Paving the Way towards Semi-automatic Design-Time Business Process Model Obfuscation

Goettelmann, Elio; Amina, Ahmed-Nacer; Youcef, Samir; Godart, Claude

doi:10.1109/icws.2015.80

Cited by 12 publications

(19 citation statements)

References 15 publications

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“…To support this process, several works [8][5][1] use separation constraints (separate(t i , t j )) for requiring a sensitive task t i and its complementing sensitive task t j to be assigned to different clouds. [5] proposes an algorithm for automating the generation of separation constraints which, if applied to our motivating example returns the following separation constraints 1 We use the BPMN (Business Process Modeling Notation (http://www.bpmn.org)) for modeling our BP models. In addition these process models are supposed to be well structured [12] • separate(AR, RR) Figure 2 describes a collaboration of BP fragments obtained by this splitting, each fragment being assigned to a different cloud, and the fragments being connected with send and receive messages.…”

Section: B Bp Obfuscation By Splitting Its Logicmentioning

confidence: 99%

“…To observe the behavior of our risk metric, we have evaluated the risk of deploying a BP in the cloud with regards to three deployment approaches: 1) an aleatory distribution of tasks, 2) a distribution respecting the principle of assigning complementing sensitive tasks in different clouds (as introduced in [5] and summarized in section II-B, 3) a distribution as the previous one but extended with fake fragments as introduced in [1].…”

Section: Application and Experimentationsmentioning

confidence: 99%

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A Metric for Evaluating the Privacy Level of a Business Process Logic in a Multi-cloud Deployment

Nacer

Godart

Youcef

et al. 2017

2017 IEEE 21st International Enterprise Distributed Object Computing Conference (EDOC)

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Some companies are willing to execute their business processes (BP) in the cloud for enjoying its benefits. However, they are also reluctant because of the new security risks that using cloud resources introduces. Security risk includes many dimensions, but this work focus on preserving the privacy of the logic of a BP deployed in a multi-cloud context by preventing a coalition of malicious clouds to reconstruct important information from this logic. More precisely, the paper presents a BP logic privacy metric directly supporting the evaluation of the risk a company has its logic hacked in a particular multi-cloud configuration Index terms-BP modelling, BP deployment in the cloud, Security risk,

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Section: B Bp Obfuscation By Splitting Its Logicmentioning

confidence: 99%

Section: Application and Experimentationsmentioning

confidence: 99%

A Metric for Evaluating the Privacy Level of a Business Process Logic in a Multi-cloud Deployment

Nacer

Godart

Youcef

et al. 2017

2017 IEEE 21st International Enterprise Distributed Object Computing Conference (EDOC)

Self Cite

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“…For mitigating risks, the bank can obfuscate its BP by transforming its BP model using the principles and the methodology introduced in [14] and in [12] overviewed in the next section.…”

Section: A Motivating Examplementioning

confidence: 99%

“…In [12] we have proposed a design time approach for transforming a BP model into BP fragments, so that these BP fragments externalized in a multi-cloud context do not allow a cloud provider alone to understand a company know-how critical fragment.…”

Section: Introductionmentioning

confidence: 99%

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Obfuscating a Business Process by Splitting Its Logic with Fake Fragments for Securing a Multi-cloud Deployment

Nacer

Goettelmann

Youcef

et al. 2016

2016 IEEE World Congress on Services (SERVICES)

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Companies are ready to outsource their business process to the cloud to enjoy its benefits. However they must be sure that their business know-how is preserved. Although some solutions already exist and consist in splitting the model into a collaboration of BP fragments for a deployment in a muticloud context, none of them takes into account the possibility of collusion between the clouds executing the different fragments. To address this issue, we propose in this paper a solution consisting in adding fake BP fragments at specific locations in the process, so as to complicate its structure and hide the direct interaction between clouds executing sensitive fragments. Therefore, the discovery of the process by malicious cloud providers is delayed. The approach is validated against an introduced metric. It demonstrates that our approach is better in the worst case than previous approaches in best cases. Index terms-Fake Fragments, Security Risk Management, Cloud Collusion. Bank Get Loan Application (GLA) Check Customer Credit (CCC) Risk Evaluation (RE) Risk Capture (RC) Direct Loan Agreement (DLA) Loan Reject (LR) Hierarchy Validation (HV) Decision Consolidation (DC)

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Malicious clouds coalition management for business processes deployment

Ahmed Nacer,

Abdmeziem,

Aid

2024

Security and Privacy

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Cloud computing has raised concerns about security, causing many companies to hesitate in adopting it. Despite these concerns, there are methods available to address the risks associated with implementing a business process (BP) in the cloud. One common approach involves breaking down the BP model into smaller fragments, allowing each cloud provider access to a specific part of the overall model. However, this method fails to protect against collaboration between malicious cloud providers, which, by pooling their knowledge, can exploit the logic of the process. To tackle this issue, our paper proposes an approach that effectively manages coalitions when they arise. To do this, we introduce observer and deceiver fragments, which play a crucial role in redirecting the process execution toward a fake task. This strategic redirection prevents access to important information. The obtained results demonstrate that our proposed solution enhances security, mitigates risks, and does not necessarily lead to higher costs compared to other methods based solely on splitting.

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Paving the Way towards Semi-automatic Design-Time Business Process Model Obfuscation

Cited by 12 publications

References 15 publications

A Metric for Evaluating the Privacy Level of a Business Process Logic in a Multi-cloud Deployment

A Metric for Evaluating the Privacy Level of a Business Process Logic in a Multi-cloud Deployment

Obfuscating a Business Process by Splitting Its Logic with Fake Fragments for Securing a Multi-cloud Deployment

Malicious clouds coalition management for business processes deployment

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