All Outputs (76)

Explainable AI-Based DDOS Attack Identification Method for IoT Networks (2023)
Journal Article
Kalutharage, C. S., Liu, X., Chrysoulas, C., Pitropakis, N., & Papadopoulos, P. (2023). Explainable AI-Based DDOS Attack Identification Method for IoT Networks. Computers, 12(2), Article 32. https://doi.org/10.3390/computers12020032

The modern digitized world is mainly dependent on online services. The availability of online systems continues to be seriously challenged by distributed denial of service (DDoS) attacks. The challenge in mitigating attacks is not limited to identify... Read More about Explainable AI-Based DDOS Attack Identification Method for IoT Networks.

Towards The Creation Of The Future Fish Farm (2023)
Journal Article
Papadopoulos, P., Buchanan, W. J., Sayeed, S., & Pitropakis, N. (2023). Towards The Creation Of The Future Fish Farm. Journal of Surveillance, Security and Safety, 4, 1-3. https://doi.org/10.20517/jsss.2022.16

Aim: A fish farm is an area where fish raise and bred for food. Fish farm environments support the care and management of seafood within a controlled environment. Over the past few decades, there has been a remarkable increase in the calorie intake o... Read More about Towards The Creation Of The Future Fish Farm.

Post Quantum Cryptography Analysis of TLS Tunneling on a Constrained Device (2022)
Presentation / Conference Contribution
Barton, J., Pitropakis, N., Buchanan, W., Sayeed, S., & Abramson, W. (2022, February). Post Quantum Cryptography Analysis of TLS Tunneling on a Constrained Device. Presented at 8th International Conference on Information Systems Security and Privacy, Online

Advances in quantum computing make Shor’s algorithm for factorising numbers ever more tractable. This threatens the security of any cryptographic system which often relies on the difficulty of factorisation. It also threatens methods based on discret... Read More about Post Quantum Cryptography Analysis of TLS Tunneling on a Constrained Device.

Using Social Media & Sentiment Analysis to Make Investment Decisions (2022)
Journal Article
Hasselgren, B., Chrysoulas, C., Pitropakis, N., & Buchanan, W. J. (2023). Using Social Media & Sentiment Analysis to Make Investment Decisions. Future Internet, 15(1), Article 5. https://doi.org/10.3390/fi15010005

Making investment decisions by utilizing sentiment data from social media (SM) is starting to become a more tangible concept. There has been a broad investigation into this field of study over the last decade, and many of the findings have promising... Read More about Using Social Media & Sentiment Analysis to Make Investment Decisions.

Investigating Machine Learning Attacks on Financial Time Series Models (2022)
Journal Article
Gallagher, M., Pitropakis, N., Chrysoulas, C., Papadopoulos, P., Mylonas, A., & Katsikas, S. (2022). Investigating Machine Learning Attacks on Financial Time Series Models. Computers and Security, 123, https://doi.org/10.1016/j.cose.2022.102933

Machine learning and Artificial Intelligence (AI) already support human decision-making and complement professional roles, and are expected in the future to be sufficiently trusted to make autonomous decisions. To trust AI systems with such tasks, a... Read More about Investigating Machine Learning Attacks on Financial Time Series Models.

Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform (2022)
Journal Article
Ali, H., Ahmad, J., Jaroucheh, Z., Papadopoulos, P., Pitropakis, N., Lo, O., Abramson, W., & Buchanan, W. J. (2022). Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform. Entropy, 24(10), Article 1379. https://doi.org/10.3390/e24101379

Historically, threat information sharing has relied on manual modelling and centralised network systems, which can be inefficient, insecure, and prone to errors. Alternatively, private blockchains are now widely used to address these issues and impro... Read More about Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform.

DRaNN_PSO: A deep random neural network with particle swarm optimization for intrusion detection in the industrial internet of things (2022)
Journal Article
Ahmad, J., Shah, S. A., Latif, S., Ahmed, F., Zou, Z., & Pitropakis, N. (2022). DRaNN_PSO: A deep random neural network with particle swarm optimization for intrusion detection in the industrial internet of things. Journal of King Saud University (Computer and Information Sciences), 34(10), 8112-8121. https://doi.org/10.1016/j.jksuci.2022.07.023

The Industrial Internet of Things (IIoT) is a rapidly emerging technology that increases the efficiency and productivity of industrial environments by integrating smart sensors and devices with the internet. The advancements in communication technolo... Read More about DRaNN_PSO: A deep random neural network with particle swarm optimization for intrusion detection in the industrial internet of things.

A New Intrusion Detection System for the Internet of Things via Deep Convolutional Neural Network and Feature Engineering (2022)
Journal Article
Ullah, S., Ahmad, J., Khan, M. A., Alkhammash, E. H., Hadjouni, M., Ghadi, Y. Y., Saeed, F., & Pitropakis, N. (2022). A New Intrusion Detection System for the Internet of Things via Deep Convolutional Neural Network and Feature Engineering. Sensors, 22(10), Article 3607. https://doi.org/10.3390/s22103607

The Internet of Things (IoT) is a widely used technology in automated network systems across the world. The impact of the IoT on different industries has occurred in recent years. Many IoT nodes collect, store, and process personal data, which is an... Read More about A New Intrusion Detection System for the Internet of Things via Deep Convolutional Neural Network and Feature Engineering.

A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map (2022)
Journal Article
Alharbi, A. R., Ahmad, J., Arshad, Shaukat, S., Masood, F., Ghadi, Y. Y., Pitropakis, N., & Buchanan, W. J. (2022). A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map. Complexity, 2022, Article 7047282. https://doi.org/10.1155/2022/7047282

With the increasing volume of data transmission through insecure communication channels, big data security has become one of the important concerns in the cybersecurity domain. To address these concerns and keep data safe, a robust privacy-preserving... Read More about A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map.

A Smart and Robust Automatic Inspection of Printed Labels Using an Image Hashing Technique (2022)
Journal Article
Khan, M. A., Ahmed, F., Khan, M. D., Ahmad, J., Kumar, H., & Pitropakis, N. (2022). A Smart and Robust Automatic Inspection of Printed Labels Using an Image Hashing Technique. Electronics, 11(6), Article 955. https://doi.org/10.3390/electronics11060955

This work is focused on the development of a smart and automatic inspection system for printed labels. This is a challenging problem to solve since the collected labels are typically subjected to a variety of geometric and non-geometric distortions.... Read More about A Smart and Robust Automatic Inspection of Printed Labels Using an Image Hashing Technique.

GLASS: A Citizen-Centric Distributed Data-Sharing Model within an e-Governance Architecture (2022)
Journal Article
Lo, O., Buchanan, W., Sayeed, S., Papadopoulos, P., Pitropakis, N., & Chrysoulas, C. (2022). GLASS: A Citizen-Centric Distributed Data-Sharing Model within an e-Governance Architecture. Sensors, 22(6), Article 2291. https://doi.org/10.3390/s22062291

E-governance is a process that aims to enhance a government’s ability to simplify all the processes that may involve government, citizens, businesses, and so on. The rapid evolution of digital technologies has often created the necessity for the esta... Read More about GLASS: A Citizen-Centric Distributed Data-Sharing Model within an e-Governance Architecture.

Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers (2022)
Presentation / Conference Contribution
Ali, H., Papadopoulos, P., Ahmad, J., Pit, N., Jaroucheh, Z., & Buchanan, W. J. (2021, December). Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers. Presented at IEEE SINCONF: 14th International Conference on Security of Information and Networks, Edinburgh

Threat information sharing is considered as one of the proactive defensive approaches for enhancing the overall security of trusted partners. Trusted partner organizations can provide access to past and current cybersecurity threats for reducing the... Read More about Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers.

PAN-DOMAIN: Privacy-preserving Sharing and Auditing of Infection Identifier Matching (2022)
Presentation / Conference Contribution
Abramson, W., Buchanan, W. J., Sayeed, S., Pitropakis, N., & Lo, O. (2021, December). PAN-DOMAIN: Privacy-preserving Sharing and Auditing of Infection Identifier Matching. Presented at 14th International Conference on Security of Information and Networks, Edinburgh [Online]

The spread of COVID-19 has highlighted the need for a robust contact tracing infrastructure that enables infected individuals to have their contacts traced, and followed up with a test. The key entities involved within a contact tracing infrastructur... Read More about PAN-DOMAIN: Privacy-preserving Sharing and Auditing of Infection Identifier Matching.

HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles (2022)
Journal Article
Ullah, S., Khan, M. A., Ahmad, J., Jamal, S. S., e Huma, Z., Hassan, M. T., Pitropakis, N., Arshad, & Buchanan, W. J. (2022). HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles. Sensors, 22(4), Article 1340. https://doi.org/10.3390/s22041340

Internet of Vehicles (IoV) is an application of the Internet of Things (IoT) network that connects smart vehicles to the internet, and vehicles with each other. With the emergence of IoV technology, customers have placed great attention on smart vehi... Read More about HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles.

GLASS: Towards Secure and Decentralized eGovernance Services using IPFS (2022)
Presentation / Conference Contribution
Chrysoulas, C., Thomson, A., Pitropakis, N., Papadopoulos, P., Lo, O., Buchanan, W. J., Domalis, G., Karacapilidis, N., Tsakalidis, D., & Tsolis, D. (2021, October). GLASS: Towards Secure and Decentralized eGovernance Services using IPFS. Presented at 7th Workshop On The Security Of Industrial Control Systems & Of Cyber-Physical Systems (CyberICPS 2021). In Conjunction With ESORICS 2021, Darmstadt, Germany

The continuously advancing digitization has provided answers to the bureaucratic problems faced by eGovernance services. This innovation led them to an era of automation, broadened the attack surface and made them a popular target for cyber attacks.... Read More about GLASS: Towards Secure and Decentralized eGovernance Services using IPFS.

Ransomware: Analysing the Impact on Windows Active Directory Domain Services (2022)
Journal Article
McDonald, G., Papadopoulos, P., Pitropakis, N., Ahmad, J., & Buchanan, W. J. (2022). Ransomware: Analysing the Impact on Windows Active Directory Domain Services. Sensors, 22(3), Article 953. https://doi.org/10.3390/s22030953

Ransomware has become an increasingly popular type of malware across the past decade and continues to rise in popularity due to its high profitability. Organisations and enterprises have become prime targets for ransomware as they are more likely to... Read More about Ransomware: Analysing the Impact on Windows Active Directory Domain Services.

Decentralised Privacy: A Distributed Ledger Approach (2021)
Book Chapter
Papadopoulos, P., Pitropakis, N., & Buchanan, W. J. (2021). Decentralised Privacy: A Distributed Ledger Approach. In C. Mustansar Hussain, & P. Di Sia (Eds.), Handbook of Smart Materials, Technologies, and Devices (1-26). Springer. https://doi.org/10.1007/978-3-030-58675-1_58-1

Our world due to the technological progress became fast-paced and is constantly evolving, thus changing every single day. Consequently, the most valuable asset on earth is not gold or oil anymore but data. Big data companies try to take advantage of... Read More about Decentralised Privacy: A Distributed Ledger Approach.

Browsers’ Private Mode: Is It What We Were Promised? (2021)
Journal Article
Hughes, K., Papadopoulos, P., Pitropakis, N., Smales, A., Ahmad, J., & Buchanan, W. J. (2021). Browsers’ Private Mode: Is It What We Were Promised?. Computers, 10(12), Article 165. https://doi.org/10.3390/computers10120165

Web browsers are one of the most used applications on every computational device in our days. Hence, they play a pivotal role in any forensic investigation and help determine if nefarious or suspicious activity has occurred on that device. Our study... Read More about Browsers’ Private Mode: Is It What We Were Promised?.

A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT (2021)
Journal Article
Almas Khan, M., Khan, M. A., Ullah Jan, S., Ahmad, J., Jamal, S. S., Shah, A. A., Pitropakis, N., Buchanan, W. J., Alonistioti, N., Panagiotakis, S., & Markakis, E. K. (2021). A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT. Sensors, 21(21), Article 7016. https://doi.org/10.3390/s21217016

A large number of smart devices in Internet of Things (IoT) environments communicate via different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely used publish–subscribe-based protocol for the communication of sensor or ev... Read More about A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT.

Launching Adversarial Label Contamination Attacks Against Malicious URL Detection (2021)
Presentation / Conference Contribution
Marchand, B., Pitropakis, N., Buchanan, W. J., & Lambrinoudakis, C. (2021, September). Launching Adversarial Label Contamination Attacks Against Malicious URL Detection. Presented at TrustBus 2021: Trust, Privacy and Security in Digital Business, Online

Web addresses, or Uniform Resource Locators (URLs), represent a vector by which attackers are able to deliver a multitude of unwanted and potentially harmful effects to users through malicious software. The ability to detect and block access to such... Read More about Launching Adversarial Label Contamination Attacks Against Malicious URL Detection.