Outputs (6)

A stacking ensemble of deep learning models for IoT intrusion detection (2023)
Journal Article
Lazzarini, R., Tianfield, H., & Charissis, V. (2023). A stacking ensemble of deep learning models for IoT intrusion detection. Knowledge-Based Systems, 279, Article 110941. https://doi.org/10.1016/j.knosys.2023.110941

The number of Internet of Things (IoT) devices has increased considerably in the past few years, which resulted in an exponential growth of cyber attacks on IoT infrastructure. As a consequence, the prompt detection of attacks in IoT environments thr... Read More about A stacking ensemble of deep learning models for IoT intrusion detection.

FitForensics: A Tool to Acquire Data from FIT-Compatible Wearables via the USB Mass Storage Interface (2023)
Journal Article
Perry, S., Levick, D., & Mckeown, S. (in press). FitForensics: A Tool to Acquire Data from FIT-Compatible Wearables via the USB Mass Storage Interface. Journal of Digital Forensics, Security and Law,

Wearable and fitness tracking devices are commonplace, with global shipments forecast to continue rising in the future. These devices store a wealth of personal data that is useful to the forensic examiner. However, due to device fragmentation, acqui... Read More about FitForensics: A Tool to Acquire Data from FIT-Compatible Wearables via the USB Mass Storage Interface.

Hamming Distributions of Popular Perceptual Hashing Techniques (2023)
Journal Article
McKeown, S., & Buchanan, W. J. (2023). Hamming Distributions of Popular Perceptual Hashing Techniques. Forensic Science International: Digital Investigation, 44(Supplement), Article 301509. https://doi.org/10.1016/j.fsidi.2023.301509

Content-based file matching has been widely deployed for decades, largely for the detection of sources of copyright infringement, extremist materials, and abusive sexual media. Perceptual hashes, such as Microsoft's PhotoDNA, are one automated mechan... Read More about Hamming Distributions of Popular Perceptual Hashing Techniques.

A forensic analysis of streaming platforms on Android OS (2022)
Journal Article
Murias, J. G., Levick, D., & McKeown, S. (2023). A forensic analysis of streaming platforms on Android OS. Forensic Science International: Digital Investigation, 44, Article 301485. https://doi.org/10.1016/j.fsidi.2022.301485

This work builds on existing research in streamed video reconstruction on the Android OS, which previously demonstrated that caching occurs in most cases for the Chrome and Firefox Web browsers. Prior work also outlined that streaming application cac... Read More about A forensic analysis of streaming platforms on Android OS.

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.

Fingerprinting JPEGs With Optimised Huffman Tables (2018)
Journal Article
McKeown, S., Russell, G., & Leimich, P. (2018). Fingerprinting JPEGs With Optimised Huffman Tables. Journal of Digital Forensics, Security and Law, 13(2), Article 7. https://doi.org/10.15394/jdfsl.2018.1451

A common task in digital forensics investigations is to identify known contraband images. This is typically achieved by calculating a cryptographic digest, using hashing algorithms such as SHA256, for each image on a given medium, and comparing indiv... Read More about Fingerprinting JPEGs With Optimised Huffman Tables.