In the era of cloud computing, the focus of cyber criminals has shifted from traditional IT infrastructures to the cloud.Cyber forensic investigations in the cloud present several challenges due to legal obligations, technical limitations, and the dynamic nature of cloud resources.For instance, access to digital assets is crucial for practical analysis but is often hindered, as investigators may not have complete access to disk images or log files.The mainstream forensic frameworks and solutions for identifying, retrieving, and preserving evidence in the cloud are lacking.Yet, NIST has identified 65 cloud forensics challenges, with 13 related to log files alone.The preservation and integrity of forensic evidence are the backbones of a digital forensic investigation, and the chain of custody proves the authenticity of the evidence.However, cloud environments are not designed to handle digital evidence with integrity, leading to severe issues when presenting evidence in a court of law.This paper delves into the challenges of cloud forensics investigation, focusing on log files, and aims to identify potential solutions and frameworks to support the chain of custody.For that purpose, the authors evaluate the suitability of blockchain technology for maintaining a proper chain of custody of log files in the cloud.A prototype is implemented to serve as a proof of concept.

This research to practice paper presents a reflective study showing the observations of the teaching teams and the practices during industrial projects for the Master of Software Development (MSwDev) program at Victoria University of Wellington (VUW), New Zealand. It is a conversion master program that helps the students to acquire specific skills to be ready for the transition to the software development industry, including the ability to work in an Agile team. Software development projects supported by industrial partners are an excellent means to evaluate the technical capacity of the students and the required skills. This reflective paper describes the evolution of an industry-sourced problem-based agile student project, which over three successive years, has included students from three different cohorts (User Experience (UX), Business Analysts (BA), and Software Developers (SwDev)). This year, a collaboration between different cohorts was not possible. Thus only software development students formed the agile teams.This paper describes and reflects on the teaching staff’s useful and problematic observations over the last twelve months using only the SwDev cohort and correlates that to the previous reflections when three different cohorts formed an Agile team. Those reflections are described, and several recommendations are drawn from the experiences. The authors also discuss the lessons learnt and the effect of COVID-19 on the teams’ performance.

This Research to Practice Full Paper presents a reflective study showing the online teaching and advisory practices during Covid-19. Due to the COVID-19 pandemic, distance learning and active practices to engage online learners are now centre focused on educational institutions' everyday praxis. Tertiary educators have often struggled during enforced lockdowns to convert courses from face-to-face delivery to pure online delivery. This change has presented challenges in curriculum development as academics strive to achieve best practice. It is also challenging to design a pedagogically sound and engaging course for diverse students from a broad spectrum of educational backgrounds. Online classes often require unique infrastructures such as devices with specific tools or hardware requirements. This paper presents a reflective study showing the online teaching and advisory practices during Covid-19 by the first author while teaching and supervising Master of Science (MSc) dissertation students online at a top-ranked UK university (i.e. University of Liverpool). The first author has been involved in the programme for more than ten years. This university is called University A (Uni A) throughout this paper. The paper demonstrates Uni A students' journey from finding the dissertation advisor to completing the research project. It also discusses the class structure, the university policy and guidelines, teaching practices, and how student progress is managed and assessed. The paper then contrasts the first authors experience at Uni A with that of all authors (including the first author - who has been working at both universities) experience supervising postgraduate and honours students at a top New Zealand University (i.e. Victoria University of Wellington). This university is called University B (Uni B) throughout this paper. The lessons learnt from teaching a stream of students enrolled in a pure distance learning degree (i.e. deliberate online degree) at Uni A offers insight into how Uni B might better restructure its predominantly face-to-face degrees to support both online and in-person best practices.

Development platforms, such as GitHub, GitLab, and BitBucket, have become very popular among software developers. Unfortunately, it is not uncommon for developers to inadvertently leak secrets (e.g. API keys, credentials) and confidential source code on public Git repositories, facilitating numerous security breaches that impact reputation and result in losing revenue. Current Git leak detection strategies and tools often fall short due to a high false-positive rate, an ever-growing number of platforms and repositories to inspect, and a limited reach. This paper investigates the shortcomings of traditional Git leak detection methodologies and introduces an alternative approach to overcome those shortcomings. The approach consists of identifying all Git repositories associated with an organisation by collecting the URLs and the respective maintainer names from its endpoint fleet, empowering blue-teams to prioritise content inspection efforts against a well-defined set of targets and to boost incident response capabilities. The paper describes a prototype we implemented that serves as a proof of concept for the approach.

Digital Right Management (DRM) is a technology developed to prevent illegal reproduction and distribution of digital contents. It protects the rights of content owners by allowing only authorised consumers to legitimately access associated digital content. DRM systems typically use a consumer's identity for authentication. In addition, some DRM systems collect consumer's preferences to obtain a content license. Thus, the behaviour of DRM systems disadvantages the digital content consumers (i.e. neglecting consumers' privacy) focusing more on securing the digital content (i.e. biased towards content owners). This paper proposes the Privacy-Preserving Digital Rights Management System (PrivDRM) that allows a consumer to acquire digital content with its license without disclosing complete personal information and without using any third parties. To evaluate the performance of the proposed solution, a prototype of the PrivDRM system has been developed and investigated. The security analysis (attacks and threats) are analysed and showed that PrivDRM supports countermeasures for well-known attacks and achieving the privacy requirements. In addition, a comparison with some well-known proposals shows that PrivDRM outperforms those proposals in terms of processing overhead.

Bitcoin is a peer-to-peer software system that is primarily used as digital money. There exist many software libraries supporting various programming languages that allow access to the Bitcoin system via an Application Programming Interface (API). APIs that are inappropriately used would lead to bugs and security vulnerabilities, which are hard to discover resulting in serious zero-day attacks. Making APIs usable is, therefore, an essential aspect related to the quality and robustness of software. This paper surveys the general academic literature concerning API usability and usable security. Furthermore, it evaluates the API usability of libbitcoin, a well-known C++ implementation of the bitcoin system, and assesses how the findings of this evaluation could affect the applications that use libbitcoin. In addition, the paper proposes two static analysis tools for such a purpose. The findings of this research have improved libbitcoin in many places as will be shown in the paper.

The number of distance learning degrees has increased dramatically over the last decade. Yet, despite this increase, teaching computer security subjects for online students remains challenging. Online classes often need a special infrastructure such as devices with specific tools, or hardware requirements. It is also a challenge to design a course that is pedagogically sound, engaging and fun for students who may come from a wide spectrum of educational backgrounds. The quality of the education delivered also differs from one institution to another. To provide a sense of accreditation and regulation, the National Cyber-security Centre, which is a part of Government Communications Headquarters (GCHQ) in the United Kingdom (UK) has certified only two online (i.e. distance learning) cybersecurity MSc degrees in the country.This paper presents an innovative way of designing capstone projects (i.e. case studies) along with the impact of it on retention, completion, and success rates in a world-class distance learning degree at the University of Liverpool (UoL) over the last ten years. The Chartered Institute for IT (i.e. BSC) is the accreditation body of the degree program studied in this research1.

Mobile computational offloading offers a solution to extend the computational power of a mobile device allowing it to run heavyweight activities/tasks. This turns low-end mobile devices into a capable machine of running heavyweight applications that require special processing power. Code offloading is achieved through migration. Migrating code from a local machine (i.e. mobile device) to the cloud where the code is actually executed is challenging. Questions such as when and how migration takes place are critical. Quite a few offloading frameworks are proposed in the literature. They are, mostly, mostly not efficient due to the lack of a standard offloading architecture, some did not propose an architecture at all. The abundance of Quality of Service (QoS) component is another concern. This paper introduces a layered approach to mobile computation offloading called LAMCO. LAMCO is implemented in the Android operating system and the run-time performance of the framework is evaluated in this paper. One advantage of LAMCO is that it does not require any modifications in the underlying operating system as the framework is dynamically installed and updated while the operating system is intact.

This innovative practice paper describes a projectbased group work where conversion master students developed the skills required for agile software development methods. There are many examples of agile methods taught in, for instance, capstone courses in software engineering programmes. It has been shown to be a popular and beneficial method of learning. However, most agile teams in the software industry are made up of members with different educational backgrounds (i.e. not just software developers, as there will also business analysts, designers, testers etc.). Such a diversity of roles might be beneficial in teaching agile methods in an academic setting. This reflective educational paper describes the evolution of an industry sourced problem-based agile student project, which over three successive years has included students from three different faculties. Although the experience has broadly been positive each year, this paper describes and reflects on both the good and problematic observations that the teaching staff has made over the years. The changes of the projects has been based by reflecting on these insights. These reflections are described and several recommendations are drawn from the experiences. These include, that it is important that the cohorts collaborate and work together in parallel. Individual groups, of diverse cohorts, should work in isolation. It is important to have industrial partners who are participating actively in the process, and it is important to not underestimate the work that is required by the academics to coordinate the projects to make them successful.

Literature-Based Discovery (LBD) is the science of relating existing knowledge in literature to discover new relationships. It is sometimes referred to as hidden knowledge. This paper provides the most recent classification of the existing LBD methods relating the problem to other domains such as information retrieval. The papers identifies that Vector Space Model, Probabilistic Model, and Inference Network Model are the mostly used for LBD problem. The researchers of this paper justified their belief that there are important differences between the problem domains with regards to novelty, time factor, reasoning, and relevance. Moreover, the paper introduces the on-going work of the authors on proposing a new evaluation methodology that addresses the weaknesses of the current methodologies investigating the desirable characteristics of the future LBD evaluation methodology.