Outputs (12)

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.

A Comparative Analysis of Honeypots on Different Cloud Platforms (2021)
Journal Article
Kelly, C., Pitropakis, N., Mylonas, A., McKeown, S., & Buchanan, W. J. (2021). A Comparative Analysis of Honeypots on Different Cloud Platforms. Sensors, 21(7), Article 2433. https://doi.org/10.3390/s21072433

In 2019, the majority of companies used at least one cloud computing service and it is expected that by the end of 2021, cloud data centres will process 94% of workloads. The financial and operational advantages of moving IT infrastructure to special... Read More about A Comparative Analysis of Honeypots on Different Cloud Platforms.

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.

Forensic Considerations for the High Efficiency Image File Format (HEIF) (2020)
Presentation / Conference Contribution
Mckeown, S., & Russell, G. (2020). Forensic Considerations for the High Efficiency Image File Format (HEIF). . https://doi.org/10.1109/CyberSecurity49315.2020.9138890

The High Efficiency File Format (HEIF) was adopted by Apple in 2017 as their favoured means of capturing images from their camera application, with Android devices such as the Galaxy S10 providing support more recently. The format is positioned to re... Read More about Forensic Considerations for the High Efficiency Image File Format (HEIF).

Using Amazon Alexa APIs as a Source of Digital Evidence (2020)
Presentation / Conference Contribution
Krueger, C., & Mckeown, S. (2020). Using Amazon Alexa APIs as a Source of Digital Evidence. . https://doi.org/10.1109/CyberSecurity49315.2020.9138849

With the release of Amazon Alexa and the first Amazon Echo device, the company revolutionised the smart home. It allowed their users to communicate with, and control, their smart home ecosystem purely using voice commands. However, this also means th... Read More about Using Amazon Alexa APIs as a Source of Digital Evidence.

Towards Identifying Human Actions, Intent, and Severity of APT Attacks Applying Deception Techniques - An Experiment (2020)
Presentation / Conference Contribution
Chacon, J., Mckeown, S., & Macfarlane, R. (2020, June). Towards Identifying Human Actions, Intent, and Severity of APT Attacks Applying Deception Techniques - An Experiment. Presented at IEEE International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2020), Dublin, Ireland

Attacks by Advanced Persistent Threats (APTs) have been shown to be difficult to detect using traditional signature-and anomaly-based intrusion detection approaches. Deception techniques such as decoy objects, often called honey items, may be deploye... Read More about Towards Identifying Human Actions, Intent, and Severity of APT Attacks Applying Deception Techniques - An Experiment.

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), Dublin, Ireland

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.

Sub-file Hashing Strategies for Fast Contraband Detection (2018)
Presentation / Conference Contribution
McKeown, S., Russell, G., & Leimich, P. (2018, June). Sub-file Hashing Strategies for Fast Contraband Detection. Presented at IEEE International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2018), Glasgow, Scotland

Traditional digital forensics processes do not scale well with the huge quantities of data present in a modern investigation, resulting in large investigative backlogs for many law enforcement agencies. Data reduction techniques are required for fast... Read More about Sub-file Hashing Strategies for Fast Contraband Detection.

Reducing the Impact of Network Bottlenecks on Remote Contraband Detection (2018)
Presentation / Conference Contribution
McKeown, S., Russell, G., & Leimich, P. (2018, June). Reducing the Impact of Network Bottlenecks on Remote Contraband Detection. Presented at IEEE International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2018), Glasgow, UK

Cloud based storage is increasing in popularity, with
large volumes of data being stored remotely. Digital forensics
investigators examining such systems remotely are limited by
bandwidth constraints when accessing this kind of data using
traditi... Read More about Reducing the Impact of Network Bottlenecks on Remote Contraband Detection.

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.

Fast Filtering of Known PNG Files Using Early File Features (2017)
Presentation / Conference Contribution
McKeown, S., Russell, G., & Leimich, P. (2017). Fast Filtering of Known PNG Files Using Early File Features. In Proceedings of the Conference on Digital Forensics, Security and Law

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 media, comparing individual... Read More about Fast Filtering of Known PNG Files Using Early File Features.