All Outputs (5)

Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems
Presentation / Conference Contribution
Grierson, S., Thomson, C., Papadopoulos, P., & Buchanan, B. (2021, December). Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems. Presented at 2021 14th International Conference on Security of Information and Networks (SIN), Edinburgh, United Kingdom

Intrusion detection systems are integral to the security of networked systems for detecting malicious or anomalous network traffic. As traditional approaches are becoming less effective, machine learning and deep learning-based intrusion detection sy... Read More about Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems.

Scalable Multi-domain Trust Infrastructures for Segmented Networks
Presentation / Conference Contribution
Grierson, S., Ghaleb, B., Buchanan, W. J., Thomson, C., Maglaras, L., & Eckl, C. (2023, November). Scalable Multi-domain Trust Infrastructures for Segmented Networks. Presented at 2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Edinburgh, UK

Within a trust infrastructure, a private key is often used to digitally sign a transaction, which can be verified with an associated public key. Using PKI (Public Key Infrastructure), a trusted entity can produce a digital signature, verifying the au... Read More about Scalable Multi-domain Trust Infrastructures for Segmented Networks.

Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode
Presentation / Conference Contribution
Buchanan, W., Grierson, S., & Uribe, D. (2024, February). Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode. Presented at 10th International Conference on Information Systems Security and Privacy, Rome, Italy

Biometric data is often highly sensitive, and a leak of this data can lead to serious privacy breaches. Some of the most sensitive of this type of data relates to the usage of DNA data on individuals. A leak of this type of data without consent could... Read More about Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode.

Double Public Key Signing Function Oracle Attack on EdDSA Software Implementations
Presentation / Conference Contribution
Grierson, S., Chalkias, K., Buchanan, W. J., & Maglaras, L. (2023, November). Double Public Key Signing Function Oracle Attack on EdDSA Software Implementations. Presented at 2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Edinburgh, United Kingdom

EdDSA is a standardised elliptic curve digital signature scheme introduced to overcome some of the issues prevalent in the more established ECDSA standard. Due to the EdDSA standard specifying that the EdDSA signature be deterministic, if the signing... Read More about Double Public Key Signing Function Oracle Attack on EdDSA Software Implementations.

DID:RING: Ring Signatures Using Decentralised Identifiers For Privacy-Aware Identity Proof
Presentation / Conference Contribution
Kasimatis, D., Grierson, S., Buchanan, W. J., Eckl, C., Papadopoulos, P., Pitropakis, N., Chrysoulas, C., Thomson, C., & Ghaleb, B. (2024, September). DID:RING: Ring Signatures Using Decentralised Identifiers For Privacy-Aware Identity Proof. Presented at 2024 IEEE International Conference on Cyber Security and Resilience (CSR), London, UK

Decentralised identifiers have become a standardised element of digital identity architecture, with supra-national organisations such as the European Union adopting them as a key component for a unified European digital identity ledger. This paper de... Read More about DID:RING: Ring Signatures Using Decentralised Identifiers For Privacy-Aware Identity Proof.