loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Lu Zhang 1 ; Reginald Cushing 1 ; Ralph Koning 1 ; Cees de Laat 2 and Paola Grosso 1

Affiliations: 1 Multiscale Networked Systems (MNS), University of Amsterdam, Amsterdam, The Netherlands ; 2 Complex Cyber Infrastructure (CCI), University of Amsterdam, Amsterdam, The Netherlands

Keyword(s): Digital Data Marketplaces (DDM), System Calls, N-gram, Profiling, Containers.

Abstract: A Digital Data Marketplace (DDM) facilitates secure and trustworthy data sharing among multiple parties. For instance, training a machine learning (ML) model using data from multiple parties normally contributes to higher prediction accuracy. It is crucial to enforce the data usage policies during the execution stage. In this paper, we propose a methodology to distinguish programs running inside containers by monitoring system calls sequence externally. To support container portability and the necessity of retraining ML models, we also investigate the stability of the proposed methodology in 7 typical containerized ML applications over different execution platform OSs and training data sets. The results show our proposed methodology can distinguish between applications over various configurations with an average classification accuracy of 93.85%, therefore it can be integrated as an enforcement component in DDM infrastructures.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.97.14.83

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Zhang, L. ; Cushing, R. ; Koning, R. ; de Laat, C. and Grosso, P. (2021). Profiling and Discriminating of Containerized ML Applications in Digital Data Marketplaces (DDM). In Proceedings of the 7th International Conference on Information Systems Security and Privacy - ICISSP; ISBN 978-989-758-491-6; ISSN 2184-4356, SciTePress, pages 508-515. DOI: 10.5220/0010254105080515

@conference{icissp21,
author={Lu Zhang and Reginald Cushing and Ralph Koning and Cees {de Laat} and Paola Grosso},
title={Profiling and Discriminating of Containerized ML Applications in Digital Data Marketplaces (DDM)},
booktitle={Proceedings of the 7th International Conference on Information Systems Security and Privacy - ICISSP},
year={2021},
pages={508-515},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010254105080515},
isbn={978-989-758-491-6},
issn={2184-4356},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Information Systems Security and Privacy - ICISSP
TI - Profiling and Discriminating of Containerized ML Applications in Digital Data Marketplaces (DDM)
SN - 978-989-758-491-6
IS - 2184-4356
AU - Zhang, L.
AU - Cushing, R.
AU - Koning, R.
AU - de Laat, C.
AU - Grosso, P.
PY - 2021
SP - 508
EP - 515
DO - 10.5220/0010254105080515
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic