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The 2020 United States presidential election was, and has continued to be, the focus of pervasive and persistent mis- and disinformation spreading through our media ecosystems, including social media. This event has driven the collection and analysis of large, directed social network datasets, but such datasets can resist intuitive understanding. In such large datasets, the overwhelming number of nodes and edges present in typical representations create visual artifacts, such as densely overlapping edges and tightly-packed formations of low-degree nodes, which obscure many features of more practical interest. We apply a method, coengagement transformations, to convert such networks of social data into tractable images. Intuitively, this approach allows for parameterized network visualizations that make shared audiences of engaged viewers salient to viewers. Using the interpretative capabilities of this method, we perform an extensive case study of the 2020 United States presidential election on Twitter, contributing an empirical analysis of coengagement. By creating and contrasting different networks at different parameter sets, we define and characterize several structures in this discourse network, including bridging accounts, satellite audiences, and followback communities. We discuss the importance and implications of these empirical network features in this context. In addition, we release open-source code for creating coengagement networks from Twitter and other structured interaction data., Comment: Accepted for publication at ICWSM '23

We present an example implementation of the previously published Malware Analysis Tool Evaluation Framework (MATEF) to explore if a systematic basis for trusted practice can be established for evaluating malware artefact detection tools used within a forensic investigation. The application of the framework is demonstrated through a case study which presents the design of two example experiments that consider the hypotheses: (1) Is there an optimal length of time in which to execution malware for analysis and (2) Is there any observable difference between tools when observing malware behaviour? The experiments used a sample of 4,800 files known to produce network artefacts. These were selected at random from a library of over 350,000 malware binaries. The tools Process Monitor and TCPVCon, popular in the digital forensic community, are chosen as the subjects for investigating these two questions. The results indicate that it is possible to use the MATEF to identify an optimal execution time for a software tool used to monitor activity generated by malware.

We introduce a novel planar tunneling architecture for van der Waals heterostructures based on via contacts, namely metallic contacts embedded into through-holes in hexagonal boron nitride ($h$BN). We use the via-based tunneling method to study the single-particle density of states of two different two-dimensional (2D) materials, NbSe$_2$ and graphene. In NbSe$_2$ devices, we characterize the barrier strength and interface disorder for barrier thicknesses of 0, 1 and 2 layers of $h$BN and study the dependence on tunnel-contact area down to $(44 \pm 14)^2 $ nm$^2$. For 0-layer $h$BN devices, we demonstrate a crossover from diffusive to point contacts in the small-contact-area limit. In graphene, we show that reducing the tunnel barrier thickness and area can suppress effects due to phonon-assisted tunneling and defects in the $h$BN barrier. This via-based architecture overcomes limitations of other planar tunneling designs and produces high-quality, ultra-clean tunneling structures from a variety of 2D materials.

It is imperative for all stakeholders that digital forensics investigations produce reliable results to ensure the field delivers a positive contribution to the pursuit of justice across the globe. Some aspects of these investigations are inevitably contingent on trust, however this is not always explicitly considered or critically evaluated. Erroneously treating features of the investigation as trusted can be enormously damaging to the overall reliability of an investigations findings as well as the confidence that external stakeholders can have in it. As an example, digital crime scenes can be manipulated by tampering with the digital artefacts left on devices, yet recent studies have shown that efforts to detect occurrences of this are rare and argue that this leaves digital forensics investigations vulnerable to accusations of inaccuracy. In this paper a new approach to digital forensics is considered based on the concept of Zero Trust, an increasingly popular design in network security. Zero Trust describes the practitioner mindset and principles upon which the reliance on trust in network components is eliminated in favour of dynamic verification of network interactions. An initial definition of Zero Trust Digital Forensics will be proposed and then a specific example considered showing how this strategy can be applied to digital forensic investigations to mitigate against the specific risk of evidence tampering. A definition of Zero Trust Digital Forensics is proposed, specifically that it is a strategy adopted by investigators whereby each aspect of an investigation is assumed to be unreliable until verified. A new principle will be introduced, namely the multifaceted verification of digital artefacts that can be used by practitioners who wish to adopt a Zero Trust Digital Forensics strategy during their investigations...

Following a series of high profile miscarriages of justice in the UK linked to questionable expert evidence, the post of the Forensic Science Regulator was created in 2008. The main objective of this role is to improve the standard of practitioner competences and forensic procedures. One of the key strategies deployed to achieve this is the push to incorporate a greater level of scientific conduct in the various fields of forensic practice. Currently there is no statutory requirement for practitioners to become accredited to continue working with the Criminal Justice System of England and Wales. However, the Forensic Science Regulator is lobbying the UK Government to make this mandatory. This paper focuses upon the challenge of incorporating a scientific methodology to digital forensic investigations where malicious software ('malware') has been identified. One aspect of such a methodology is the approach followed to both select and evaluate the tools used to perform dynamic malware analysis during an investigation. Based on the literature, legal, regulatory and practical needs we derive a set of requirements to address this challenge. We present a framework, called the 'Malware Analysis Tool Evaluation Framework' (MATEF), to address this lack of methodology to evaluate software tools used to perform dynamic malware analysis during investigations involving malware and discuss how it meets the derived requirements., Comment: Article in press. Accepted by Journal of Digital Forensics, Security and Law (JDFSL)