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The rise of online transactions has led to a corresponding increase in online criminal activities. Account takeover attacks, in particular, are challenging to detect, and novel approaches utilize machine learning to identify compromised accounts. This paper aims to conduct a literature review on account takeover detection and user behavior analysis within the cybersecurity domain. By exploring these areas, the goal is to combat account takeovers and other fraudulent attempts effectively.

While postmodern metafiction (or reflexive fiction) is commonly positioned outside the scope of the Ontological Turn due to metafiction's association with postmodernism's insistence on "world as text," this article argues that metafiction's proximity to scientific theories of reflexivity engenders a shift toward what the article calls body as text, a shift that is synchronous with reflexivity's evolution from cybernetics to biological autopoiesis. To trace metafiction's aesthetic evolution from world as text to body as text, the article examines Jorge Luis Borges's short story "The Circular Ruins" (1940) alongside early-order cybernetic theories of reflexivity before examining Salvador Plascencia's The People of Paper (2005) alongside later theories of biological autopoiesis. While both narratives demonstrate an interest in the world-building powers of the text, the article argues that Plascencia's novel demonstrates reflexivity's autopoietic ability to examine the interstitial relationship between material embodiment and nonhuman agencies. By moving away from Borgesian self-regulation toward self-assembly, The People of Paper gradually sheds the epistemological preoccupations of its world-as-text aesthetic in favor a more ontological body-as-text aesthetic, thereby opening up the possibility of interpreting Plascencia's novel as an aestheticization not of the construction of reality but of the construction of the body itself. In marking a distinction between world-as-text metafiction and body-as-text metafiction, the latter emerges as a uniquely useful heuristic in the Ontological Turn for modeling molecular embodiment and nonhuman agency. [ABSTRACT FROM AUTHOR]

Artificial Intelligence, and Machine Learning especially, are becoming increasingly foundational to our collective future. Recent developments around generative models such as ChatGPT, and DALL-E represent just the tip of the iceberg in new gadgets that will change the way we live our lives. Convolutional Neural Networks (CNNs) and Transformer models are at the heart of advancements in the autonomous vehicles and health care industries as well. Yet these models, as impressive as they are, still make plenty of mistakes without justifying or explaining what aspects of the input or internal state, was responsible for the error. Often, the goal of automation is to increase throughput, processing as many tasks as possible in a short a period of time. For some use cases the cost of mistakes might be acceptable as long as production is increased above some set margin. However, in health care, autonomous vehicles, and financial applications, the cost of a mistake might have catastrophic consequences. For this reason, industries where single mistakes can be costly are less enthusiastic about early AI adoption. The field of eXplainable AI (XAI) has attracted significant attention in recent years with the goal of producing algorithms that shed light into the decision-making process of neural networks. In this paper we show how robust vision pipelines can be built using XAI algorithms with the goal of producing automated watchdogs that actively monitor the decision-making process of neural networks for signs of mistakes or ambiguous data. We call these robust vision pipelines, squinting pipelines.

2022 opened with World War C, the first major cyber world war. Wanting to capitalize on history in the making, Information Systems faculty are integrating real time events to increase student engagement, comprehension, and application of IS concepts. This paper outlines a successful midterm evaluation pivot that leverages current events. We discuss two different actions taken and objectives, outcomes, and implications for teaching and educational research. We find that incorporating extreme current events motivates students towards self-learning and creative knowledge outlets, which in turn stimulate greater comprehension, application, and retention across the entire class.

With the rapid development of the autonomous world, local decision making between devices is becoming important. This article provides a new paradigm (Rock-Paper-Scissors-Hammer: RPSH) that can reduce the number of conflicts or decision draws and thus increase the throughput of autonomous devices while reducing the kept number of records or transactions. The paradigm requires a sealed envelope protocol and sequential message passing between both parties to decide unanimously a winner between the two participants without a third-party mediation. The message passing proposes a detailed record in a blockchain-like format that is not corruptible and is verifiable for conflict resolution. A simulated IoT environment is created to show the advantage of the proposed protocol and it shows significant reduction in mean efforts due to the elimination of draws or undecided situations. Autonomous devices, such as cars, need to maintain meticulous, lightweight, but blockchain-like record keeping for insurance settlements or conflict resolutions; that archival data size is significantly reduced by the RPSH protocol.

Complex phenomena such as play, creativity or innovation are familiar, yet difficult to describe in a systematic manner. In this short article I propose six necessary conditions for any comprehensive description of play. Against this background I discuss my systems-theoretic, constructivist and practice-informed approach to play.

The article provides a quantitative and qualitative description of machine learning research in India using measures such as growth rate, global publication share, national-level share of international collaborative papers, citations per paper, and highly cited papers. The data for the study was sourced from Scopus database covering 12-year period 2006-17. The study finds that the United States is the world leader in the machine learning research, followed by China, United Kingdom, Germany, and India. India registered 52.46% annual growth in the subject, more than twice that of the world (22.03%). India's citation impact was 5.34 citations per paper and its national share of highly cited papers was 0.68% (27 papers). The leading Indian research organizations in machine learning research include Vellore Institute of Technology, Anna University, Chennai, Indian Institute of Technology, New Delhi, Indian Institute of Science (IIS), Bangalore, and so on. The top 15 journals that accounted for 31.46% of India's output include International Journal of Machine Learning and Cybernetics (with 82 papers), International Journal of Applied Engineering Research (77 papers), Journal of Machine Learning Research (46 papers), Neurocomputing (44 papers), and so on. [ABSTRACT FROM AUTHOR]

A co-lab in Cyborg Arts was conducted at Parsons/New School University, a leading design school in New York City, over the course of sixteen weeks. This paper discusses the use of Bruno Latour's Actor Network Theory (ANT) (Latour, 2007) in facilitating creative collaboration solutions. Previously, an open call had been placed in targeted venues such as Art and Education, as well as a number of technology user groups in the New York City area to solicit ideas and participants. With the assistance of the Cyborg Foundation three teams were chosen to build prototypes of a new cyborg sense: Team Glass, Team Radiation, and Team Haptics. Team Glass strove to make a cyborg sense detecting the rhythm of changes in the sun's solar flares. Team Radiation made a sense that distinguished between, and alerted the user to different types of organic and inorganic radiation in the environment. Team Haptics used the team leader's own body as a site environment to correct a medical problem by developing a new cyborg sense. Students from Parsons chose which team to work with. Experts and guests either visited the co-lab in person, or used Skype to converse with the participants throughout the course of the semester. Registered Parsons students stayed committed to the lab in order to receive a grade. Other participants had various reasons to remain involved, such as learning new skills, seeing their ideas realized, or stepping outside of their core discipline. The major conduits of communication for the teams outside of lab time were the web-based Slack application that logged a history of their thoughts and interactions, as well as a private student Tumblr to document their progress. This paper discusses how an ANT analysis of practice based learning led to incremental breakthroughs such as starting, stopping, abandoning, and resuming developing these sensing techniques. This resulted in proof of concept artworks, and showcased new aspects of cyborg art.