| 1. |
- Ahmadi Mehri, Vida, et al.
(författare)
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Automated Context-Aware Vulnerability Risk Management for Patch Prioritization
- 2022
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Ingår i: Electronics. - : MDPI. - 2079-9292. ; 11:21
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Tidskriftsartikel (refereegranskat)abstract
- The information-security landscape continuously evolves by discovering new vulnerabilities daily and sophisticated exploit tools. Vulnerability risk management (VRM) is the most crucial cyber defense to eliminate attack surfaces in IT environments. VRM is a cyclical practice of identifying, classifying, evaluating, and remediating vulnerabilities. The evaluation stage of VRM is neither automated nor cost-effective, as it demands great manual administrative efforts to prioritize the patch. Therefore, there is an urgent need to improve the VRM procedure by automating the entire VRM cycle in the context of a given organization. The authors propose automated context-aware VRM (ACVRM), to address the above challenges. This study defines the criteria to consider in the evaluation stage of ACVRM to prioritize the patching. Moreover, patch prioritization is customized in an organization’s context by allowing the organization to select the vulnerability management mode and weigh the selected criteria. Specifically, this study considers four vulnerability evaluation cases: (i) evaluation criteria are weighted homogeneously; (ii) attack complexity and availability are not considered important criteria; (iii) the security score is the only important criteria considered; and (iv) criteria are weighted based on the organization’s risk appetite. The result verifies the proposed solution’s efficiency compared with the Rudder vulnerability management tool (CVE-plugin). While Rudder produces a ranking independent from the scenario, ACVRM can sort vulnerabilities according to the organization’s criteria and context. Moreover, while Rudder randomly sorts vulnerabilities with the same patch score, ACVRM sorts them according to their age, giving a higher security score to older publicly known vulnerabilities. © 2022 by the authors.
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| 2. |
- Ahmadi Mehri, Vida, et al.
(författare)
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Automated Patch Management : An Empirical Evaluation Study
- 2023
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Ingår i: Proceedings of the 2023 IEEE International Conference on Cyber Security and Resilience, CSR 2023. - : IEEE. - 9798350311709 ; , s. 321-328
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Konferensbidrag (refereegranskat)abstract
- Vulnerability patch management is one of IT organizations' most complex issues due to the increasing number of publicly known vulnerabilities and explicit patch deadlines for compliance. Patch management requires human involvement in testing, deploying, and verifying the patch and its potential side effects. Hence, there is a need to automate the patch management procedure to keep the patch deadline with a limited number of available experts. This study proposed and implemented an automated patch management procedure to address mentioned challenges. The method also includes logic to automatically handle errors that might occur in patch deployment and verification. Moreover, the authors added an automated review step before patch management to adjust the patch prioritization list if multiple cumulative patches or dependencies are detected. The result indicated that our method reduced the need for human intervention, increased the ratio of successfully patched vulnerabilities, and decreased the execution time of vulnerability risk management.
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| 3. |
- Ahmadi Mehri, Vida, et al.
(författare)
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Designing a Secure IoT System Architecture from a Virtual Premise for a Collaborative AI Lab
- 2019
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Konferensbidrag (refereegranskat)abstract
- IoT systems are increasingly composed out of flexible, programmable, virtualised, and arbitrarily chained IoT elements and services using portable code. Moreover, they might be sliced, i.e. allowing multiple logical IoT systems (network + application) to run on top of a shared physical network and compute infrastructure. However, implementing and designing particularly security mechanisms for such IoT systems is challenging since a) promising technologies are still maturing, and b) the relationships among the many requirements, technologies and components are difficult to model a-priori.The aim of the paper is to define design cues for the security architecture and mechanisms of future, virtualised, arbitrarily chained, and eventually sliced IoT systems. Hereby, our focus is laid on the authorisation and authentication of user, host, and code integrity in these virtualised systems. The design cues are derived from the design and implementation of a secure virtual environment for distributed and collaborative AI system engineering using so called AI pipelines. The pipelines apply chained virtual elements and services and facilitate the slicing of the system. The virtual environment is denoted for short as the virtual premise (VP). The use-case of the VP for AI design provides insight into the complex interactions in the architecture, leading us to believe that the VP concept can be generalised to the IoT systems mentioned above. In addition, the use-case permits to derive, implement, and test solutions. This paper describes the flexible architecture of the VP and the design and implementation of access and execution control in virtual and containerised environments.
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| 4. |
- Ahmadi Mehri, Vida, et al.
(författare)
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Flexible Privacy and High Trust in the Next Generation Internet : The Use Case of a Cloud-based Marketplace for AI
- 2017
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Konferensbidrag (refereegranskat)abstract
- Cloudified architectures facilitate resource ac-cess and sharing which is independent from physical lo-cations. They permit high availability of resources at lowoperational costs. These advantages, however, do not comefor free. End users might fear that they lose control overthe location of their data and, thus, of their autonomy indeciding to whom the data is communicate to. Thus, strongprivacy and trust concerns arise for end users.In this work we will review and investigate privacy andtrust requirements for Cloud systems in general and for acloud-based marketplace (CMP) for AI in particular. We willinvestigate whether and how the current privacy and trustdimensions can be applied to Clouds and for the design ofa CMP. We also propose the concept of a "virtual premise"for enabling "Privacy-by-Design" [1] in Clouds. The ideaof a "virtual premise" might probably not be a universalsolution for any privacy requirement. However, we expectthat it provides flexibility in designing privacy in Cloudsand thus leading to higher trust.
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| 5. |
- Ahmadi Mehri, Vida, et al.
(författare)
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Normalization Framework for Vulnerability Risk Management in Cloud
- 2021
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Ingår i: Proceedings - 2021 International Conference on Future Internet of Things and Cloud, FiCloud 2021. - : IEEE. ; , s. 99-106
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Konferensbidrag (refereegranskat)abstract
- Vulnerability Risk Management (VRM) is a critical element in cloud security that directly impacts cloud providers’ security assurance levels. Today, VRM is a challenging process because of the dramatic increase of known vulnerabilities (+26% in the last five years), and because it is even more dependent on the organization’s context. Moreover, the vulnerability’s severity score depends on the Vulnerability Database (VD) selected as a reference in VRM. All these factors introduce a new challenge for security specialists in evaluating and patching the vulnerabilities. This study provides a framework to improve the classification and evaluation phases in vulnerability risk management while using multiple vulnerability databases as a reference. Our solution normalizes the severity score of each vulnerability based on the selected security assurance level. The results of our study highlighted the role of the vulnerability databases in patch prioritization, showing the advantage of using multiple VDs.
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| 6. |
- Ahmadi Mehri, Vida, et al.
(författare)
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Normalization of Severity Rating for Automated Context-aware Vulnerability Risk Management
- 2020
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Ingår i: Proceedings - 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2020. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781728184142 ; , s. 200-205
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Konferensbidrag (refereegranskat)abstract
- In the last three years, the unprecedented increase in discovered vulnerabilities ranked with critical and high severity raise new challenges in Vulnerability Risk Management (VRM). Indeed, identifying, analyzing and remediating this high rate of vulnerabilities is labour intensive, especially for enterprises dealing with complex computing infrastructures such as Infrastructure-as-a-Service providers. Hence there is a demand for new criteria to prioritize vulnerabilities remediation and new automated/autonomic approaches to VRM.In this paper, we address the above challenge proposing an Automated Context-aware Vulnerability Risk Management (AC- VRM) methodology that aims: to reduce the labour intensive tasks of security experts; to prioritize vulnerability remediation on the basis of the organization context rather than risk severity only. The proposed solution considers multiple vulnerabilities databases to have a great coverage on known vulnerabilities and to determine the vulnerability rank. After the description of the new VRM methodology, we focus on the problem of obtaining a single vulnerability score by normalization and fusion of ranks obtained from multiple vulnerabilities databases. Our solution is a parametric normalization that accounts for organization needs/specifications.
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| 7. |
- Ahmadi Mehri, Vida, et al.
(författare)
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Privacy and DRM Requirements for Collaborative Development of AI Application
- 2019
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Ingår i: ACM International Conference Proceeding Series. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450364485
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Konferensbidrag (refereegranskat)abstract
- The use of data is essential for the capabilities of Data-driven Artificial intelligence (AI), Deep Learning and Big Data analysis techniques. This data usage, however, raises intrinsically the concerns on data privacy. In addition, supporting collaborative development of AI applications across organisations has become a major need in AI system design. Digital Rights Management (DRM) is required to protect intellectual property in such collaboration. As a consequence of DRM, privacy threats and privacy-enforcing mechanisms will interact with each other.This paper describes the privacy and DRM requirements in collaborative AI system design using AI pipelines. It describes the relationships between DRM and privacy and outlines the threats against these non-functional features. Finally, the paper provides first security architecture to protect against the threats on DRM and privacy in collaborative AI design using AI pipelines.
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| 8. |
- Ahmadi Mehri, Vida, et al.
(författare)
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Privacy and trust in cloud-based marketplaces for AI and data resources
- 2017
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Ingår i: IFIP Advances in Information and Communication Technology. - Cham : Springer New York LLC. - 9783319591704 ; , s. 223-225
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Konferensbidrag (refereegranskat)abstract
- The processing of the huge amounts of information from the Internet of Things (IoT) has become challenging. Artificial Intelligence (AI) techniques have been developed to handle this task efficiently. However, they require annotated data sets for training, while manual preprocessing of the data sets is costly. The H2020 project “Bonseyes” has suggested a “Market Place for AI”, where the stakeholders can engage trustfully in business around AI resources and data sets. The MP permits trading of resources that have high privacy requirements (e.g. data sets containing patient medical information) as well as ones with low requirements (e.g. fuel consumption of cars) for the sake of its generality. In this abstract we review trust and privacy definitions and provide a first requirement analysis for them with regards to Cloud-based Market Places (CMPs). The comparison of definitions and requirements allows for the identification of the research gap that will be addressed by the main authors PhD project. © IFIP International Federation for Information Processing 2017.
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| 9. |
- Ahmadi Mehri, Vida
(författare)
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Towards Automated Context-aware Vulnerability Risk Management
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The information security landscape continually evolves with increasing publicly known vulnerabilities (e.g., 25064 new vulnerabilities in 2022). Vulnerabilities play a prominent role in all types of security related attacks, including ransomware and data breaches. Vulnerability Risk Management (VRM) is an essential cyber defense mechanism to eliminate or reduce attack surfaces in information technology. VRM is a continuous procedure of identification, classification, evaluation, and remediation of vulnerabilities. The traditional VRM procedure is time-consuming as classification, evaluation, and remediation require skills and knowledge of specific computer systems, software, network, and security policies. Activities requiring human input slow down the VRM process, increasing the risk of exploiting a vulnerability.The thesis introduces the Automated Context-aware Vulnerability Risk Management (ACVRM) methodology to improve VRM procedures by automating the entire VRM cycle and reducing the procedure time and experts' intervention. ACVRM focuses on the challenging stages (i.e., classification, evaluation, and remediation) of VRM to support security experts in promptly prioritizing and patching the vulnerabilities. ACVRM concept is designed and implemented in a test environment for proof of concept. The efficiency of patch prioritization by ACVRM compared against a commercial vulnerability management tool (i.e., Rudder). ACVRM prioritized the vulnerability based on the patch score (i.e., the numeric representation of the vulnerability characteristic and the risk), the historical data, and dependencies. The experiments indicate that ACVRM could rank the vulnerabilities in the organization's context by weighting the criteria used in patch score calculation. The automated patch deployment is implemented with three use cases to investigate the impact of learning from historical events and dependencies on the success rate of the patch and human intervention. Our finding shows that ACVRM reduced the need for human actions, increased the ratio of successfully patched vulnerabilities, and decreased the cycle time of VRM process.
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| 10. |
- Ahmadi Mehri, Vida, et al.
(författare)
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Towards Privacy Requirements for Collaborative Development of AI Applications
- 2018
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Ingår i: 14th Swedish National Computer Networking Workshop (SNCNW).
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Konferensbidrag (refereegranskat)abstract
- The use of data is essential for the capabilities of Data- driven Artificial intelligence (AI), Deep Learning and Big Data analysis techniques. The use of data, however, raises intrinsically the concern of the data privacy, in particular for the individuals that provide data. Hence, data privacy is considered as one of the main non-functional features of the Next Generation Internet. This paper describes the privacy challenges and requirements for collaborative AI application development. We investigate the constraints of using digital right management for supporting collaboration to address the privacy requirements in the regulation.
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