An evaluation of the ‘open source internet research tool’: a user-centred and participatory design approach with UK law enforcement

As part of their routine investigations, law enforcement conducts open source research; that is, investigating and researching using publicly available information online. Historically, the notion of collecting open sources of information is as ingrained as the concept of intelligence itself. However, utilising open source research in UK law enforcement is a relatively new concept not generally, or practically, considered until after the civil unrest seen in the UK’s major cities in the summer of 2011. While open source research focuses on the understanding of bein‘publicly available’, there are legal, ethical and procedural issues that law enforcement must consider. This asks the following mainresearch question: What constraints do law enforcement face when conducting open source research? From a legal perspective, law enforcement officials must ensure their actions are necessary and proportionate, more so where an individual’s privacy is concerned under human rights legislation and data protection laws such as the General Data Protection Regulation. Privacy issues appear, though, when considering the boom and usage of social media, where lines can be easily blurred as to what is public and private. Guidance from Association of Chief Police Officers (ACPO) and, now, the National Police Chief’s Council (NPCC) tends to be non-committal in tone, but nods towards obtaining legal authorisation under the Regulation of Investigatory Powers Act (RIPA) 2000 when conducting what may be ‘directed surveillance’. RIPA, however, pre-dates the modern era of social media by several years, so its applicability as the de-facto piece of legislation for conducting higher levels of open source research is called into question. 22 semi-structured interviews with law enforcement officials were conducted and discovered a grey area surrounding legal authorities when conducting open source research. From a technical and procedural aspect of conducting open source research, officers used a variety of software tools that would vary both in price and quality, with no standard toolset. This was evidenced from 20 questionnaire responses from 12 police forces within the UK. In an attempt to bring about standardisation, the College of Policing’s Research, Identifying and Tracing the Electronic Suspect (RITES) course recommended several capturing and productivity tools. Trainers on the RITES course, however, soon discovered the cognitive overload this had on the cohort, who would often spend more time learning to use the tools than learn about open source research techniques. The problem highlighted above prompted the creation of Open Source Internet Research Tool (OSIRT); an all-in-one browser for conducting open source research. OSIRT’s creation followed the user-centred design (UCD) method, with two phases of development using the software engineering methodologies ‘throwaway prototyping’, for the prototype version, and ‘incremental and iterative development’ for the release version. OSIRT has since been integrated into the RITES course, which trains over 100 officers a year, and provides a feedback outlet for OSIRT. System Usability Scale questionnaires administered on RITES courses have shown OSIRT to be usable, with feedback being positive. Beyond the RITES course, surveys, interviews and observations also show OSIRT makes an impact on everyday policing and has reduced the burden officers faced when conducting opens source research. OSIRT’s impact now reaches beyond the UK and sees usage across the globe. OSIRT contributes to law enforcement output in countries such as the USA, Canada, Australia and even Israel, demonstrating OSIRT’s usefulness and necessity are not only applicable to UK law enforcement. This thesis makes several contributions both academically and from a practical perspective to law enforcement. The main contributions are: • Discussion and analysis of the constraints law enforcement within the UK face when conducting open source research from a legal, ethical and procedural perspective. • Discussion, analysis and reflective discourse surrounding the development of a software tool for law enforcement and the challenges faced in what is a unique development. • An approach to collaborating with those who are in ‘closed’ environments, such as law enforcement, to create bespoke software. Additionally, this approach offers a method of measuring the value and usefulness of OSIRT with UK law enforcement. • The creation and integration of OSIRT in to law enforcement and law enforcement training packages

Digital Forensics AI: on Practicality, Optimality, and Interpretability of Digital Evidence Mining Techniques

Digital forensics as a field has progressed alongside technological advancements over the years, just as digital devices have gotten more robust and sophisticated. However, criminals and attackers have devised means for exploiting the vulnerabilities or sophistication of these devices to carry out malicious activities in unprecedented ways. Their belief is that electronic crimes can be committed without identities being revealed or trails being established. Several applications of artificial intelligence (AI) have demonstrated interesting and promising solutions to seemingly intractable societal challenges. This thesis aims to advance the concept of applying AI techniques in digital forensic investigation. Our approach involves experimenting with a complex case scenario in which suspects corresponded by e-mail and deleted, suspiciously, certain communications, presumably to conceal evidence. The purpose is to demonstrate the efficacy of Artificial Neural Networks (ANN) in learning and detecting communication patterns over time, and then predicting the possibility of missing communication(s) along with potential topics of discussion. To do this, we developed a novel approach and included other existing models. The accuracy of our results is evaluated, and their performance on previously unseen data is measured. Second, we proposed conceptualizing the term “Digital Forensics AI” (DFAI) to formalize the application of AI in digital forensics. The objective is to highlight the instruments that facilitate the best evidential outcomes and presentation mechanisms that are adaptable to the probabilistic output of AI models. Finally, we enhanced our notion in support of the application of AI in digital forensics by recommending methodologies and approaches for bridging trust gaps through the development of interpretable models that facilitate the admissibility of digital evidence in legal proceedings

Digital Forensics AI: on Practicality, Optimality, and Interpretability of Digital Evidence Mining Techniques

Digital forensics as a field has progressed alongside technological advancements over the years, just as digital devices have gotten more robust and sophisticated. However, criminals and attackers have devised means for exploiting the vulnerabilities or sophistication of these devices to carry out malicious activities in unprecedented ways. Their belief is that electronic crimes can be committed without identities being revealed or trails being established. Several applications of artificial intelligence (AI) have demonstrated interesting and promising solutions to seemingly intractable societal challenges. This thesis aims to advance the concept of applying AI techniques in digital forensic investigation. Our approach involves experimenting with a complex case scenario in which suspects corresponded by e-mail and deleted, suspiciously, certain communications, presumably to conceal evidence. The purpose is to demonstrate the efficacy of Artificial Neural Networks (ANN) in learning and detecting communication patterns over time, and then predicting the possibility of missing communication(s) along with potential topics of discussion. To do this, we developed a novel approach and included other existing models. The accuracy of our results is evaluated, and their performance on previously unseen data is measured. Second, we proposed conceptualizing the term “Digital Forensics AI” (DFAI) to formalize the application of AI in digital forensics. The objective is to highlight the instruments that facilitate the best evidential outcomes and presentation mechanisms that are adaptable to the probabilistic output of AI models. Finally, we enhanced our notion in support of the application of AI in digital forensics by recommending methodologies and approaches for bridging trust gaps through the development of interpretable models that facilitate the admissibility of digital evidence in legal proceedings

Virginia Commonwealth University Courses

Listing of courses for the 2022-2023 year

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe