Rethinking Digital Forensics

© IAER 2019In the modern socially-driven, knowledge-based virtual computing environment in which organisations are operating, the current digital forensics tools and practices can no longer meet the need for scientific rigour. There has been an exponential increase in the complexity of the networks with the rise of the Internet of Things, cloud technologies and fog computing altering business operations and models. Adding to the problem are the increased capacity of storage devices and the increased diversity of devices that are attached to networks, operating autonomously. We argue that the laws and standards that have been written, the processes, procedures and tools that are in common use are increasingly not capable of ensuring the requirement for scientific integrity. This paper looks at a number of issues with current practice and discusses measures that can be taken to improve the potential of achieving scientific rigour for digital forensics in the current and developing landscapePeer reviewe

An Evaluation of eScience Lab Kits for Online Learning

Higher education online science courses generally lack the hands-on components essential in understanding theories, methods, and techniques in chemistry and biology. Companies like eScience Labs construct kits to facilitate online learning, which provide students with hands-on activities relevant to their science courses. In order to evaluate ease, efficacy, and comprehension of the forensic science kits by eScience Labs was completed while writing observations of the activities during and after completion; the lab manual learning objectives were compared to results of activities and two stopwatches took elapsed time of each activity to compare with the stated times in the kit manual. This method determined that the eScience manual does not provide enough information for a college freshman to fully understand the topic; however, combining these labs with professor provided online lectures would allow full comprehension of the forensic science applications or techniques. Recommendations to obtain maximum learning outcomes include requiring the completion of prerequisites like algebra and general chemistry. With these aspects combined, the eScience lab kit is a great addition to an introductory forensic science course as it provides safe and interactive hands-on activities

Multinational perspectives on information technology from academia and industry

As the term \u27information technology\u27 has many meanings for various stakeholders and continues to evolve, this work presents a comprehensive approach for developing curriculum guidelines for rigorous, high quality, bachelor\u27s degree programs in information technology (IT) to prepare successful graduates for a future global technological society. The aim is to address three research questions in the context of IT concerning (1) the educational frameworks relevant for academics and students of IT, (2) the pathways into IT programs, and (3) graduates\u27 preparation for meeting future technologies. The analysis of current trends comes from survey data of IT faculty members and professional IT industry leaders. With these analyses, the IT Model Curricula of CC2005, IT2008, IT2017, extensive literature review, and the multinational insights of the authors into the status of IT, this paper presents a comprehensive overview and discussion of future directions of global IT education toward 2025

A Comprehensive Analysis of the Role of Artificial Intelligence and Machine Learning in Modern Digital Forensics and Incident Response

In the dynamic landscape of digital forensics, the integration of Artificial Intelligence (AI) and Machine Learning (ML) stands as a transformative technology, poised to amplify the efficiency and precision of digital forensics investigations. However, the use of ML and AI in digital forensics is still in its nascent stages. As a result, this paper gives a thorough and in-depth analysis that goes beyond a simple survey and review. The goal is to look closely at how AI and ML techniques are used in digital forensics and incident response. This research explores cutting-edge research initiatives that cross domains such as data collection and recovery, the intricate reconstruction of cybercrime timelines, robust big data analysis, pattern recognition, safeguarding the chain of custody, and orchestrating responsive strategies to hacking incidents. This endeavour digs far beneath the surface to unearth the intricate ways AI-driven methodologies are shaping these crucial facets of digital forensics practice. While the promise of AI in digital forensics is evident, the challenges arising from increasing database sizes and evolving criminal tactics necessitate ongoing collaborative research and refinement within the digital forensics profession. This study examines the contributions, limitations, and gaps in the existing research, shedding light on the potential and limitations of AI and ML techniques. By exploring these different research areas, we highlight the critical need for strategic planning, continual research, and development to unlock AI's full potential in digital forensics and incident response. Ultimately, this paper underscores the significance of AI and ML integration in digital forensics, offering insights into their benefits, drawbacks, and broader implications for tackling modern cyber threats

Using Project Management Knowledge and Practice to Address Digital Forensic Investigation Challenges

The management of digital forensics investigations represents a unique challenge. The field is relatively new, and combines the technical challenges of Information Systems with the legal challenges of forensics investigations. The challenges for the Digital Forensics Investigators and the organizations they support are many. This research effort examines the characteristics and challenges of Digital Forensics Investigations and compares them with the features and knowledge areas of project management. The goal was to determine if project management knowledge, as defined in a common body of knowledge, would be helpful in addressing digital forensics investigation challenges identified in the literature. The results indicate that there are parallels between the two areas

PRECEPT:a framework for ethical digital forensics investigations

Purpose: Cyber-enabled crimes are on the increase, and law enforcement has had to expand many of their detecting activities into the digital domain. As such, the field of digital forensics has become far more sophisticated over the years and is now able to uncover even more evidence that can be used to support prosecution of cyber criminals in a court of law. Governments, too, have embraced the ability to track suspicious individuals in the online world. Forensics investigators are driven to gather data exhaustively, being under pressure to provide law enforcement with sufficient evidence to secure a conviction. Yet, there are concerns about the ethics and justice of untrammeled investigations on a number of levels. On an organizational level, unconstrained investigations could interfere with, and damage, the organization’s right to control the disclosure of their intellectual capital. On an individual level, those being investigated could easily have their legal privacy rights violated by forensics investigations. On a societal level, there might be a sense of injustice at the perceived inequality of current practice in this domain. This paper argues the need for a practical, ethically-grounded approach to digital forensic investigations, one that acknowledges and respects the privacy rights of individuals and the intellectual capital disclosure rights of organisations, as well as acknowledging the needs of law enforcement. We derive a set of ethical guidelines, then map these onto a forensics investigation framework. We subjected the framework to expert review in two stages, refining the framework after each stage. We conclude by proposing the refined ethically-grounded digital forensics investigation framework. Our treatise is primarily UK based, but the concepts presented here have international relevance and applicability.Design methodology: In this paper, the lens of justice theory is used to explore the tension that exists between the needs of digital forensic investigations into cybercrimes on the one hand, and, on the other, individuals’ rights to privacy and organizations’ rights to control intellectual capital disclosure.Findings: The investigation revealed a potential inequality between the practices of digital forensics investigators and the rights of other stakeholders. That being so, the need for a more ethically-informed approach to digital forensics investigations, as a remedy, is highlighted, and a framework proposed to provide this.Practical Implications: Our proposed ethically-informed framework for guiding digital forensics investigations suggest a way of re-establishing the equality of the stakeholders in this arena, and ensuring that the potential for a sense of injustice is reduced.Originality/value: Justice theory is used to highlight the difficulties in squaring the circle between the rights and expectations of all stakeholders in the digital forensics arena. The outcome is the forensics investigation guideline, PRECEpt: Privacy-Respecting EthiCal framEwork, which provides the basis for a re-aligning of the balance between the requirements and expectations of digital forensic investigators on the one hand, and individual and organizational expectations and rights, on the other

Educating the effective digital forensics practitioner: academic, professional, graduate and student perspectives

Over the years, digital forensics has become an important and sought-after profession where the gateway of training and education has developed vastly over the past decade. Many UK higher education (HE) institutions now deliver courses that prepare students for careers in digital forensics and, in most recent advances, cyber security. Skills shortages and external influences attributed within the field of cyber security, and its relationship as a discipline with digital forensics, has shifted the dynamic of UK higher education provisions. The implications of this now sees the route to becoming a digital forensic practitioner, be it in law enforcement or business, transform from on-the-job training to university educated, trained analysts. This thesis examined courses within HE and discovered that the delivery of these courses often overlooked areas such as mobile forensics, live data forensics, Linux and Mac knowledge. This research also considered current standards available across HE to understand whether educational programmes are delivering what is documented as relevant curriculum. Cyber security was found to be the central focus of these standards within inclusion of digital forensics, adding further to the debate and lack of distinctive nature of digital forensics as its own discipline. Few standards demonstrated how the topics, knowledge, skills and competences drawn were identified as relevant and effective for producing digital forensic practitioners. Additionally, this thesis analyses and discusses results from 201 participants across five stakeholder groups: graduates, professionals, academics, students and the public. These areas were selected due to being underdeveloped in existing literature and the crucial role they play in the cycle of producing effective practitioners. Analysis on stakeholder views, experiences and thoughts surrounding education and training offer unique insight, theoretical underpinnings and original contributions not seen in existing literature. For example, challenges, costs and initial issues with introducing graduates to employment for the employers and/or supervising practitioners, the lack of awareness and contextualisation on behalf of students and graduates towards what knowledge and skills they have learned and acquired on a course and its practical application on-the-job which often lead to suggestions of a lack of fundamental knowledge and skills. This is evidenced throughout the thesis, but examples include graduates: for their reflections on education based on their new on-the-job experiences and practices; professionals: for their job experiences and requirements, academics: for their educational practices and challenges; students: their initial expectations and views; and, the public: for their general understanding. This research uniquely captures these perspectives, bolstering the development of digital forensics as an academic discipline, along with the importance these diverse views play in the overall approach to delivering skilled practitioners. While the main contribution to knowledge within this thesis is its narrative focusing on the education of effective digital forensic practitioners and its major stakeholders, this thesis also makes additional contributions both academically and professionally; including the discussion, analysis and reflection of: - improvements for education and digital forensics topics for research and curriculum development; - where course offerings can be improved for institutions offering digital forensic degree programmes; - the need for further collaboration between industry and academia to provide students and graduates with greater understanding of the real-life role of a digital forensic practitioner and the expectations in employment; - continuous and unique challenges within both academia and the industry which digital forensics possess and the need for improved facilities and tool development to curate and share problem and scenario-based learning studies

Digital Forensics AI: Evaluating, Standardizing and Optimizing Digital Evidence Mining Techniques

The impact of AI on numerous sectors of our society and its successes over the years indicate that it can assist in resolving a variety of complex digital forensics investigative problems. Forensics analysis can make use of machine learning models’ pattern detection and recognition capabilities to uncover hidden evidence in digital artifacts that would have been missed if conducted manually. Numerous works have proposed ways for applying AI to digital forensics; nevertheless, scepticism regarding the opacity of AI has impeded the domain’s adequate formalization and standardization. We present three critical instruments necessary for the development of sound machine-driven digital forensics methodologies in this paper. We cover various methods for evaluating, standardizing, and optimizing techniques applicable to artificial intelligence models used in digital forensics. Additionally, we describe several applications of these instruments in digital forensics, emphasizing their strengths and weaknesses that may be critical to the methods’ admissibility in a judicial process