Privacy-preserving Surveillance Methods using Homomorphic Encryption (2020)
Presentation / Conference Contribution
Bowditch, W., Abramson, W., Buchanan, W. J., Pitropakis, N., & Hall, A. J. (2020, February). Privacy-preserving Surveillance Methods using Homomorphic Encryption. Presented at 6th International Conference on Information Security Systems and Privacy (ICISSP), Valletta, Malta

Data analysis and machine learning methods often involve the processing of cleartext data, and where this could breach the rights to privacy. Increasingly, we must use encryption to protect all states of the data: in-transit, at-rest, and in-memory.... Read More about Privacy-preserving Surveillance Methods using Homomorphic Encryption.

Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach (2020)
Presentation / Conference Contribution
Christou, O., Pitropakis, N., Papadopoulos, P., Mckeown, S., & Buchanan, W. J. (2020, February). Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach. Presented at ICISSP 2020, Valletta, Malta

Phishing is considered to be one of the most prevalent cyber-attacks because of its immense flexibility and alarmingly high success rate. Even with adequate training and high situational awareness, it can still be hard for users to continually be awa... Read More about Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach.

Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection (2020)
Journal Article
Tian, Z., Shi, W., Tan, Z., Qiu, J., Sun, Y., Jiang, F., & Liu, Y. (online). Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection. Mobile Networks and Applications, https://doi.org/10.1007/s11036-020-01656-7

Organizations' own personnel now have a greater ability than ever before to misuse their access to critical organizational assets. Insider threat detection is a key component in identifying rare anomalies in context, which is a growing concern for ma... Read More about Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection.

Props Alive: A Framework for Augmented Reality Stop Motion Animation (2020)
Presentation / Conference Contribution
Casas, L., Kosek, M., & Mitchell, K. (2017, March). Props Alive: A Framework for Augmented Reality Stop Motion Animation. Presented at 2017 IEEE 10th Workshop on Software Engineering and Architectures for Realtime Interactive Systems (SEARIS), Los Angeles, CA, USA

Stop motion animation evolved in the early days of cinema with the aim to create an illusion of movement with static puppets posed manually each frame. Current stop motion movies introduced 3D printing processes in order to acquire animations more ac... Read More about Props Alive: A Framework for Augmented Reality Stop Motion Animation.

Exploring coupled images fusion based on joint tensor decomposition (2020)
Journal Article
Lu, L., Ren, X., Yeh, K.-H., 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.

Trust-aware and Cooperative Routing Protocol for IoT Security (2020)
Journal Article
Djedjig, N., Tandjaoui, D., Medjek, F., & Romdhani, I. (2020). Trust-aware and Cooperative Routing Protocol for IoT Security. Journal of Information Security and Applications, 52, Article 102467. https://doi.org/10.1016/j.jisa.2020.102467

The resource-constrained nature of IoT objects makes the Routing Protocol for Low-power and Lossy Networks (RPL) vulnerable to several attacks. Although RPL specification provides encryption protection to control messages, RPL is still vulnerable to... Read More about Trust-aware and Cooperative Routing Protocol for IoT Security.

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.

BCFR: Blockchain-based Controller Against False Flow Rule Injection in SDN (2020)
Presentation / Conference Contribution
Boukria, S., Guerroumi, M., & Romdhani, I. (2019, June). BCFR: Blockchain-based Controller Against False Flow Rule Injection in SDN. Presented at 11th IEEE International Workshop on Performance Evaluation of Communications in Distributed Systems and Web based Service Architectures, PEDISWESA'2019, Barcelona, Spain

Software Defined Networking (SDN) technology increases the evolution of Internet and network development. SDN, with its logical centralization of controllers and global network overview changes the network's characteristics, on term of flexibility, a... Read More about BCFR: Blockchain-based Controller Against False Flow Rule Injection in SDN.

Using MAP-Elites to support policy making around Workforce Scheduling and Routing (2020)
Journal Article
Urquhart, N., Hart, E., & Hutcheson, W. (2020). Using MAP-Elites to support policy making around Workforce Scheduling and Routing. Automatisierungstechnik, 68(2), https://doi.org/10.1515/auto-2019-0107

English abstract: Algorithms such as MAP-Elites provide a means of allowing users to explore a solution space by returning an archive of high-performing solutions. Such an archive, can allow the user an overview of the solution space which may be use... Read More about Using MAP-Elites to support policy making around Workforce Scheduling and Routing.

An authentication protocol based on chaos and zero knowledge proof (2020)
Journal Article
Major, W., Buchanan, W. J., & Ahmad, J. (2020). An authentication protocol based on chaos and zero knowledge proof. Nonlinear Dynamics, 99, 3065-3087. https://doi.org/10.1007/s11071-020-05463-3

Port Knocking is a method for authenticating clients through a closed stance firewall, and authorising their requested actions, enabling severs to offer services to authenticated clients, without opening ports on the firewall. Advances in port knocki... Read More about An authentication protocol based on chaos and zero knowledge proof.

Fast Forensic Triage Using Centralised Thumbnail Caches on Windows Operating Systems (2020)
Journal Article
Mckeown, S., Russell, G., & Leimich, P. (2020). Fast Forensic Triage Using Centralised Thumbnail Caches on Windows Operating Systems. Journal of Digital Forensics, Security and Law, 14(3), Article 1

A common investigative task is to identify known contraband images on a device, which typically involves calculating cryptographic hashes for all the files on a disk and checking these against a database of known contraband. However, modern drives ar... Read More about Fast Forensic Triage Using Centralised Thumbnail Caches on Windows Operating Systems.

Double-Arc Parallel Coordinates and its Axes re-Ordering Methods (2020)
Journal Article
Lu, L., Wang, W., & Tan, Z. (2020). Double-Arc Parallel Coordinates and its Axes re-Ordering Methods. Mobile Networks and Applications, 25(4), 1376-1391. https://doi.org/10.1007/s11036-019-01455-9

The Parallel Coordinates Plot (PCP) is a popular technique for the exploration of high-dimensional data. In many cases, researchers apply it as an effective method to analyze and mine data. However, when today's data volume is getting larger, visual... Read More about Double-Arc Parallel Coordinates and its Axes re-Ordering Methods.

Photo-Realistic Facial Details Synthesis from Single Image (2019)
Presentation / Conference Contribution
Chen, A., Chen, Z., Zhang, G., Zhang, Z., Mitchell, K., & Yu, J. (2019, October). Photo-Realistic Facial Details Synthesis from Single Image. Presented at 2019 IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, Korea

We present a single-image 3D face synthesis technique that can handle challenging facial expressions while recovering fine geometric details. Our technique employs expression analysis for proxy face geometry generation and combines supervised and uns... Read More about Photo-Realistic Facial Details Synthesis from Single Image.

A Review on Deep Learning Approaches to Image Classification and Object Segmentation (2019)
Journal Article
Wu, H., Liu, Q., & Liu, X. (2019). A Review on Deep Learning Approaches to Image Classification and Object Segmentation. Computers, Materials & Continua, 60(2), 575-597. https://doi.org/10.32604/cmc.2019.03595

Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Present proposed artificial neural networks and optimization skills have effe... Read More about A Review on Deep Learning Approaches to Image Classification and Object Segmentation.

PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing (2019)
Journal Article
Zhu, R., Yu, T., Tan, Z., Du, W., Zhao, L., Li, J., & Xia, X. (2020). PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing. IEEE Access, 8, 1475-1485. https://doi.org/10.1109/ACCESS.2019.2962066

Outlier detection over sliding window is a fundamental problem in the domain of streaming data management, which has been studied over 10 years. The key of supporting outlier detection is to construct a neighbour-list for each object. It is used for... Read More about PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing.

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, December). A Multi-attributes-based Trust Model of Internet of Vehicle. Presented at 13th International Conference on Network and System Security, Sapporo, Japan

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.

Fuzzy-Based Distributed Protocol for Vehicle-to-Vehicle Communication (2019)
Journal Article
Hawbani, A., Torbosh, E., Wang, X., Sincak, P., Zhao, L., & Al-Dubai, A. (2021). Fuzzy-Based Distributed Protocol for Vehicle-to-Vehicle Communication. IEEE Transactions on Fuzzy Systems, 29(3), 612-626. https://doi.org/10.1109/tfuzz.2019.2957254

This paper modeled the multihop data-routing in Vehicular Ad-hoc Networks(VANET) as Multiple Criteria Decision Making (MCDM) in four steps. First, the criteria which have an impact on the performance of the network layer are captured and transformed... Read More about Fuzzy-Based Distributed Protocol for Vehicle-to-Vehicle Communication.

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.

MRC4: A Modified RC4 Algorithm using Symmetric Random Function Generator for Improved Cryptographic Features (2019)
Journal Article
Saha, R., Geetha, G., Kumar, G., Kim, T.-H., & Buchanan, W. J. (2019). MRC4: A Modified RC4 Algorithm using Symmetric Random Function Generator for Improved Cryptographic Features. IEEE Access, 7, 172045-172054. https://doi.org/10.1109/access.2019.2956160

The Rivest Cipher 4 (RC4) has been one of the most popular stream ciphers for providing symmetric key encryption, and is now proposed as an efficient cipher within light-weight cryptography. As an algorithm it has been considered to be one of the fas... Read More about MRC4: A Modified RC4 Algorithm using Symmetric Random Function Generator for Improved Cryptographic Features.

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.