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Dr Haider al-Khateeb holds a position as a Reader in Cybersecurity at the Wolverhampton Cyber Research Institute (WCRI), University of Wolverhampton. He is a project lead for R&D and Knowledge Transfer activities with over 12 years of experience in the UK’s HE sector. Haider is actively engaged with the latest trends on Distributed Digital Forensics and Incident Response (DFIR), Cyber Resilience, Cyber Threat Intelligence (CTI), and Online Safety for vulnerable groups. He has published numerous professional and peer-reviewed articles, participated in a broad range of funded projects and worked with SMEs to launch new innovative products. Haider delivers hands-on training on topics such as Ethical Hacking as part of a proactive approach to protect computer systems. He has many years of experience with Transnational Education (TNE) and supported MSc programmes at Northumbria University, as well as delivering training in Cybersecurity through leading IT training providers in the UK such as QA Ltd. Haider has also worked on the NCSC’s CyberFirst initiative, a pivotal part of the UK government’s National Cyber Security Programme to develop the UK's next generation of cyber professionals. Earlier in his career, he was a lecturer at the School of Computer Science and Technology, University of Bedfordshire.
Disability hate crime is under-reported in the UK with perceived limited support given to the victims. The use of online communication resulted in cyber-disability hate cases, recognised by the Police with the addition of an ‘online-flag’ in the documentation. However, the cases remain under-reported, with potential individual, societal and organisational barriers to reporting especially during a pandemic. This paper aims to contextualise the reporting of cyber-disability hate cases, identify potential barriers, and provide recommendations to improve support to victims by the Police. The retrospective examination was carried out on disability-related cyber incidents documented by a police force in the UK for 19 months. Among 3,349 cyber-crimes, 23 cases were included. The analysis covered descriptive statistics and qualitative document analysis (QDA). Only 0.7% of cyber incidents or 6.7% of cyber-hate incidents were disability related. The age of victims ranged between 15 and 61 years, with a mean of 25.8 years. Most of the victims (78%) were from White ethnic background, and the majority were females (61.5%). Three overarching themes emerged from the qualitative data as influencers of reporting or documentation, these were: psychological impact, fear for safety, and the type of disability. Cyber-offences resulted in a serious impact on wellbeing, however, cases that included people with visible disabilities were more documented. Further awareness-raising targeting the police and public is needed to understand the impact of cyber-offences and recognise the different types of disabilities, which might encourage both reporting and documentation.
Zhraa A. Alhaboby; Haider M. Al-Khateeb; James Barnes; Hamid Jahankhani; Melanie Pitchford; Liesl Conradie; Emma Short. Cyber-Disability Hate Cases in the UK: The Documentation by the Police and Potential Barriers to Reporting. Cyberspace 2021, 123 -133.
AMA StyleZhraa A. Alhaboby, Haider M. Al-Khateeb, James Barnes, Hamid Jahankhani, Melanie Pitchford, Liesl Conradie, Emma Short. Cyber-Disability Hate Cases in the UK: The Documentation by the Police and Potential Barriers to Reporting. Cyberspace. 2021; ():123-133.
Chicago/Turabian StyleZhraa A. Alhaboby; Haider M. Al-Khateeb; James Barnes; Hamid Jahankhani; Melanie Pitchford; Liesl Conradie; Emma Short. 2021. "Cyber-Disability Hate Cases in the UK: The Documentation by the Police and Potential Barriers to Reporting." Cyberspace , no. : 123-133.
Connected cars have a massive impact on the automotive sector, and whilst this catalyst and disruptor technology introduce threats, it brings opportunities to address existing vehicle-related crimes such as carjacking. Connected cars are fitted with sensors, and capable of sophisticated computational processing which can be used to model and differentiate drivers as means of layered security. We generate a dataset collecting 14 h of driving in the city of London. The route was 8.1 miles long and included various road conditions such as roundabouts, traffic lights, and several speed zones. We identify and rank the features from the driving segments, classify our sample using Random Forest, and optimise the learning-based model with 98.84% accuracy (95% confidence) given a small 10 s driving window size. Differences in driving patterns were uncovered to distinguish between female and male drivers especially through variations in longitudinal acceleration, driving speed, torque and revolutions per minute.
Gabriela Ahmadi-Assalemi; Haider M. Al-Khateeb; Carsten Maple; Gregory Epiphaniou; Mohammad Hammoudeh; Hamid Jahankhani; Prashant Pillai. Optimising driver profiling through behaviour modelling of in-car sensor and global positioning system data. Computers & Electrical Engineering 2021, 91, 107047 .
AMA StyleGabriela Ahmadi-Assalemi, Haider M. Al-Khateeb, Carsten Maple, Gregory Epiphaniou, Mohammad Hammoudeh, Hamid Jahankhani, Prashant Pillai. Optimising driver profiling through behaviour modelling of in-car sensor and global positioning system data. Computers & Electrical Engineering. 2021; 91 ():107047.
Chicago/Turabian StyleGabriela Ahmadi-Assalemi; Haider M. Al-Khateeb; Carsten Maple; Gregory Epiphaniou; Mohammad Hammoudeh; Hamid Jahankhani; Prashant Pillai. 2021. "Optimising driver profiling through behaviour modelling of in-car sensor and global positioning system data." Computers & Electrical Engineering 91, no. : 107047.
By law, schools are required to protect the well-being of students against problems such as on-campus bullying and physical abuse. In the UK, a report by the Office for Education (OfE) showed 17% of young people had been bullied during 2017–2018. This problem continues to prevail with consequences including depression, anxiety, suicidal thoughts, and eating disorders. Additionally, recent evidence suggests this type of victimisation could intensify existing health complications. This study investigates the opportunities provided by Internet of Medical Things (IoMT) data towards next-generation safeguarding. A new model is developed based on blockchain technology to enable real-time intervention triggered by IoMT data that can be used to detect stressful events, e.g., when bullying takes place. The model utilises private permissioned blockchain to manage IoMT data to achieve quicker and better decision-making while revolutionising aspects related to compliance, double-entry, confidentiality, and privacy. The feasibility of the model and the interaction between the sensors and the blockchain was simulated. To facilitate a close approximation of an actual IoMT environment, we clustered and decomposed existing medical sensors to their attributes, including their function, for a variety of scenarios. Then, we demonstrated the performance and capabilities of the emulator under different loads of sensor-generated data. We argue to the suitability of this emulator for schools and medical centres to conduct feasibility studies to address sensor data with disruptive data processing and management technologies.
Nikolaos Ersotelos; Mirko Bottarelli; Haider Al-Khateeb; Gregory Epiphaniou; Zhraa Alhaboby; Prashant Pillai; Amar Aggoun. Blockchain and IoMT against Physical Abuse: Bullying in Schools as a Case Study. Journal of Sensor and Actuator Networks 2020, 10, 1 .
AMA StyleNikolaos Ersotelos, Mirko Bottarelli, Haider Al-Khateeb, Gregory Epiphaniou, Zhraa Alhaboby, Prashant Pillai, Amar Aggoun. Blockchain and IoMT against Physical Abuse: Bullying in Schools as a Case Study. Journal of Sensor and Actuator Networks. 2020; 10 (1):1.
Chicago/Turabian StyleNikolaos Ersotelos; Mirko Bottarelli; Haider Al-Khateeb; Gregory Epiphaniou; Zhraa Alhaboby; Prashant Pillai; Amar Aggoun. 2020. "Blockchain and IoMT against Physical Abuse: Bullying in Schools as a Case Study." Journal of Sensor and Actuator Networks 10, no. 1: 1.
The world is experiencing a rapid growth of smart cities accelerated by Industry 4.0, including the Internet of Things (IoT), and enhanced by the application of emerging innovative technologies which in turn create highly fragile and complex cyber–physical–natural ecosystems. This paper systematically identifies peer-reviewed literature and explicitly investigates empirical primary studies that address cyber resilience and digital forensic incident response (DFIR) aspects of cyber–physical systems (CPSs) in smart cities. Our findings show that CPSs addressing cyber resilience and support for modern DFIR are a recent paradigm. Most of the primary studies are focused on a subset of the incident response process, the “detection and analysis” phase whilst attempts to address other parts of the DFIR process remain limited. Further analysis shows that research focused on smart healthcare and smart citizen were addressed only by a small number of primary studies. Additionally, our findings identify a lack of available real CPS-generated datasets limiting the experiments to mostly testbed type environments or in some cases authors relied on simulation software. Therefore, contributing this systematic literature review (SLR), we used a search protocol providing an evidence-based summary of the key themes and main focus domains investigating cyber resilience and DFIR addressed by CPS frameworks and systems. This SLR also provides scientific evidence of the gaps in the literature for possible future directions for research within the CPS cybersecurity realm. In total, 600 papers were surveyed from which 52 primary studies were included and analysed.
Gabriela Ahmadi-Assalemi; Haider Al-Khateeb; Gregory Epiphaniou; Carsten Maple. Cyber Resilience and Incident Response in Smart Cities: A Systematic Literature Review. Smart Cities 2020, 3, 894 -927.
AMA StyleGabriela Ahmadi-Assalemi, Haider Al-Khateeb, Gregory Epiphaniou, Carsten Maple. Cyber Resilience and Incident Response in Smart Cities: A Systematic Literature Review. Smart Cities. 2020; 3 (3):894-927.
Chicago/Turabian StyleGabriela Ahmadi-Assalemi; Haider Al-Khateeb; Gregory Epiphaniou; Carsten Maple. 2020. "Cyber Resilience and Incident Response in Smart Cities: A Systematic Literature Review." Smart Cities 3, no. 3: 894-927.
Gregory Epiphaniou; Prashant Pillai; Mirko Bottarelli; Haider Al-Khateeb; Mohammad Hammoudeh; Carsten Maple. Corrections to “Electronic Regulation of Data Sharing and Processing Using Smart Ledger Technologies for Supply-Chain Security”. IEEE Transactions on Engineering Management 2020, 67, 979 -979.
AMA StyleGregory Epiphaniou, Prashant Pillai, Mirko Bottarelli, Haider Al-Khateeb, Mohammad Hammoudeh, Carsten Maple. Corrections to “Electronic Regulation of Data Sharing and Processing Using Smart Ledger Technologies for Supply-Chain Security”. IEEE Transactions on Engineering Management. 2020; 67 (3):979-979.
Chicago/Turabian StyleGregory Epiphaniou; Prashant Pillai; Mirko Bottarelli; Haider Al-Khateeb; Mohammad Hammoudeh; Carsten Maple. 2020. "Corrections to “Electronic Regulation of Data Sharing and Processing Using Smart Ledger Technologies for Supply-Chain Security”." IEEE Transactions on Engineering Management 67, no. 3: 979-979.
The rise of new digital economies and data-driven supply-chains seeks to revolutionalise the ways information is transferred, processed and analysed across different industry segments in the value-creation. This data-driven manufacturing revolution promises to increase productivity, democratise data sharing capabilities and foster industrial growth in scales never seen before. The traditional transactional models are to be re-visited, and distributed data storage architectures are to be re-designed to accommodate for optimised data flows across different organisation units. Data is increasingly becoming a strategic business resource that through innovation in existing sharing and processing approaches can decompose business bottlenecks in existing production lines and processes and disrupt traditional supply-chain models. This work seeks to articulate a state-of-the-art review of the application and impact of ML techniques and distributed Ledger technologies to further disrupt supply-chain capabilities with regards to data accuracy and completeness.
Gregory Epiphaniou; Mirko Bottarelli; Haider Al-Khateeb; Nikolaos Th. Ersotelos; John Kanyaru; Vinita Nahar. Smart Distributed Ledger Technologies in Industry 4.0: Challenges and Opportunities in Supply Chain Management. Cyberspace 2020, 319 -345.
AMA StyleGregory Epiphaniou, Mirko Bottarelli, Haider Al-Khateeb, Nikolaos Th. Ersotelos, John Kanyaru, Vinita Nahar. Smart Distributed Ledger Technologies in Industry 4.0: Challenges and Opportunities in Supply Chain Management. Cyberspace. 2020; ():319-345.
Chicago/Turabian StyleGregory Epiphaniou; Mirko Bottarelli; Haider Al-Khateeb; Nikolaos Th. Ersotelos; John Kanyaru; Vinita Nahar. 2020. "Smart Distributed Ledger Technologies in Industry 4.0: Challenges and Opportunities in Supply Chain Management." Cyberspace , no. : 319-345.
Precision healthcare is an emerging concept that will see technology-driven digital transformation of the health service. It enables customised patient outcomes via the development of novel, targeted medical approaches with a focus on intelligent, data-centric smart healthcare models. Currently, precision healthcare is seen as a challenging model to apply due to the complexity of the healthcare ecosystem, which is a multi-level and multifaceted environment with high real-time interactions among disciplines, practitioners, patients and discrete computer systems. Digital Twins (DT) pairs individual physical artefacts with digital models reflecting their status in real-time. Creating a live-model for healthcare services introduces new opportunities for patient care including better risk assessment and evaluation without disturbing daily activities. In this article, to address design and management in this complexity, we examine recent work in Digital Twins (DT) to investigate the goals of precision healthcare at a patient and healthcare system levels. We further discuss the role of DT to achieve precision healthcare, proposed frameworks, the value of active participation and continuous monitoring, and the cyber-security challenges and ethical implications for this emerging paradigm.
Gabriela Ahmadi-Assalemi; Haider Al-Khateeb; Carsten Maple; Gregory Epiphaniou; Zhraa A. Alhaboby; Sultan Alkaabi; Doaa Alhaboby. Digital Twins for Precision Healthcare. Advanced Sciences and Technologies for Security Applications 2020, 133 -158.
AMA StyleGabriela Ahmadi-Assalemi, Haider Al-Khateeb, Carsten Maple, Gregory Epiphaniou, Zhraa A. Alhaboby, Sultan Alkaabi, Doaa Alhaboby. Digital Twins for Precision Healthcare. Advanced Sciences and Technologies for Security Applications. 2020; ():133-158.
Chicago/Turabian StyleGabriela Ahmadi-Assalemi; Haider Al-Khateeb; Carsten Maple; Gregory Epiphaniou; Zhraa A. Alhaboby; Sultan Alkaabi; Doaa Alhaboby. 2020. "Digital Twins for Precision Healthcare." Advanced Sciences and Technologies for Security Applications , no. : 133-158.
Forensic age estimation is usually requested by courts, but applications can go beyond the legal requirement to enforce policies or offer age-sensitive services. Various biological features such as the face, bones, skeletal and dental structures can be utilised to estimate age. This article will cover how modern technology has developed to provide new methods and algorithms to digitalise this process for the medical community and beyond. The scientific study of Machine Learning (ML) have introduced statistical models without relying on explicit instructions, instead, these models rely on patterns and inference. Furthermore, the large-scale availability of relevant data (medical images) and computational power facilitated by the availability of powerful Graphics Processing Units (GPUs) and Cloud Computing services have accelerated this transformation in age estimation. Magnetic Resonant Imaging (MRI) and X-ray are examples of imaging techniques used to document bones and dental structures with attention to detail making them suitable for age estimation. We discuss how Convolutional Neural Network (CNN) can be used for this purpose and the advantage of using deep CNNs over traditional methods. The article also aims to evaluate various databases and algorithms used for age estimation using facial images and dental images.
Sultan Alkaabi; Salman Yussof; Haider Al-Khateeb; Gabriela Ahmadi-Assalemi; Gregory Epiphaniou. Deep Convolutional Neural Networks for Forensic Age Estimation: A Review. Cyberspace 2020, 375 -395.
AMA StyleSultan Alkaabi, Salman Yussof, Haider Al-Khateeb, Gabriela Ahmadi-Assalemi, Gregory Epiphaniou. Deep Convolutional Neural Networks for Forensic Age Estimation: A Review. Cyberspace. 2020; ():375-395.
Chicago/Turabian StyleSultan Alkaabi; Salman Yussof; Haider Al-Khateeb; Gabriela Ahmadi-Assalemi; Gregory Epiphaniou. 2020. "Deep Convolutional Neural Networks for Forensic Age Estimation: A Review." Cyberspace , no. : 375-395.
Traditional centralized data storage and processing solutions manifest limitations with regards to overall operational cost and the security and auditability of data. One of the biggest issues with existing solutions is the difficulty of keeping track of who has had access to the data and how the data may have changed over its lifetime; while providing a secure and easy-to-use mechanism to share the data between different users. The ability to electronically regulate data sharing within and across different organizational entities in the supply chain (SC) is an open issue that is only addressed partially by existing legal and regulatory compliance frameworks. In this article, we present Cydon, a decentralized data management platform that executes bespoke distributed applications utilizing a novel search and retrieve algorithm leveraging metadata attributes. Cydon utilizes a smart distributed ledger to offer an immutable audit trail and transaction history for all different levels of data access and modification within a SC and for all data flows within the environment. Results suggest that Cydon provides authorized and fast access to secure distributed data, avoids single points of failure by securely distributing encrypted data across different nodes while maintains an “always-on” chain of custody.
Gregory Epiphaniou; Prashant Pillai; Mirko Bottarelli; Haider Al-Khateeb; Mohammad Hammoudesh; Carsten Maple. Electronic Regulation of Data Sharing and Processing Using Smart Ledger Technologies for Supply-Chain Security. IEEE Transactions on Engineering Management 2020, 67, 1059 -1073.
AMA StyleGregory Epiphaniou, Prashant Pillai, Mirko Bottarelli, Haider Al-Khateeb, Mohammad Hammoudesh, Carsten Maple. Electronic Regulation of Data Sharing and Processing Using Smart Ledger Technologies for Supply-Chain Security. IEEE Transactions on Engineering Management. 2020; 67 (4):1059-1073.
Chicago/Turabian StyleGregory Epiphaniou; Prashant Pillai; Mirko Bottarelli; Haider Al-Khateeb; Mohammad Hammoudesh; Carsten Maple. 2020. "Electronic Regulation of Data Sharing and Processing Using Smart Ledger Technologies for Supply-Chain Security." IEEE Transactions on Engineering Management 67, no. 4: 1059-1073.
Hand-written signatures are marked on documents to establish legally binding evidence of identity and intent. However, they are prone to forgery, and the design of an accurate feature extractor to distinguish between highly-skilled forgeries and genuine signatures is a challenging task. In this paper, we propose a Convolution Neural Network (CNN) architecture for Signature Verification (SV). The algorithm is trained using two signatures, genuine and forged. Then the SV module performs a classification task to determine if any two signatures are of the same individual or not. The simulation results show that the proposed method can achieve 27% (relatively) better results than the benchmark scheme. The paper also integrated different data augmentation techniques for the signature data, which further improved the efficiency of the proposed method by 14% (relative).
Sultan Alkaabi; Salman Yussof; Sameera Almulla; Haider Al-Khateeb; Abdulrahman A AlAbdulsalam. A Novel Architecture to verify Offline Hand-written Signatures using Convolutional Neural Network. 2019 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) 2019, 1 -4.
AMA StyleSultan Alkaabi, Salman Yussof, Sameera Almulla, Haider Al-Khateeb, Abdulrahman A AlAbdulsalam. A Novel Architecture to verify Offline Hand-written Signatures using Convolutional Neural Network. 2019 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT). 2019; ():1-4.
Chicago/Turabian StyleSultan Alkaabi; Salman Yussof; Sameera Almulla; Haider Al-Khateeb; Abdulrahman A AlAbdulsalam. 2019. "A Novel Architecture to verify Offline Hand-written Signatures using Convolutional Neural Network." 2019 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) , no. : 1-4.
Current authentication protocols seek to establish authenticated sessions over insecure channels while maintaining a small footprint considering the energy consumption and computational overheads. Traditional authentication schemes must store a form of authentication data on the devices, putting this data at risk. Approaches based on purely public/private key infrastructure come with additional computation and maintenance costs. This work proposes a novel non-interactive zero-knowledge (NIZKP) authentication protocol that incorporates the limiting factors in IoT communication devices and sensors. Our protocol considers the inherent network instability and replaces the ZKP NP-hard problem using the Merkle tree structure for the creation of the authentication challenge. A series of simulations evaluate the performance of NIZKP against traditional ZKP approaches based on graph isomorphism. A set of performance metrics has been used, namely the channel rounds for client authentication, effects of the authentication processes, and the protocol interactions to determine areas of improvements. The simulation results indicate empirical evidence for the suitability of our NIKP approach for authentication purposes in resource-constrained IoT environments.
Marcus Walshe; Gregory Epiphaniou; Haider Al-Khateeb; Mohammad Hammoudeh; Vasilios Katos; Ali Dehghantanha. Non-interactive zero knowledge proofs for the authentication of IoT devices in reduced connectivity environments. Ad Hoc Networks 2019, 95, 101988 .
AMA StyleMarcus Walshe, Gregory Epiphaniou, Haider Al-Khateeb, Mohammad Hammoudeh, Vasilios Katos, Ali Dehghantanha. Non-interactive zero knowledge proofs for the authentication of IoT devices in reduced connectivity environments. Ad Hoc Networks. 2019; 95 ():101988.
Chicago/Turabian StyleMarcus Walshe; Gregory Epiphaniou; Haider Al-Khateeb; Mohammad Hammoudeh; Vasilios Katos; Ali Dehghantanha. 2019. "Non-interactive zero knowledge proofs for the authentication of IoT devices in reduced connectivity environments." Ad Hoc Networks 95, no. : 101988.
Distributed Ledger Technologies are promised to be genuinely disruptive in a variety of industries and sectors, from the food supply, pharmaceutical, real estate, financial services, academia and healthcare. Blockchain technologies vastly improve the flow of data within and among companies and people and transform the way that the Internet is used to exchange value. The use of distributed applications can revolutionise and simplify complex system tasks and create new substructures in a fully developing distributed economy as part of Industry 4.0. Blockchain technologies have the enormous potential to transform healthcare and existing security, privacy and interoperability issues allowing more flexibility and freedom to patients and their data. New economies of scale are emerging for health information exchange that makes the management of electronic records easier while eliminating fictions and costs associated with current intermediaries. This chapter seeks to explore the idiosyncrasies of Blockchain technology and its adaptation in healthcare with an emphasis to its core features and applications. We expand to the key risks and opportunities of Blockchain and briefly discuss this pilot studies in healthcare.
Gregory Epiphaniou; Herbert Daly; Haider Al-Khateeb. Blockchain and Healthcare. Physics of Automatic Target Recognition 2019, 1 -29.
AMA StyleGregory Epiphaniou, Herbert Daly, Haider Al-Khateeb. Blockchain and Healthcare. Physics of Automatic Target Recognition. 2019; ():1-29.
Chicago/Turabian StyleGregory Epiphaniou; Herbert Daly; Haider Al-Khateeb. 2019. "Blockchain and Healthcare." Physics of Automatic Target Recognition , no. : 1-29.
Blockchain technology can be incorporated into new systems to facilitate modern Digital Forensics and Incident Response (DFIR). For example, it is widely acknowledged that the Internet-of-Things (IoT) has introduced complexity to the cyberspace, however, incident responders should also realise the advantages presented by these new “Digital Witnesses” (DW) to support their investigation. Logs generated by IoT devices can help in the process of event reconstruction, but their integrity -and therefore admissibility- can be achieved only if a Chain-of-Custody (CoC) is maintained within the wider context of an on-going digital investigation. Likewise, the transition to electronic documentation improves data availability, legibility, the utility of notes, and therefore enhances the communication between stakeholders. However, without a proof of validity, these data could be falsified. For example, in an application area such as eHealth, there is a requirement to maintain various existing (and new) rules and regulations concerning authorship, auditing, and the integrity of medical records. Lacking data control could lead to system abuse, fraud and severe compromise of service quality. These concerns can be resolved by implementing an online CoC. In this paper, we discuss the value and means of utilising Blockchain in modern systems to support DFIR. we demonstrate the value of Blockchain to improve the implementation of Digital Forensic Models and discuss why law enforcement and incident responders need to understand Blockchain technology. Furthermore, the admissibility of a Digital Evidence to a Court of Law requires chronological documentation. Hence, we discuss how the CoC can be sustained based on a distributed ledger. Finally, we provide a practical scenario related to eHealth to demonstrate the value of this approach to introduce forensic readiness to computer systems and enable better Police interventions.
Haider Al-Khateeb; Gregory Epiphaniou; Herbert Daly. Blockchain for Modern Digital Forensics: The Chain-of-Custody as a Distributed Ledger. Cyberspace 2019, 149 -168.
AMA StyleHaider Al-Khateeb, Gregory Epiphaniou, Herbert Daly. Blockchain for Modern Digital Forensics: The Chain-of-Custody as a Distributed Ledger. Cyberspace. 2019; ():149-168.
Chicago/Turabian StyleHaider Al-Khateeb; Gregory Epiphaniou; Herbert Daly. 2019. "Blockchain for Modern Digital Forensics: The Chain-of-Custody as a Distributed Ledger." Cyberspace , no. : 149-168.
Industrial Control Systems (ICSs) are responsible for the automation of different processes and the overall control of systems that include highly sensitive potential targets such as nuclear facilities, energy-distribution, water-supply, and mass-transit systems. Given the increased complexity and rapid evolvement of their threat landscape, and the fact that these systems form part of the Critical National infrastructure (CNI), makes them an emerging domain of conflict, terrorist attacks, and a playground for cyberexploitation. Existing layered-defence approaches are increasingly criticised for their inability to adequately protect against resourceful and persistent adversaries. It is therefore essential that emerging techniques, such as orthogonality, be combined with existing security strategies to leverage defence advantages against adaptive and often asymmetrical attack vectors. The concept of orthogonality is relatively new and unexplored in an ICS environment and consists of having assurance control as well as functional control at each layer. Our work seeks to partially articulate a framework where multiple functional and assurance controls are introduced at each layer of ICS architectural design to further enhance security while maintaining critical real-time transfer of command and control traffic.
Mike Mackintosh; Gregory Epiphaniou; Haider Al-Khateeb; Keith Burnham; Prashant Pillai; Mohammad Hammoudeh. Preliminaries of Orthogonal Layered Defence Using Functional and Assurance Controls in Industrial Control Systems. Journal of Sensor and Actuator Networks 2019, 8, 14 .
AMA StyleMike Mackintosh, Gregory Epiphaniou, Haider Al-Khateeb, Keith Burnham, Prashant Pillai, Mohammad Hammoudeh. Preliminaries of Orthogonal Layered Defence Using Functional and Assurance Controls in Industrial Control Systems. Journal of Sensor and Actuator Networks. 2019; 8 (1):14.
Chicago/Turabian StyleMike Mackintosh; Gregory Epiphaniou; Haider Al-Khateeb; Keith Burnham; Prashant Pillai; Mohammad Hammoudeh. 2019. "Preliminaries of Orthogonal Layered Defence Using Functional and Assurance Controls in Industrial Control Systems." Journal of Sensor and Actuator Networks 8, no. 1: 14.
We present an algorithm that allows two users to establish a symmetric cryptographic key by incorporating the most important features of the wireless channel in vehicle-to-vehicle (V2V) communication. Non-reciprocity compensation is combined with turbo codes (TCs) for error reconciliation purposes. For fair comparisons, the indexing technique is applied in conjunction with the non-reciprocity compensation technique. A series of simulations are run to calculate key performance indicators (KPIs). High entropy values are obtained throughout all rounds of simulation during the key extraction process. Furthermore, simulation results indicate a significant improvement in bit mismatch rate (BMR) and key generation rate (KGR) when TCs are used. Increasing the number of iterations in the TC can significantly improve the Bit Error Rate (BER), thus generating more symmetric keys. The key generation rate was reported high ranging from 17 to 19 for the 256-bit symmetric keys per minute with TCs, while it is ranging from 2 to 5 when compared with a sample indexing technique published in the public domain. Finally, simulations proved also improvements for different key lengths as part of the error reconciliation process when TCs are used with an almost regular permutation (ARP) instead of a random permutation.
Dhouha Kbaier Ben Ismail; Petros Karadimas; Gregory Epiphaniou; Haider Al-Khateeb. Optimizing Turbo Codes for Secret Key Generation in Vehicular Ad Hoc Networks. Plant-Microbes-Engineered Nano-particles (PM-ENPs) Nexus in Agro-Ecosystems 2019, 287 -293.
AMA StyleDhouha Kbaier Ben Ismail, Petros Karadimas, Gregory Epiphaniou, Haider Al-Khateeb. Optimizing Turbo Codes for Secret Key Generation in Vehicular Ad Hoc Networks. Plant-Microbes-Engineered Nano-particles (PM-ENPs) Nexus in Agro-Ecosystems. 2019; ():287-293.
Chicago/Turabian StyleDhouha Kbaier Ben Ismail; Petros Karadimas; Gregory Epiphaniou; Haider Al-Khateeb. 2019. "Optimizing Turbo Codes for Secret Key Generation in Vehicular Ad Hoc Networks." Plant-Microbes-Engineered Nano-particles (PM-ENPs) Nexus in Agro-Ecosystems , no. : 287-293.
The world of online advertising is directly dependent on data collection of the online browsing habits of individuals to enable effective advertisement targeting and retargeting. However, these data collection practices can cause leakage of private data belonging to website visitors (end-users) without their knowledge. The growing privacy concern of end-users is amplified by a lack of trust and understanding of what and how advertisement trackers are collecting and using their data. This paper presents an investigation to restore the trust or validate the concerns. We aim to facilitate the assessment of the actual end-user related data being collected by advertising platforms (APs) by means of a critical discussion but also the development of a new tool, AdPExT (Advertising Parameter Extraction Tool), which can be used to extract third-party parameter key-value pairs at an individual key-value level. Furthermore, we conduct a survey covering mostly United Kingdom-based frequent internet users to gather the perceived sensitivity sentiment for various representative tracking parameters. End-users have a definite concern with regards to advertisement tracking of sensitive data by global dominating platforms such as Facebook and Google.
Joseph Waldu Woensdregt; Haider Al-Khateeb; Gregory Epiphaniou; Hamid Jahankhani. AdPExT: Designing a Tool to Assess Information Gleaned from Browsers by Online Advertising Platforms. 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3) 2019, 204 -212.
AMA StyleJoseph Waldu Woensdregt, Haider Al-Khateeb, Gregory Epiphaniou, Hamid Jahankhani. AdPExT: Designing a Tool to Assess Information Gleaned from Browsers by Online Advertising Platforms. 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3). 2019; ():204-212.
Chicago/Turabian StyleJoseph Waldu Woensdregt; Haider Al-Khateeb; Gregory Epiphaniou; Hamid Jahankhani. 2019. "AdPExT: Designing a Tool to Assess Information Gleaned from Browsers by Online Advertising Platforms." 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3) , no. : 204-212.
Research shows that people with long term conditions and disabilities are frequently labelled as vulnerable, and commonly victimised online. They require instrumental support to understand their conditions and empower them to manage their own treatment in everyday life. However, additional short and long term consequences related to cyber-victimisation could intensify existing psychological and health complications. For instance, ‘distress’ as a commonly reported impact of cyber-victimisation could theoretically lead to neurohormonal changes in the blood, increasing cortisol, catecholamine and insulin secretion resulting in increased blood glucose, heartbeat, blood pressure, urination and other changes. Therefore, in this study we demonstrate the need and explain the means towards extending support and risk assessment systems and procedures to cover the collection and preservation of incidents reported by individuals. This can be used to support third-party interventions such as taking a legal action in cases where the impact of cyber-victimisation is seen to escalate and worsen. As such, we first define vulnerable groups with long term conditions and provide a review of the impact of various types of cyber-victimisation on their health management. Then, we discuss how Disease Management Programmes (DMP) developed over time to include web-based applications as an example of existing cost-effective approaches to improve the quality of healthcare provided to people with long term conditions. We then demonstrate the added value of incorporating forensics readiness to enable Police intervention, support the victim’s eligibility for extended instrumental support from national health services. Finally, this level of documentation offers an opportunity to implement more accurate methods to assess risk associated with victimisation.
Zhraa A. Alhaboby; Doaa Alhaboby; Haider M. Al-Khateeb; Gregory Epiphaniou; Dhouha Kbaier Ben Ismail; Hamid Jahankhani; Prashant Pillai. Understanding the Cyber-Victimisation of People with Long Term Conditions and the Need for Collaborative Forensics-Enabled Disease Management Programmes. Cyberspace 2018, 227 -250.
AMA StyleZhraa A. Alhaboby, Doaa Alhaboby, Haider M. Al-Khateeb, Gregory Epiphaniou, Dhouha Kbaier Ben Ismail, Hamid Jahankhani, Prashant Pillai. Understanding the Cyber-Victimisation of People with Long Term Conditions and the Need for Collaborative Forensics-Enabled Disease Management Programmes. Cyberspace. 2018; ():227-250.
Chicago/Turabian StyleZhraa A. Alhaboby; Doaa Alhaboby; Haider M. Al-Khateeb; Gregory Epiphaniou; Dhouha Kbaier Ben Ismail; Hamid Jahankhani; Prashant Pillai. 2018. "Understanding the Cyber-Victimisation of People with Long Term Conditions and the Need for Collaborative Forensics-Enabled Disease Management Programmes." Cyberspace , no. : 227-250.
We present an algorithm that allows two users to establish a symmetric cryptographic key by incorporating the most important features of the wireless channel in vehicle-to-vehicle (V2V) communication. The proposed model includes surrounding scatterers’ mobility by considering other vehicles; it also includes three-dimensional (3D) multipath propagation. These temporal variability attributes are incorporated into the key generation process where non-reciprocity compensation is combined with turbo codes (TCs). For fair comparisons, the indexing technique is applied in conjunction with the non-reciprocity compensation technique. A series of simulations are run to calculate key performance indicators (KPIs). The entropy values were high throughout all rounds of simulation and estimated around 0.94 to 0.99 bits per sample. Furthermore, simulation results reveal a decrease in bit mismatch rate (BMR) and an increase key generation rate (KGR) when TCs are used. The estimated BMR is nearly the same for different key lengths, and it is estimated to only 0.02 with TCs, compared to 0.22 obtained with the indexing technique. Finally, the key generation rate was also reported high ranging from 35 to 39 for the 128-bit symmetric keys per minute with TCs, while it is ranging from 3 to 7 when compared with a sample indexing technique published in the public domain.
Dhouha Kbaier Ben Ismail; Petros Karadimas; Gregory Epiphaniou; Haider M. Al-Khateeb. Error Reconciliation with Turbo Codes for Secret Key Generation in Vehicular Ad Hoc Networks. Advances in Intelligent Systems and Computing 2018, 696 -704.
AMA StyleDhouha Kbaier Ben Ismail, Petros Karadimas, Gregory Epiphaniou, Haider M. Al-Khateeb. Error Reconciliation with Turbo Codes for Secret Key Generation in Vehicular Ad Hoc Networks. Advances in Intelligent Systems and Computing. 2018; ():696-704.
Chicago/Turabian StyleDhouha Kbaier Ben Ismail; Petros Karadimas; Gregory Epiphaniou; Haider M. Al-Khateeb. 2018. "Error Reconciliation with Turbo Codes for Secret Key Generation in Vehicular Ad Hoc Networks." Advances in Intelligent Systems and Computing , no. : 696-704.
The rise of interconnected “intelligent” objects that move their capabilities from sensing and data processing to decision making will be a disruptive phenomenon that further widens the gaps between legal, regulatory and technological approaches. This research sets out to establish a guided road map through the maze of regulation by incorporating the fragmented governance efforts into a single focus where security and privacy gaps unique to machine-to-machine communication (M2M) are identified against key performance metrics. We use privacy, ethics, trust, legality, data sharing, operational integration and device and communication protocols as our key performance metrics to highlight areas of significant overlap and gaps in a comprehensive list of standards to assist policymakers and researchers in the field. Results also indicate that policy concerns and diffused responses from existing standards raise unacceptable risks for the cyber and physical spheres in the IoT preventing their integration with existing hierarchical security architectures and reducing the opportunities for mass-market economies of scale.
Geraldine Lee; Gregory Epiphaniou; Haider Al-Khateeb; Carsten Maple. Security and Privacy of Things: Regulatory Challenges and Gaps for the Secure Integration of Cyber-Physical Systems. Advances in Intelligent Systems and Computing 2018, 1 -12.
AMA StyleGeraldine Lee, Gregory Epiphaniou, Haider Al-Khateeb, Carsten Maple. Security and Privacy of Things: Regulatory Challenges and Gaps for the Secure Integration of Cyber-Physical Systems. Advances in Intelligent Systems and Computing. 2018; ():1-12.
Chicago/Turabian StyleGeraldine Lee; Gregory Epiphaniou; Haider Al-Khateeb; Carsten Maple. 2018. "Security and Privacy of Things: Regulatory Challenges and Gaps for the Secure Integration of Cyber-Physical Systems." Advances in Intelligent Systems and Computing , no. : 1-12.
Physical layer security protocols have recently been deployed in the context of Wireless communications. These are derived from the intrinsic characteristics of the communication media for key generation, sharing and randomness extraction. These protocols always seek to exhibit both low computational complexity and energy efficiency, whilst also maintain unconditionally secure communications. We present herein, a comprehensive literature review of existing “state-of-the-art” quantisation schemes for physical layer security, with a strong emphasis upon key performance metrics and intrinsic channel characteristics. Our survey seeks not only to concentrate upon the most common quantisation methods, hence their efficiency during key generation; but also crucially, describes the inherent trade-offs as between these standardised metrics. The exact way(s) in which these metrics are duly influenced by quantisation schemes is also discussed, by means of a comprehensive critical narrative of both existing and future developments in the field.
Mirko Bottarelli; Gregory Epiphaniou; Dhouha Kbaier Ben Ismail; Petros Karadimas; Haider Al-Khateeb. Physical characteristics of wireless communication channels for secret key establishment: A survey of the research. Computers & Security 2018, 78, 454 -476.
AMA StyleMirko Bottarelli, Gregory Epiphaniou, Dhouha Kbaier Ben Ismail, Petros Karadimas, Haider Al-Khateeb. Physical characteristics of wireless communication channels for secret key establishment: A survey of the research. Computers & Security. 2018; 78 ():454-476.
Chicago/Turabian StyleMirko Bottarelli; Gregory Epiphaniou; Dhouha Kbaier Ben Ismail; Petros Karadimas; Haider Al-Khateeb. 2018. "Physical characteristics of wireless communication channels for secret key establishment: A survey of the research." Computers & Security 78, no. : 454-476.