Optimal Evidence Collection for Accountability in the Cloud

Fatma Masmoudi; Mohamed Sellami; Monia Loulou; Ahmed Hadj Kacem

doi:10.1109/ICEBE.2018.00022

Optimal Evidence Collection for Accountability in the Cloud

Fatma Masmoudi
, Mohamed Sellami
, Monia Loulou
, Ahmed Hadj Kacem

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

In multi-tenant cloud services, accountability can be used to strengthen the trust of tenants in the cloud. It provides the reassurance that the processing of personal data hosted in the cloud is done according to tenants' requirements (a.k.a. Accountability obligations). Ensuring accountability requires multiple measures ranging from preventive controls to violation detection and analysis, based on evidences so as to prove that a violation has occurred or to ensure violation judgment. In a complex cloud environment with multi-tenant services, judging violations encounters difficulties due to the plethora of evidences to be analyzed, which may burden the post-violation analysis in terms of latency and workloads. In this work, we offer a method ensuring the collection of the necessary and minimal (optimal) evidences and avoiding re-evaluating all of them for each violated obligation. Basically, we use a linear program-with an objective function under a set of constraints-and we perform actions in order to obtain optimal evidences elements for the judgment. Finally, our approach is implemented and the results of our experiments highlight its feasibility.

Original language	English
Title of host publication	Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	78-85
Number of pages	8
ISBN (Electronic)	9781538679920
DOIs	https://doi.org/10.1109/ICEBE.2018.00022
State	Published - 27 Dec 2018
Externally published	Yes
Event	15th International Conference on e-Business Engineering, ICEBE 2018 - Xi'an, China Duration: 12 Oct 2018 → 14 Oct 2018

Publication series

Name	Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018

Conference

Conference	15th International Conference on e-Business Engineering, ICEBE 2018
Country/Territory	China
City	Xi'an
Period	12/10/18 → 14/10/18

Keywords

Accountability Management
Cloud computing
Evidence
General Data Protection Regulation
Multi tenancy
Obligation model
Optimization
Trustworthiness

Access to Document

10.1109/ICEBE.2018.00022

Cite this

Masmoudi, F., Sellami, M., Loulou, M., & Hadj Kacem, A. (2018). Optimal Evidence Collection for Accountability in the Cloud. In Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018 (pp. 78-85). Article 8592633 (Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICEBE.2018.00022

Masmoudi, Fatma ; Sellami, Mohamed ; Loulou, Monia et al. / Optimal Evidence Collection for Accountability in the Cloud. Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 78-85 (Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018).

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title = "Optimal Evidence Collection for Accountability in the Cloud",

abstract = "In multi-tenant cloud services, accountability can be used to strengthen the trust of tenants in the cloud. It provides the reassurance that the processing of personal data hosted in the cloud is done according to tenants' requirements (a.k.a. Accountability obligations). Ensuring accountability requires multiple measures ranging from preventive controls to violation detection and analysis, based on evidences so as to prove that a violation has occurred or to ensure violation judgment. In a complex cloud environment with multi-tenant services, judging violations encounters difficulties due to the plethora of evidences to be analyzed, which may burden the post-violation analysis in terms of latency and workloads. In this work, we offer a method ensuring the collection of the necessary and minimal (optimal) evidences and avoiding re-evaluating all of them for each violated obligation. Basically, we use a linear program-with an objective function under a set of constraints-and we perform actions in order to obtain optimal evidences elements for the judgment. Finally, our approach is implemented and the results of our experiments highlight its feasibility.",

keywords = "Accountability Management, Cloud computing, Evidence, General Data Protection Regulation, Multi tenancy, Obligation model, Optimization, Trustworthiness",

author = "Fatma Masmoudi and Mohamed Sellami and Monia Loulou and \{Hadj Kacem\}, Ahmed",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 15th International Conference on e-Business Engineering, ICEBE 2018 ; Conference date: 12-10-2018 Through 14-10-2018",

year = "2018",

month = dec,

day = "27",

doi = "10.1109/ICEBE.2018.00022",

language = "English",

series = "Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018",

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Masmoudi, F, Sellami, M, Loulou, M & Hadj Kacem, A 2018, Optimal Evidence Collection for Accountability in the Cloud. in Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018., 8592633, Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018, Institute of Electrical and Electronics Engineers Inc., pp. 78-85, 15th International Conference on e-Business Engineering, ICEBE 2018, Xi'an, China, 12/10/18. https://doi.org/10.1109/ICEBE.2018.00022

Optimal Evidence Collection for Accountability in the Cloud. / Masmoudi, Fatma; Sellami, Mohamed; Loulou, Monia et al.
Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 78-85 8592633 (Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Masmoudi, Fatma

AU - Sellami, Mohamed

AU - Loulou, Monia

AU - Hadj Kacem, Ahmed

PY - 2018/12/27

Y1 - 2018/12/27

N2 - In multi-tenant cloud services, accountability can be used to strengthen the trust of tenants in the cloud. It provides the reassurance that the processing of personal data hosted in the cloud is done according to tenants' requirements (a.k.a. Accountability obligations). Ensuring accountability requires multiple measures ranging from preventive controls to violation detection and analysis, based on evidences so as to prove that a violation has occurred or to ensure violation judgment. In a complex cloud environment with multi-tenant services, judging violations encounters difficulties due to the plethora of evidences to be analyzed, which may burden the post-violation analysis in terms of latency and workloads. In this work, we offer a method ensuring the collection of the necessary and minimal (optimal) evidences and avoiding re-evaluating all of them for each violated obligation. Basically, we use a linear program-with an objective function under a set of constraints-and we perform actions in order to obtain optimal evidences elements for the judgment. Finally, our approach is implemented and the results of our experiments highlight its feasibility.

AB - In multi-tenant cloud services, accountability can be used to strengthen the trust of tenants in the cloud. It provides the reassurance that the processing of personal data hosted in the cloud is done according to tenants' requirements (a.k.a. Accountability obligations). Ensuring accountability requires multiple measures ranging from preventive controls to violation detection and analysis, based on evidences so as to prove that a violation has occurred or to ensure violation judgment. In a complex cloud environment with multi-tenant services, judging violations encounters difficulties due to the plethora of evidences to be analyzed, which may burden the post-violation analysis in terms of latency and workloads. In this work, we offer a method ensuring the collection of the necessary and minimal (optimal) evidences and avoiding re-evaluating all of them for each violated obligation. Basically, we use a linear program-with an objective function under a set of constraints-and we perform actions in order to obtain optimal evidences elements for the judgment. Finally, our approach is implemented and the results of our experiments highlight its feasibility.

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KW - Cloud computing

KW - Evidence

KW - General Data Protection Regulation

KW - Multi tenancy

KW - Obligation model

KW - Optimization

KW - Trustworthiness

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BT - Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 15th International Conference on e-Business Engineering, ICEBE 2018

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ER -

Masmoudi F, Sellami M, Loulou M, Hadj Kacem A. Optimal Evidence Collection for Accountability in the Cloud. In Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 78-85. 8592633. (Proceedings - 2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018). doi: 10.1109/ICEBE.2018.00022

Optimal Evidence Collection for Accountability in the Cloud

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Keywords

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