All Outputs (3)

Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode (2024)
Conference Proceeding
Buchanan, W., Grierson, S., & Uribe, D. (2024). Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode. In Proceedings of the 10th International Conference on Information Systems Security and Privacy (226-233). https://doi.org/10.5220/0012454300003648

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.

Scalable Multi-domain Trust Infrastructures for Segmented Networks (2023)
Conference Proceeding
Grierson, S., Ghaleb, B., Buchanan, W. J., Thomson, C., Maglaras, L., & Eckl, C. (in press). Scalable Multi-domain Trust Infrastructures for Segmented Networks.

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.

Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems (2022)
Conference Proceeding
Grierson, S., Thomson, C., Papadopoulos, P., & Buchanan, B. (2022). Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems. In 2021 14th International Conference on Security of Information and Networks (SIN). https://doi.org/10.1109/sin54109.2021.9699157

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.