All Outputs (29)

SRSS: A New Chaos-Based Single-Round Single S-Box Image Encryption Scheme for Highly Auto-Correlated Data (2023)
Presentation / Conference Contribution
Shahbaz Khan, M., Ahmad, J., Ali, H., Pitropakis, N., Al-Dubai, A., Ghaleb, B., & Buchanan, W. J. (2023, October). SRSS: A New Chaos-Based Single-Round Single S-Box Image Encryption Scheme for Highly Auto-Correlated Data. Presented at 9th International Co

With the advent of digital communication, securing digital images during transmission and storage has become a critical concern. The traditional s-box substitution methods often fail to effectively conceal the information within highly auto-correlate... Read More about SRSS: A New Chaos-Based Single-Round Single S-Box Image Encryption Scheme for Highly Auto-Correlated Data.

CellSecure: Securing Image Data in Industrial Internet-of-Things via Cellular Automata and Chaos-Based Encryption (2023)
Presentation / Conference Contribution
Ali, H., Khan, M. S., Driss, M., Ahmad, J., Buchanan, W. J., & Pitropakis, N. (2023, October). CellSecure: Securing Image Data in Industrial Internet-of-Things via Cellular Automata and Chaos-Based Encryption. Presented at 2023 IEEE 98th Vehicular Technol

In the era of Industrial IoT (IIoT) and Industry 4.0, ensuring secure data transmission has become a critical concern. Among other data types, images are widely transmitted and utilized across various IIoT applications, ranging from sensor-generated... Read More about CellSecure: Securing Image Data in Industrial Internet-of-Things via Cellular Automata and Chaos-Based Encryption.

TRUSTEE: Towards the creation of secure, trustworthy and privacy-preserving framework (2023)
Presentation / Conference Contribution
Sayeed, S., Pitropakis, N., Buchanan, W. J., Markakis, E., Papatsaroucha, D., & Politis, I. (2023). TRUSTEE: Towards the creation of secure, trustworthy and privacy-preserving framework. In ARES '23: Proceedings of the 18th International Conference on Av

Digital transformation is a method where new technologies replace the old to meet essential organisational requirements and enhance the end-user experience. Technological transformation often improvises the manner in which a facility or resources are... Read More about TRUSTEE: Towards the creation of secure, trustworthy and privacy-preserving framework.

Progressive Web Apps to Support (Critical) Systems in Low or No Connectivity Areas (2023)
Presentation / Conference Contribution
Josephe, A. O., Chrysoulas, C., Peng, T., El Boudani, B., Iatropoulos, I., & Pitropakis, N. (2023). Progressive Web Apps to Support (Critical) Systems in Low or No Connectivity Areas. In 2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET

Web applications are popular in our world today and every organization or individual either build or access at least one each day. It’s important for every application user to continue accessing contents of a web application irrespective of the netwo... Read More about Progressive Web Apps to Support (Critical) Systems in Low or No Connectivity Areas.

Forensic Investigation Using RAM Analysis on the Hadoop Distributed File System (2023)
Presentation / Conference Contribution
Laing, S., Ludwiniak, R., El Boudani, . B., Chrysoulas, C., Ubakanma, G., & Pitropakis, N. (2023). Forensic Investigation Using RAM Analysis on the Hadoop Distributed File System. In 2023 19th International Conference on the Design of Reliable Communicat

The usage of cloud systems is at an all-time high, and with more organizations reaching for Big Data the forensic implications must be analyzed. The Hadoop Distributed File System is widely used both as a cloud service and with organizations implemen... Read More about Forensic Investigation Using RAM Analysis on the Hadoop Distributed File System.

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). Post Quantum Cryptography Analysis of TLS Tunneling on a Constrained Device. In Proceedings of the 8th International Conference on Information Systems Security and Privacy - ICI

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.

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

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,

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.

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

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.

Evaluating Tooling and Methodology when Analysing Bitcoin Mixing Services After Forensic Seizure (2021)
Presentation / Conference Contribution
Young, E. H., Chrysoulas, C., Pitropakis, N., Papadopoulos, P., & Buchanan, W. J. (2021, October). Evaluating Tooling and Methodology when Analysing Bitcoin Mixing Services After Forensic Seizure. Paper presented at International Conference on Data Analyt

Little or no research has been directed to analysis and researching forensic analysis of the Bitcoin mixing or 'tumbling' service themselves. This work is intended to examine effective tooling and methodology for recovering forensic artifacts from tw... Read More about Evaluating Tooling and Methodology when Analysing Bitcoin Mixing Services After Forensic Seizure.

Launching Adversarial Label Contamination Attacks Against Malicious URL Detection (2021)
Presentation / Conference Contribution
Marchand, B., Pitropakis, N., Buchanan, W. J., & Lambrinoudakis, C. (2021). Launching Adversarial Label Contamination Attacks Against Malicious URL Detection. In Trust, Privacy and Security in Digital Business: 18th International Conference, TrustBus 20

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.

SANCUS–Towards Unifying the Analysis and Control of Security, Privacy and Service Reliability (2021)
Presentation / Conference Contribution
Zarakovitis, C., Pitropakis, N., Klonidis, D., & Khalife, H. (2021, June). SANCUS–Towards Unifying the Analysis and Control of Security, Privacy and Service Reliability. Poster presented at EuCNC & 6G Summit, Grenoble, France

The arrival of new technologies change the global digital landscape in many ways. In the past years, for example, network virtualization and cloud computing have given raise to organizations for meeting their everyday needs in an elastic manner witho... Read More about SANCUS–Towards Unifying the Analysis and Control of Security, Privacy and Service Reliability.

Towards An SDN Assisted IDS (2021)
Presentation / Conference Contribution
Sutton, R., Ludwiniak, R., Pitropakis, N., Chrysoulas, C., & Dagiuklas, T. (2021). Towards An SDN Assisted IDS. In 2021 11th IFIP International Conference on New Technologies, Mobility and Security (NTMS). https://doi.org/10.1109/NTMS49979.2021.9432651

Modern Intrusion Detection Systems are able to identify and check all traffic crossing the network segments that they are only set to monitor. Traditional network infrastructures use static detection mechanisms that check and monitor specific types o... Read More about Towards An SDN Assisted IDS.

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 (ICISS

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.

Microtargeting or Microphishing? Phishing Unveiled (2020)
Presentation / Conference Contribution
Khursheed, B., Pitropakis, N., McKeown, S., & Lambrinoudakis, C. (2020). Microtargeting or Microphishing? Phishing Unveiled. In Trust, Privacy and Security in Digital Business (89-105). https://doi.org/10.1007/978-3-030-58986-8_7

Online advertisements delivered via social media platforms function in a similar way to phishing emails. In recent years there has been a growing awareness that political advertisements are being microtargeted and tailored to specific demographics, w... Read More about Microtargeting or Microphishing? Phishing Unveiled.

A Distributed Trust Framework for Privacy-Preserving Machine Learning (2020)
Presentation / Conference Contribution
Abramson, W., Hall, A. J., Papadopoulos, P., Pitropakis, N., & Buchanan, W. J. (2020, September). A Distributed Trust Framework for Privacy-Preserving Machine Learning. Presented at The 17th International Conference on Trust, Privacy and Security in Digit

When training a machine learning model, it is standard procedure for the researcher to have full knowledge of both the data and model. However, this engenders a lack of trust between data owners and data scientists. Data owners are justifiably reluct... Read More about A Distributed Trust Framework for Privacy-Preserving Machine Learning.

Testing And Hardening IoT Devices Against the Mirai Botnet (2020)
Presentation / Conference Contribution
Kelly, C., Pitropakis, N., McKeown, S., & Lambrinoudakis, C. (2020, June). Testing And Hardening IoT Devices Against the Mirai Botnet. Presented at IEEE International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2020), D

A large majority of cheap Internet of Things (IoT) devices that arrive brand new, and are configured with out-of-the-box settings, are not being properly secured by the manufactures, and are vulnerable to existing malware lurking on the Internet. Amo... Read More about Testing And Hardening IoT Devices Against the Mirai Botnet.

Towards The Creation of A Threat Intelligence Framework for Maritime Infrastructures (2020)
Presentation / Conference Contribution
Pitropakis, N., Logothetis, M., Andrienko, G., Karapistoli, I., Stephanatos, J., & Lambrinoudakis, C. (2020). Towards The Creation of A Threat Intelligence Framework for Maritime Infrastructures. In Computer Security: ESORICS 2019 International Workshops

The maritime ecosystem has undergone through changes due to the increasing use of information systems and smart devices. The newly introduced technologies give rise to new attack surface in maritime infrastructures. In this position paper, we propose... Read More about Towards The Creation of A Threat Intelligence Framework for Maritime Infrastructures.

Predicting Malicious Insider Threat Scenarios Using Organizational Data and a Heterogeneous Stack-Classifier (2019)
Presentation / Conference Contribution
Hall, A. J., Pitropakis, N., Buchanan, W. J., & Moradpoor, N. (2019). Predicting Malicious Insider Threat Scenarios Using Organizational Data and a Heterogeneous Stack-Classifier. In 2018 IEEE International Conference on Big Data (Big Data). https://doi.

Insider threats continue to present a major challenge for the information security community. Despite constant research taking place in this area; a substantial gap still exists between the requirements of this community and the solutions that are cu... Read More about Predicting Malicious Insider Threat Scenarios Using Organizational Data and a Heterogeneous Stack-Classifier.