Cosmic Topologies of Imitation: From the Horror of Digital Autotoxicus to the Auto-Toxicity of the Social

This article expands on an earlier concept of horror autotoxicus linked to digital contagions of spam and network Virality.1 It aims to present, as such, a broader conception of cosmic topologies of imitation (CTI) intended to better grasp the relatively new practices of social media marketing. Similar to digital autotoxicity, CTI provide the perfect medium for sharing while also spreading contagions that can potentially contaminate the medium itself. However, whereas digital contagions are perhaps limited to the toxicity of a technical layer of information viruses, the contagions of CTI are an all pervasive auto-toxicity which can infect human bodies and technologies increasingly in concert with each other. This is an exceptional autotoxicus that significantly blurs the immunological line of exemption between self and nonself, and potentially, the anthropomorphic distinction between individual self and collective others.

Mining Police-Recorded Offence and Incident Data to Inform a Definition of Repeat Domestic Abuse Victimization for Statistical Reporting

Following inspections in 2013 of all police forces, Her Majesty’s Inspectorate of Constabulary found that one-third of forces could not provide data on repeat victims of domestic abuse (DA) and concluded that in general there were ambiguities around the term ‘repeat victim’ and that there was a need for consistent and comparable statistics on DA. Using an analysis of police-recorded DA data from two forces, an argument is made for including both offences and non-crime incidents when identifying repeat victims of DA. Furthermore, for statistical purposes the counting period for repeat victimizations should be taken as a rolling 12 months from first recorded victimization. Examples are given of summary statistics that can be derived from these data down to Community Safety Partnership level. To reinforce the need to include both offences and incidents in analyses, repeat victim chronologies from policerecorded data are also used to briefly examine cases of escalation to homicide as an example of how they can offer new insights and greater scope for evaluating risk and effectiveness of interventions.

Search Based Clustering for Protecting Software with Diversified Updates

Reverse engineering is usually the stepping stone of a variety of at-tacks aiming at identifying sensitive information (keys, credentials, data, algo-rithms) or vulnerabilities and flaws for broader exploitation. Software applica-tions are usually deployed as identical binary code installed on millions of com-puters, enabling an adversary to develop a generic reverse-engineering strategy that, if working on one code instance, could be applied to crack all the other in-stances. A solution to mitigate this problem is represented by Software Diversity, which aims at creating several structurally different (but functionally equivalent) binary code versions out of the same source code, so that even if a successful attack can be elaborated for one version, it should not work on a diversified ver-sion. In this paper, we address the problem of maximizing software diversity from a search-based optimization point of view. The program to protect is subject to a catalogue of transformations to generate many candidate versions. The problem of selecting the subset of most diversified versions to be deployed is formulated as an optimisation problem, that we tackle with different search heuristics. We show the applicability of this approach on some popular Android apps.