The specification and design of secure context-aware workflows

Zedan, Hussein; Al-Sultan, Saif

doi:10.1016/j.eswa.2017.05.078

Cited by 7 publications

(4 citation statements)

References 19 publications

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“…one of the process's instances is executed in a platform and another instance is executed in a different platform). For this reason, a recent work proposes a language for the specification and design of context-aware and secure workflow systems [59]. The approaches to enforce security policies at runtime mainly focus on integrating security control mechanisms into business process management systems [9].…”

Section: Related Workmentioning

confidence: 99%

Reasoning on the usage control security policies over data artifact business process models

et al. 2022

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The inclusion of security aspects in organizations is a crucial aspect to ensure compliance with both internal and external regulations. Business process models are a well-known mechanism to describe and automate the activities of the organizations, which should include security policies to ensure the correct performance of the daily activities. Frequently, these security policies involve complex data which cannot be represented using the standard Business Process Model Notation (BPMN). In this paper, we propose the enrichment of the BPMN with a UML class diagram to describe the data model, that is also combined with security policies defined using the UCONABC framework annotated within the business process model. The integration of the business process model, the data model, and the security policies provides a context where more complex reasoning can be applied about the satisfiability of the security policies in accordance with the business process and data models. To do so, we transform the original models, including security policies, into the BAUML framework (an artifact-centric approach to business process modelling). Once this is done, it is possible to ensure that there are no inherent errors in the model (verification) and that it fulfils the business requirements (validation), thus ensuring that the business process and the security policies are compatible and that they are aligned with the business security requirements.

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Section: Related Workmentioning

confidence: 99%

Reasoning on the usage control security policies over data artifact business process models

et al. 2022

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“…Aich et al [20] proposed the spatiotemporal RBAC (STARBAC) that takes into consideration time and location constraints in addition to the traditional RBAC. Zedan and Al-Sultan proposed in [21] a policy-based approach that defines policies as compositional rules where policies are analyzed and verified at run time. Md Emanual Kabir and Hua Wang [22] proposed a conditional based access control model that enables access to data based on the conditional intended purpose.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Performance-Aware Adaptation of Control Policies for Optimizing Banking Teller Process Using Machine Learning

Tay

Mourad

2020

IEEE Access

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In the current banking systems and business processes, the permission granted to employees is controlled and managed by the configured access control methods, in which static role-based models focus on access to information and functions. The deployed configuration is not reviewed/updated systematically and is handled manually by managers. Consequently, banks and companies are looking for systems and applications to automate and optimize their business processes and data management intelligently. In this context, the notion of integrating machine learning (ML) techniques in banking business processes has emerged. In order to build an intelligent and systematic solution, we combine in this paper ML and dynamic authorization techniques to enable performance-based policy evaluation into the banking teller process, where policies adapt to the changes recognized by the ML model. The objective of this work is to focus on the banking teller process that may be generalized to other operational banking processes. In this context, we propose in this paper a new model providing Intelligent Performance-Aware Adaptation of Roles and Policy Control using a support vector machine (SVM). We demonstrate that our model is capable of assessing the deployed control policies and updating them systematically with new roles and authorization levels based on tellers' performance, work history, and system constraints. We evaluated different machine learning models on a real dataset generated from a real-life banking environment. Experimental results explore the relevance and efficiency of our proposed scheme in terms of prediction accuracy, required authorizations, transaction time, and employees' working hours.

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“…As an example, Sultan et. al (Zedan & Al-Sultan, 2017) applied some features such as term weight, length ratio, lexical, and semantic similarities with supervised learning algorithm. Their experiments, which were performed on SemEval-2013 (Agirre et al, 2013) and Mohler (Mohler et al, 2011) datasets concluded that the augmentation of key gradingspecific construct (i.e question demoting) to text similarity features are proved to be effective by producing top results on multiple benchmarks.…”

Section: Related Workmentioning

confidence: 99%

UKARA: A Fast and Simple Automatic Short Answer Scoring System for Bahasa Indonesia

Herwanto

Sari

Prastowo

et al. 2018

ICEAP Proceeding Book Vol 2

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This paper presents UKARA, a fast and simple automatic short-answer scoring system for Bahasa Indonesia. Automatic short-answer scoring holds an important role in speeding up automatic assessment process. Although this area has been widely explored, only very limited number of previous work have studied Bahasa Indonesia. One of the major challenges in this field is the different type of questions which require different assessments. We are addressing this problem by implementing a combination of Natural Language Processing (NLP) and supervised machine learning techniques. Our system works by training a classifier model on human-labeled data. Using three different types of Programme for International Student Assessment (PISA) student responses, our system successfully produced the F1-score above 97% and 70% on dichotomous and polytomous scoring types respectively. Moreover, UKARA provides a user-friendly interface which is simple and easy to use. UKARA offers a flexibility for human grader to do re-scoring and retraining the model until the optimal performance is obtained.

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The specification and design of secure context-aware workflows

Cited by 7 publications

References 19 publications

Reasoning on the usage control security policies over data artifact business process models

Reasoning on the usage control security policies over data artifact business process models

Intelligent Performance-Aware Adaptation of Control Policies for Optimizing Banking Teller Process Using Machine Learning

UKARA: A Fast and Simple Automatic Short Answer Scoring System for Bahasa Indonesia

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