Faster and as Satisfying: An Evaluation of Alaska's Early Resolution Triage Program

The Alaska Court Early Resolution Program (ERP) addresses many issues – self‐representation in divorce and custody cases, triaging to determine the appropriate resolution approach, the importance of early intervention and the desire to use a simplified process and a problem‐solving approach. This article reports on an evaluation of the Anchorage ERP. It found different outcomes for ERP cases that settled than comparable cases that proceeded on the regular trial process track with respect to the following outcomes:

• time to disposition,
• number of staff processing steps and associated completion time, and
• number of motions to modify filed within two years of the disposition.

     

Monte-Carlo Filesystem Search – A crawl strategy for digital forensics

Criminal investigations invariably involve the triage or cursory examination of relevant electronic media for evidentiary value. Legislative restrictions and operational considerations can result in investigators having minimal time and resources to establish such relevance, particularly in situations where a person is in custody and awaiting interview. Traditional uninformed search methods can be slow, and informed search techniques are very sensitive to the search heuristic's quality. This research introduces Monte-Carlo Filesystem Search, an efficient crawl strategy designed to assist investigators by identifying known materials of interest in minimum time, particularly in bandwidth constrained environments. This is achieved by leveraging random selection with non-binary scoring to ensure robustness. The algorithm is then expanded with the integration of domain knowledge. A rigorous and extensive training and testing regime conducted using electronic media seized during investigations into online child exploitation proves the efficacy of this approach.     

A RAM triage methodology for Hadoop HDFS forensics

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 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.     

Triaging digital device content at-scene:- Formalising the decision-making process

The prominence of technology usage in society has inevitably led to increasing numbers of digital devices being seized, where digital evidence often features in criminal investigations. Such demand has led to well documented backlogs placing pressure on digital forensic labs, where in an effort to combat this issue, the ‘at-scene triage’ of devices has been touted as a solution. Yet such triage approaches are not straightforward to implement with multiple technical and procedural issues existing, including determining when it is actually appropriate to triage the contents of a device at-scene. This work remains focused on this point due to the complexities associated with it, and to support first responders a nine-stage triage decision model is offered which is designed to promote consistent and transparent practice when determining if a device should be triaged.     

Automated event and social network extraction from digital evidence sources with ontological mapping

The sharp rise in consumer computing, electronic and mobile devices and data volumes has resulted in increased workloads for digital forensic investigators and analysts. The number of crimes involving electronic devices is increasing, as is the amount of data for each job. This is becoming unscaleable and alternate methods to reduce the time trained analysts spend on each job are necessary.This work leverages standardised knowledge representations techniques and automated rule-based systems to encapsulate expert knowledge for forensic data. The implementation of this research can provide high-level analysis based on low-level digital artefacts in a way that allows an understanding of what decisions support the facts. Analysts can quickly make determinations as to which artefacts warrant further investigation and create high level case data without manually creating it from the low-level artefacts. Extraction and understanding of users and social networks and translating the state of file systems to sequences of events are the first uses for this work.A major goal of this work is to automatically derive ‘events’ from the base forensic artefacts. Events may be system events, representing logins, start-ups, shutdowns, or user events, such as web browsing, sending email. The same information fusion and homogenisation techniques are used to reconstruct social networks. There can be numerous social network data sources on a single computer; internet cache can locate Facebook, LinkedIn, Google Plus caches; email has address books and copies of emails sent and received; instant messenger has friend lists and call histories. Fusing these into a single graph allows a more complete, less fractured view for an investigator.Both event creation and social network creation are expected to assist investigator-led triage and other fast forensic analysis situations.     

“Blood,Bucks and Bias”: Reliability and biasability of crime scene investigators’ selection and prioritization of blood traces

When crime scene investigators (CSIs) encounter crime scenes with large volumes of blood, some selection and prioritization is often needed, and this will impact on what blood is and is not available for forensic analysis. What factors influence CSIs decision making process is largely unknown. This study examines the effects of awareness of limited resources and irrelevant contextual case information indicating either a homicide or a suicide on CSIs collection of blood traces. To this end, two scenario-based experiments with CSIs and novices were conducted. Overall, the results suggest that even when CSIs decisions are made under identical conditions, their trace selection varies both when it comes to numbers and locations. Furthermore, awareness of limited resources made CSIs collect fewer traces and their selections also varied following the contextual case information, showing similarities and differences with novices. Since blood traces can be used to establish both activity and identity the findings can have important implications for the subsequent investigation as well as trial.     

STR genotyping of DNA extracted from used Triage kits

This study examined whether short tandem repeat (STR) genotyping can be performed using DNA remaining in Triage kits used to screen for drugs of abuse in urine. STR genotyping was successful for 15 loci using 12 kits stored for 1–6 months at room temperature. These results suggest that STR genotyping for human identification can be performed using DNA extracted from used Triage kits.     

OpenLV: Empowering investigators and first-responders in the digital forensics process

The continuing decline in the cost-per-megabyte of hard disk storage has inevitably led to a ballooning volume of data that needs to be reviewed in digital investigations. The result: case backlogs that commonly stretch for months at forensic labs, and per-case processing that occupies days or weeks of analytical effort. Yet speed is critical in situations where delay may render the evidence useless or endanger personal safety, such as when a suspect may flee, a victim is at risk, criminal tactics or control infrastructure may change, etc. In these and other cases, investigators need tools to enable quick triage of computer evidence in order to answer urgent questions, maintain the pace of an investigation and assess the likelihood of acquiring pertinent information from the device.This paper details the design and application of a tool, OpenLV, that not only meets the needs for speedy initial triage, but also can facilitate the review of digital evidence at later stages of investigation. With OpenLV, an investigator can quickly and safely interact with collected evidence, much as if they had sat down at the computer at the time the evidence was collected. Since OpenLV works without modifying the evidence, its use in triage does not preclude subsequent, in-depth forensic analysis. Unlike many popular forensics tools, OpenLV requires little training and facilitates a unprecedented level of interaction with the evidence.