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The increasing use of encrypted data within file storage and in network communications leaves investigators with many challenges. One of the most challenging is the Tor protocol, as its main focus is to protect the privacy of the user, in both its local footprint within a host and over a network connection. The Tor browser, though, can leave behind digital artefacts which can be used by an investigator. This paper outlines an experimental methodology and provides results for evidence trails which can be used within real-life investigations.

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 are now so large that it can take several hours just to read this data from the disk, and can contribute to the large investigative backlogs suffered by many law enforcement bodies. Digital forensic triage techniques may thus be used to prioritise evidence and effect faster investigation turnarounds. This paper proposes a new forensic triage method for investigating disk evidence relating to picture files, making use of centralised thumbnail caches that are present in the Windows operating system. Such centralised caches serve as a catalogue of images on the device, allowing for fast triage. This work includes a comprehensive analysis of the thumbnail variants across a range of windows operating systems, which causes difficulties when detecting contraband using cryptographic hash databases. A novel method for large-scale hash database generation is described which allows precalculated cryptographic hash databases to be built from arbitrary image sets for use in thumbnail contraband detection. This approach allows for cryptographic hashes to be generated for multiple Windows versions from the original source image, facilitating wider detection. Finally, a more flexible approach is also proposed which makes novel use of perceptual hashing techniques, mitigating issues caused by the differences between thumbnails across Windows versions. A key contribution of this work demonstrates that by using new techniques, thumbnail caches can be used to robustly and effectively detect contraband in seconds, with processing times being largely independent of disk capacity.

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 individual digests with a database of known contraband. However, the large capacities of modern storage media and time pressures placed on forensics examiners necessitates the development of more efficient processing methods. This work describes a technique for fingerprinting JPEGs with optimised Huffman tables which requires only the image header to be present on the media. Such fingerprints are shown to be robust across large datasets, with demonstrably faster processing times.

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 and effective digital forensics triage, and to reduce the time taken to conduct an investigation. This work explores the potential of sub-file cryptographic hashing strategies, where small fragments of files are hashed in lieu of processing the file in its entirety, for contraband detection. Results show that subfile hashing techniques perform well, particularly on solid state media, while also retaining a high degree of discriminating power. Such strategies may offer an opportunity to take advantage of the performance characteristics of non-mechanical media, streamlining future investigations and greatly reducing investigation times.

This paper discusses the challenges of performing a forensic investigation against a multi-node Hadoop cluster and proposes a methodology for examiners to use in such situations. The procedure's aim of minimising disruption to the data centre during the acquisition process is achieved through the use of RAM forensics. This affords initial cluster reconnaissance which in turn facilitates targeted data acquisition on the identified DataNodes. To evaluate the methodology's feasibility, a small Hadoop Distributed File System (HDFS) was configured, and forensic artefacts simulated upon it by deleting data originally stored in in the cluster. RAM acquisition and analysis was then performed on the NameNode in order to test the validity of the suggested methodology. The results are cautiously positive in establishing that RAM analysis of the NameNode can be used to pinpoint the data blocks affected by the attack, allowing a targeted approach to the acquisition of data from the DataNodes, provided that the physical locations can be determined. A full forensic analysis of the DataNodes was beyond the scope of this project.

A new approach to the space-time modelling of infectious diseases is considered. A modulated heterogeneous Poisson process with intensity defined as a function of a two-dimensional susceptibility field is proposed. The model is fitted to a measles epidemic using a proportional hazards approximation.

A new approach to the space-time modelling of infectious diseases is considered. A modulated heterogeneous Poisson process with intensity defined as a function of a 2-dimensional susceptibility field is proposed. The model is fitted to a measles epidemic.