Outputs (682)

Machine Learning for Health and Social Care Demographics in Scotland (2019)
Presentation / Conference Contribution
Buchanan, W. J., Smales, A., Lawson, A., & Chute, C. (2019, November). Machine Learning for Health and Social Care Demographics in Scotland. Paper presented at HEALTHINFO 2019, Valencia, Spain

This paper outlines an extensive study of applying machine learning to the analysis of publicly available health and social care data within Scotland, with a focus on learning the most significant variables involved in key health care outcome factors... Read More about Machine Learning for Health and Social Care Demographics in Scotland.

On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining (2020)
Journal Article
Cha, S., Wang, H., Tan, Z., Joung, Y., Tseng, Y., & Yeh, K. (2020). On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining. IEEE Transactions on Emerging Topics in Computational Intelligence, 4(5), 641-652. https://doi.org/10.1109/tetci.2019.2938547

Intelligence mining is one of the most promising technologies for effectively extracting intelligence (and knowledge) to enhance the quality of decision-making. In Taiwan, the government curtails underground economic activities and facilitates tax ma... Read More about On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining.

Novel Fuzzy and Game Theory Based Clustering and Decision Making for VANETs (2019)
Journal Article
Alsarhan, A., Kilani, Y., Al-Dubai, A., Zomaya, A. Y., & Hussain, A. (2020). Novel Fuzzy and Game Theory Based Clustering and Decision Making for VANETs. IEEE Transactions on Vehicular Technology, 69(2), 1568-1581. https://doi.org/10.1109/TVT.2019.2956228

Different studies have recently emphasized the importance of deploying clustering schemes in Vehicular ad hoc Network (VANET) to overcome challenging problems related to scalability, frequent topology changes, scarcity of spectrum resources, maintain... Read More about Novel Fuzzy and Game Theory Based Clustering and Decision Making for VANETs.

A Multi-attributes-based Trust Model of Internet of Vehicle (2019)
Presentation / Conference Contribution
Ou, W., Luo, E., Tan, Z., Xiang, L., Yi, Q., & Tian, C. (2019). A Multi-attributes-based Trust Model of Internet of Vehicle. In Network and System Security (706-713). https://doi.org/10.1007/978-3-030-36938-5_45

Internet of Vehicle (IoV) is an open network and it changes in constant, where there are large number of entities. Effective way to keep security of data in IoV is to establish a trustworthy mechanism. Through transmission and dissemination of trust,... Read More about A Multi-attributes-based Trust Model of Internet of Vehicle.

Employing a Machine Learning Approach to Detect Combined Internet of Things Attacks Against Two Objective Functions Using a Novel Dataset (2020)
Journal Article
Foley, J., Moradpoor, N., & Ochen, H. (2020). Employing a Machine Learning Approach to Detect Combined Internet of Things Attacks Against Two Objective Functions Using a Novel Dataset. Security and Communication Networks, 2020, Article 2804291. https://doi.org/10.1155/2020/2804291

One of the important features of Routing Protocol for Low-Power and Lossy Networks (RPL) is Objective Function (OF). OF influences an IoT network in terms of routing strategies and network topology. On the other hand, detecting a combination of attac... Read More about Employing a Machine Learning Approach to Detect Combined Internet of Things Attacks Against Two Objective Functions Using a Novel Dataset.

KNN-Based Approximate Outlier Detection Algorithm Over IoT Streaming Data (2020)
Journal Article
Zhu, R., Ji, X., Yu, D., Tan, Z., Zhao, L., Li, J., & Xia, X. (2020). KNN-Based Approximate Outlier Detection Algorithm Over IoT Streaming Data. IEEE Access, 8, 42749-42759. https://doi.org/10.1109/access.2020.2977114

KNN-Based outlier detection over IoT streaming data is a fundamental problem, which has many applications. However, due to its computational complexity, existing efforts cannot efficiently work in the IoT streaming data. In this paper, we propose a n... Read More about KNN-Based Approximate Outlier Detection Algorithm Over IoT Streaming Data.

Forensic Considerations for the High Efficiency Image File Format (HEIF) (2020)
Presentation / Conference Contribution
Mckeown, S., & Russell, G. (2020). Forensic Considerations for the High Efficiency Image File Format (HEIF). . https://doi.org/10.1109/CyberSecurity49315.2020.9138890

The High Efficiency File Format (HEIF) was adopted by Apple in 2017 as their favoured means of capturing images from their camera application, with Android devices such as the Galaxy S10 providing support more recently. The format is positioned to re... Read More about Forensic Considerations for the High Efficiency Image File Format (HEIF).

Mitigation Mechanisms Against the DAO Attack on the Routing Protocol for Low Power and Lossy Networks (RPL) (2020)
Journal Article
Wadhaj, I., Ghaleb, B., Thomson, C., Al-Dubai, A., & Buchanen, B. (2020). Mitigation Mechanisms Against the DAO Attack on the Routing Protocol for Low Power and Lossy Networks (RPL). IEEE Access, 8, 43665-43675. https://doi.org/10.1109/ACCESS.2020.2977476

Destination Advertisement Objects (DAOs) are sent upward by RPL nodes toward the DODAG root, to build the downward routing paths carrying traffic from the root to its associated nodes. This routing mechanism can be exploited by a malicious node perio... Read More about Mitigation Mechanisms Against the DAO Attack on the Routing Protocol for Low Power and Lossy Networks (RPL).

The Importance of Authenticity in Cyber Security Training and Education (2019)
Presentation / Conference Contribution
Macfarlane, R., & Mata de Acuna, J. (2019, November). The Importance of Authenticity in Cyber Security Training and Education. Presented at JISC Security Conference, Newcastle, England

The knowledge gap between academy and industry is a challenging issue that educators face every day. In the field of cyber security, it is important that students understand the need of adapting and acquiring new skills that allow them to put their t... Read More about The Importance of Authenticity in Cyber Security Training and Education.

Blockchain for Cybersecurity and Privacy: Architectures, Challenges, and Applications (2020)
Book
Maleh, Y., Shojaafar, M., Alazab, M., & Romdhani, I. (Eds.). (2020). Blockchain for Cybersecurity and Privacy: Architectures, Challenges, and Applications. CRC Press

Blockchain Technology is defined as a decentralized system of distributed registers that are used to record data transactions on multiple computers. The reason this technology has gained popularity is that you can put any digital asset or transaction... Read More about Blockchain for Cybersecurity and Privacy: Architectures, Challenges, and Applications.

Wi-Fi Channel Saturation as a Mechanism to Improve Passive Capture of Bluetooth Through Channel Usage Restriction (2019)
Journal Article
Lowe, I., Buchanan, W. J., Macfarlane, R., & Lo, O. (2019). Wi-Fi Channel Saturation as a Mechanism to Improve Passive Capture of Bluetooth Through Channel Usage Restriction. Journal of Networking Technology, 10(4), 124-155. https://doi.org/10.6025/jnt/2019/10/4/124-155

Bluetooth is a short-range wireless technology that provides audio and data links between personal smartphones and playback devices, such as speakers, headsets and car entertainment systems. Since its introduction in 2001, security researchers have s... Read More about Wi-Fi Channel Saturation as a Mechanism to Improve Passive Capture of Bluetooth Through Channel Usage Restriction.

Exploring coupled images fusion based on joint tensor decomposition (2020)
Journal Article
Lu, L., Ren, X., Yeh, K., Tan, Z., & Chanussot, J. (2020). Exploring coupled images fusion based on joint tensor decomposition. Human-Centric Computing and Information Sciences, 10, Article 10 (2020). https://doi.org/10.1186/s13673-020-00215-z

Data fusion has always been a hot research topic in human-centric computing and extended with the development of artificial intelligence. Generally, the coupled data fusion algorithm usually utilizes the information from one data set to improve the e... Read More about Exploring coupled images fusion based on joint tensor decomposition.

Using Amazon Alexa APIs as a Source of Digital Evidence (2020)
Presentation / Conference Contribution
Krueger, C., & Mckeown, S. (2020). Using Amazon Alexa APIs as a Source of Digital Evidence. . https://doi.org/10.1109/CyberSecurity49315.2020.9138849

With the release of Amazon Alexa and the first Amazon Echo device, the company revolutionised the smart home. It allowed their users to communicate with, and control, their smart home ecosystem purely using voice commands. However, this also means th... Read More about Using Amazon Alexa APIs as a Source of Digital Evidence.

Fast Probabilistic Consensus with Weighted Votes (2020)
Presentation / Conference Contribution
Müller, S., Penzkofer, A., Ku´smierz, B., Camargo, D., & Buchanan, W. J. (2020, November). Fast Probabilistic Consensus with Weighted Votes. Presented at FTC 2020 - Future Technologies Conference 2020, Vancouver, Canada

The fast probabilistic consensus (FPC) is a voting consensus protocol that is robust and efficient in Byzantine infrastructure. We propose an adaption of the FPC to a setting where the voting power is proportional to the nodes reputations. We model t... Read More about Fast Probabilistic Consensus with Weighted Votes.

A Privacy Preserving Distributed Ledger Framework for Global Human Resource Record Management: The Blockchain Aspect (2020)
Journal Article
Kim, T., Kumar, G., Saha, R., Rai, M. K., Buchanan, W. J., Thomas, R., & Alazab, M. (2020). A Privacy Preserving Distributed Ledger Framework for Global Human Resource Record Management: The Blockchain Aspect. IEEE Access, 8, 96455-96467. https://doi.org/10.1109/access.2020.2995481

Blockchain is a technology used with the series of users in peer-to-peer transactions to utilize the usability properties of the immutable data records. The distributed nature of this technology has given the wide acceptance to its range of applicati... Read More about A Privacy Preserving Distributed Ledger Framework for Global Human Resource Record Management: The Blockchain Aspect.

A Novel Privacy Approach of Digital Aerial Images Based on Mersenne Twister Method with DNA Genetic Encoding and Chaos (2020)
Journal Article
Masood, F., Boulila, W., Ahmad, J., Arshad, A., Sankar, S., Rubaiee, S., & Buchanan, W. J. (2020). A Novel Privacy Approach of Digital Aerial Images Based on Mersenne Twister Method with DNA Genetic Encoding and Chaos. Remote Sensing, 12(11), Article 1893. https://doi.org/10.3390/rs12111893

Aerial photography involves capturing images from aircraft and other flying objects, including Unmanned Aerial Vehicles (UAV). Aerial images are used in many fields and can contain sensitive information that requires secure processing. We proposed an... Read More about A Novel Privacy Approach of Digital Aerial Images Based on Mersenne Twister Method with DNA Genetic Encoding and Chaos.

Trust-by-Design: Evaluating Issues and Perceptions within Clinical Passporting (2020)
Journal Article
Abramson, W., van Deursen, N. E., & Buchanan, W. J. (2020). Trust-by-Design: Evaluating Issues and Perceptions within Clinical Passporting. Blockchain in Healthcare Today, 3, https://doi.org/10.30953/bhty.v3.140

A substantial administrative burden is placed on healthcare professionals as they manage and progress through their careers. Identity verification, pre-employment screening and appraisals: the bureaucracy associated with each of these processes takes... Read More about Trust-by-Design: Evaluating Issues and Perceptions within Clinical Passporting.

BeepTrace: Blockchain-enabled Privacy-preserving Contact Tracing for COVID-19 Pandemic and Beyond (2020)
Journal Article
Xu, H., Zhang, L., Onireti, O., Fang, Y., Buchanan, W. J., & Imran, M. A. (2021). BeepTrace: Blockchain-enabled Privacy-preserving Contact Tracing for COVID-19 Pandemic and Beyond. IEEE Internet of Things, 8(5), 3915-3929. https://doi.org/10.1109/jiot.2020.3025953

The outbreak of COVID-19 pandemic has exposed an urgent need for effective contact tracing solutions through mobile phone applications to prevent the infection from spreading further. However, due to the nature of contact tracing, public concern on p... Read More about BeepTrace: Blockchain-enabled Privacy-preserving Contact Tracing for COVID-19 Pandemic and Beyond.

Toward Machine Intelligence that Learns to Fingerprint Polymorphic Worms in IoT (2022)
Journal Article
Wang, F., Yang, S., Wang, C., Li, Q., Babaagba, K., & Tan, Z. (2022). Toward Machine Intelligence that Learns to Fingerprint Polymorphic Worms in IoT. International Journal of Intelligent Systems, 37(10), 7058-7078. https://doi.org/10.1002/int.22871

Internet of Things (IoT) is fast growing. Non-PC devices under the umbrella of IoT have been increasingly applied in various fields and will soon account for a significant share of total Internet traffic. However, the security and privacy of IoT and... Read More about Toward Machine Intelligence that Learns to Fingerprint Polymorphic Worms in IoT.

Privacy-Preserving Passive DNS (2020)
Journal Article
Papadopoulos, P., Pitropakis, N., Buchanan, W. J., Lo, O., & Katsikas, S. (2020). Privacy-Preserving Passive DNS. Computers, 9(3), Article 64. https://doi.org/10.3390/computers9030064

The Domain Name System (DNS) was created to resolve the IP addresses of web servers to easily remembered names. When it was initially created, security was not a major concern; nowadays, this lack of inherent security and trust has exposed the global... Read More about Privacy-Preserving Passive DNS.