Heteronormativity and the exclusion of bisexuality in psychology

About the book: There has been a recent explosion of interest in Lesbian, Gay, Bisexual and Trans Perspective Psychology amongst students and academics, and this interest is predicted to continue to rise. Recent media debates on subjects such as same-sex marriage have fuelled interest in LGBTQ perspectives. This edited collection showcases the latest thinking in LGBTQ psychology. The book has 21 chapters covering subjects such as same sex parenting, outing, young LGBTQ people, sport, learning disabilities, lesbian and gay identities etc. The book has an international focus, with contributors from UK, US, Canada, Australia and New Zealan

Re-composing the digital present

This paper investigates the temporality that is produced in some recent and historical examples of media art. In exploring works by Janet Cardiff, Dennis Del Favero, and Omer Fast, I use the philosophy of Michel Serres and Gilles Deleuze to understand the convergence of temporalities that are composed in the digital present, as one moment in time overlays another moment. Developing Serres' concept of multi-temporality and Deleuze's philosophy of time and memory into a means to understand the non-linear time presented in these works, I argue that the different compositional strategies enacted by these artists provide the aesthetic grounding to experience “temporal thickness.” From here I investigate the interactive digital artworks Frames by Grahame Weinbren and Can You See Me Now? by the artist group Blast Theory. In this investigation, I understand interaction with technology, and the way that it shapes our sensory and processual experience, as a specifically temporal and temporalizing transaction, where human movements in the present are overlayed by technological processes

Reviews

Eta De Cicco, Mike Farmer and James Hargrave, Using the Internet in Secondary Schools, London: Kogan Page (2nd edn), 2001. ISBN: 0–7494–3459–7. Softback, x + 192 pages, £16.99

On tops, bottoms and ethical sluts: The place of BDSM and polyamory in lesbian and gay psychology

Meg Barker in conversation with Dossie Easton

Applications of Machine Learning to Threat Intelligence, Intrusion Detection and Malware

Artificial Intelligence (AI) and Machine Learning (ML) are emerging technologies with applications to many fields. This paper is a survey of use cases of ML for threat intelligence, intrusion detection, and malware analysis and detection. Threat intelligence, especially attack attribution, can benefit from the use of ML classification. False positives from rule-based intrusion detection systems can be reduced with the use of ML models. Malware analysis and classification can be made easier by developing ML frameworks to distill similarities between the malicious programs. Adversarial machine learning will also be discussed, because while ML can be used to solve problems or reduce analyst workload, it also introduces new attack surfaces