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Alert!!! This isn’t just another typical generative AI blog. It’s an opportunity to step beyond the basics and explore the lesser-known, often surprising aspects of what these models come up with when we step out of the room. Curious? Now imagine this. A generative model working silently in a data center, processing information at lightning The post The Secret Lives of Generative AI Models: What They Create When We’re Not Watching appeared first on IEEE Computer Society.

Security verification for hardware is literally foundational: hardware resides on technology’s ground floor, so attacks on it can impact every floor above it, including operating systems, applications, and communications. To examine technology’s hardware foundation, a group of researchers recently used simulation-based hardware information-flow tracking (IFT) for hardware secu­rity verification. IFT uses knowledge of design assets The post OpenTitan Security Verification: An Information Flow Tracking (IFT) Approach appeared first on IEEE Computer Society.

In a boon for student engagement in computer science and engineering disciplines, 70 pre-college students gathered for the IEEE Computer Society (CS) Juniors Program in Sayama, Japan. Over two days, these junior, middle, and high school students experienced the excitement of programming and artificial intelligence (AI) through creative, hands-on activities like game development and virtual The post Future Innovators Unite: IEEE Computer Society Juniors Program Empowers Students with AI Knowledge appeared first on IEEE Computer Society.

Software-only solutions for preventing attackers from exploiting memory errors face two problems: They are too expensive to be broadly deployed. They are prone to circumvention. These issues have motivated researchers to explore how to build and implement more reliable, efficient defensive features in hardware. Exploring Hardware Security Approaches The ongoing research efforts into the development, The post Hardware Security Features and Their Impact appeared first on IEEE Computer Society.

Introduction IEEE P3366.1 (Standard for Geometry Point Cloud Compression) aims at the standardization of point cloud compression technologies. There is a practical demand for point cloud compression standardization, especially for the transmission of high-volume volumetric data over bandwidth-constrained networks and the processing of such data on storage-constrained consumer devices. Point cloud consists of a set The post Participate in Standards Development for Point Cloud Compression (IEEE P3366.1) appeared first on IEEE Computer Society.

When traditional semiconductor technologies are unable to meet specific nonfunctional requirements of emerging products—including for factors such as energy consumption, peak power dissipation, and chip cost and/or size—new technologies must emerge to fill the gap. In a recent IEEE Security & Privacy column, “Hardware Security in the Era of Emerging Device and System Technologies,” Associate The post Hardware Security for Emerging Technologies appeared first on IEEE Computer Society.

Deep neural networks will be crucial to future human–machine teams aiming to modernize safety-critical systems. Yet DNNs have at least two key problems: Researchers have proposed many defense schemes to counter many attack vectors, yet none have yet secured DNNs from adversarial examples (AEs). This DNN vulnerability to AEs renders their role in safety-critical systems The post ARLA: Using Reinforcement Learning to Strengthen DNNs appeared first on IEEE Computer Society.

For 50 years, the IEEE Transactions on Software Engineering (TSE) has published influential research on the field of software engineering, and in celebration of its 50 years of excellence, IEEE CS is honoring the journal with a special issue this March. Designed to be both retrospective and forward-looking, the TSE anniversary issue includes reflections from The post IEEE Transactions on Software Engineering (TSE) Celebrates 50 Years of Excellence with Special Issue appeared first on IEEE Computer Society.

As AI applications proliferate across industries and sectors, two key security questions arise: Are these AI applications cyber-secure? Can bad actors exploit them through attacks? A recent article discusses these questions in relation to AI’s Achilles’ heel: adversarial machine learning (AdvML). In “Lights Toward Adversarial Machine Learning: The Achilles’ Heel of Artificial Intelligence,” authors Luca The post AdvML: AI’s Achilles Heel appeared first on IEEE Computer Society.

For all its promised benefits and applications across industries, AI remains neither fully transparent nor explainable. For this and other reasons, AI is challenging us in myriad ways, both in what we must learn and how we must learn it—and it is doing so at warp speed. The Computer article, “Grow Your Artificial Intelligence Competence,” The post Growing Your AI IQ: A Guide to Building AI Competence appeared first on IEEE Computer Society.