communications of the ACM  Volume 64, Issue 12
December 2021
101 pages
ISSN:0001-0782
EISSN:1557-7317
DOI:10.1145/3502158
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 November 2021
Published in CACM Volume 64, Issue 12

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Cited By

View all
  • (2023)TeSec: Accurate Server-side Attack Investigation for Web Applications2023 IEEE Symposium on Security and Privacy (SP)10.1109/SP46215.2023.10179402(2799-2816)Online publication date: May-2023
  • (2023)XFedGraph-Hunter: An Interpretable Federated Learning Framework for Hunting Advanced Persistent Threat in Provenance GraphInformation Security Practice and Experience10.1007/978-981-99-7032-2_32(546-561)Online publication date: 24-Aug-2023
  • (2022)PACED: Provenance-based Automated Container Escape Detection2022 IEEE International Conference on Cloud Engineering (IC2E)10.1109/IC2E55432.2022.00035(261-272)Online publication date: Sep-2022

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