ORCID Profile
0000-0003-4071-4596
Current Organisations
Blekinge Institute of Technology
,
Colorado State University
,
University of Pretoria
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Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: ACM
Date: 31-03-2020
Publisher: Insight Society
Date: 14-02-2018
Publisher: MDPI AG
Date: 23-06-2021
DOI: 10.3390/ELECTRONICS10131519
Abstract: The emergence of unmanned aerial vehicles (also referred to as drones) has transformed the digital landscape of surveillance and supply chain logistics, especially in terrains where such was previously deemed unattainable. Moreover, the adoption of drones has further led to the proliferation of erse drone types and drone-related criminality, which has introduced a myriad of security and forensics-related concerns. As a step towards understanding the state-of-the-art research into these challenges and potential approaches to mitigation, this study provides a detailed review of existing digital forensic models using the Design Science Research method. The outcome of this study generated in-depth knowledge of the research challenges and opportunities through which an effective investigation can be carried out on drone-related incidents. Furthermore, a potential generic investigation model has been proposed. The findings presented in this study are essentially relevant to forensic researchers and practitioners towards a guided methodology for drone-related event investigation. Ultimately, it is important to mention that this study presents a background for the development of international standardization for drone forensics.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: IEEE
Date: 08-2018
Publisher: IEEE
Date: 05-2016
Publisher: Insight Society
Date: 31-03-2018
Publisher: Springer Science and Business Media LLC
Date: 05-12-2020
DOI: 10.1007/S41870-020-00585-8
Abstract: The phenomenon of network vigilantism is autonomously attributed to how anomalies and obscure activities from adversaries can be tracked in real-time. Needless to say, in today’s dynamic, virtualized, and complex network environments, it has become undeniably necessary for network administrators, analysts as well as engineers to practice network vigilantism, on traffic as well as other network events in real-time. The reason is to understand the exact security posture of an organization’s network environment at any given time. This is driven by the fact that modern network environments do, not only present new opportunities to organizations but also a different set of new and complex cybersecurity challenges that need to be resolved daily. The growing size, scope, complexity, and volume of networked devices in our modern network environments also makes it hard even for the most experienced network administrators to independently provide the breadth and depth of knowledge needed to oversee or diagnose complex network problems. Besides, with the growing number of Cyber Security Threats (CSTs) in the world today, many organisations have been forced to change the way they plan, develop and implement cybersecurity strategies as a way to reinforce their ability to respond to cybersecurity incidents. This paper, therefore, examines the relevance of Real-Time Monitoring (RTM) as a supplementary security component of vigilantism in modern network environments, more especially for proper planning, preparedness, and mitigation in case of a cybersecurity incident. Additionally, this paper also investigates some of the key issues and challenges surrounding the implementation of RTM for security vigilantism in our modern network environments.
Publisher: Springer International Publishing
Date: 13-08-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Wiley
Date: 09-03-2020
DOI: 10.1002/WFS2.1372
Abstract: A Cloud Forensic Readiness as a Service (CFRaaS) model allows an environment to preemptively accumulate relevant potential digital evidence (PDE) which may be needed during a post‐event response process. The benefit of applying a CFRaaS model in a cloud environment, is that, it is designed to prevent the modification/t ering of the cloud architectures or the infrastructure during the reactive process, which if it could, may end up having far‐reaching implications. The authors of this article present the reactive process as a very costly exercise when the infrastructure must be reprogrammed every time the process is conducted. This may h er successful investigation from the forensic experts and law enforcement agencies perspectives. The CFRaaS model, in its current state, has not been presented in a way that can help to classify or visualize the different types of potential evidence in all the cloud deployable models, and this may limit the expectations of what or how the required PDE may be collected. To address this problem, the article presents the CFRaaS from a holistic ontology‐driven perspective, which allows the forensic experts to be able to apply the CFRaaS based on its simplicity of the concepts, relationship or semantics between different form of potential evidence, as well as how the security of a digital environment being investigated could be upheld. The CFRaaS in this context follows a fundamental ontology engineering approach that is based on the classical Resource Description Framework. The proposed ontology‐driven approach to CFRaaS is, therefore, a knowledge‐base that uses layer‐dependencies, which could be an essential toolkit for digital forensic examiners and other stakeholders in cloud‐security. The implementation of this approach could further provide a platform to develop other knowledge base components for cloud forensics and security. This article is categorized under: Digital and Multimedia Science Cloud Forensics Digital and Multimedia Science Cyber Threat Intelligence Digital and Multimedia Science Multimedia Forensics
Publisher: IEEE
Date: 05-2017
Publisher: Wiley
Date: 11-08-2021
DOI: 10.1002/SPY2.182
Abstract: The importance of demonstrating the correctness of forensic analysis tools and automated incident management tools reinforces the need for a finite state machine (FSM) engine that can generate automated forensic processes. Hence, in this paper, we present an event‐based FSM representation for Cloud Forensic Readiness as a Service (CFRaaS), where we also show how the FSM's predetermined states and transitions could be used to formulate an automated forensic process and generate a hypothesis for litigation purposes. Specifically, this proposition comprises a two‐step level CFRaaS‐FSM with possible transitions and states. This representation is useful because it can alert digital forensic investigators on how to deduce current and next state of attacks based on transitions and current states.
Publisher: Wiley
Date: 16-02-2021
DOI: 10.1002/SPY2.151
Publisher: MDPI AG
Date: 08-09-2021
DOI: 10.3390/S21186018
Abstract: Continuous and emerging advances in Information and Communication Technology (ICT) have enabled Internet-of-Things (IoT)-to-Cloud applications to be induced by data pipelines and Edge Intelligence-based architectures. Advanced vehicular networks greatly benefit from these architectures due to the implicit functionalities that are focused on realizing the Internet of Vehicle (IoV) vision. However, IoV is susceptible to attacks, where adversaries can easily exploit existing vulnerabilities. Several attacks may succeed due to inadequate or ineffective authentication techniques. Hence, there is a timely need for hardening the authentication process through cutting-edge access control mechanisms. This paper proposes a Blockchain-based Multi-Factor authentication model that uses an embedded Digital Signature (MFBC_eDS) for vehicular clouds and Cloud-enabled IoV. Our proposed MFBC_eDS model consists of a scheme that integrates the Security Assertion Mark-up Language (SAML) to the Single Sign-On (SSO) capabilities for a connected edge to cloud ecosystem. MFBC_eDS draws an essential comparison with the baseline authentication scheme suggested by Karla and Sood. Based on the foundations of Karla and Sood’s scheme, an embedded Probabilistic Polynomial-Time Algorithm (ePPTA) and an additional Hash function for the Pi generated during Karla and Sood’s authentication were proposed and discussed. The preliminary analysis of the proposition shows that the approach is more suitable to counter major adversarial attacks in an IoV-centered environment based on the Dolev–Yao adversarial model while satisfying aspects of the Confidentiality, Integrity, and Availability (CIA) triad.
Publisher: Springer International Publishing
Date: 02-11-2020
Publisher: MDPI AG
Date: 03-05-2022
DOI: 10.3390/ELECTRONICS11091468
Abstract: The popularity of unique image compression features of image files opens an interesting research analysis process, given that several digital forensics cases are related to erse file types. Of interest has been fragmented file carving and recovery which forms a major aspect of digital forensics research on JPEG files. Whilst there exist several challenges, this paper focuses on the challenge of determining the co-existence of JPEG fragments within various file fragment types. Existing works have exhibited a high false-positive rate, therefore rendering the need for manual validation. This study develops a technique that can identify the unique signature of JPEG 8 × 8 blocks using the Error Level Analysis technique, implemented in MATLAB. The experimental result that was conducted with 21 images of JFIF format with 1008 blocks shows the efficacy of the proposed technique. Specifically, the initial results from the experiment show that JPEG 8 × 8 blocks have unique characteristics which can be leveraged for digital forensics. An investigator could, therefore, search for the unique characteristics to identify a JPEG fragment during a digital investigation process.
Publisher: IEEE
Date: 08-2018
Publisher: IEEE
Date: 12-2018
Publisher: IEEE
Date: 07-2017
No related grants have been discovered for Victor R. Kebande.