Side Channel Analysis (SCA) presents a clear threat to privacy and security in modern computing systems. The vast majority of communications are secured through cryptographic algorithms. These algorithms are often provably-secure from a cryptographical perspective, but their implementation on real hardware introduces vulnerabilities. Adversaries can exploit these vulnerabilities to conduct SCA and recover confidential information, such as secret keys or internal states. The threat of SCA has greatly increased as machine learning, and in particular deep learning, enhanced attacks become more common. In this work, we will examine the latest state-of-the-art deep learning techniques for side channel analysis, the theory behind them, and how they are conducted. Our focus will be on profiling attacks using deep learning techniques, but we will also examine some new and emerging methodologies enhanced by deep learning techniques, such as non-profiled attacks, artificial trace generation, and others. Finally, different deep learning enhanced SCA schemes attempted against the ANSSI SCA Database (ASCAD) and their relative performance will be evaluated and compared. This will lead to new research directions to secure cryptographic implementations against the latest SCA attacks.

The field of computer vision has rapidly evolved in recent years and achieved results that seemed like science fiction a few years back. These breakthroughs have many causes -- building better, more accessible compute resources, but also the fact that they are the closest thing we have to Open Source Data Science (OSDS). Revealing the source code to the community unlocks the "wisdom of the crowd" and enables innovation and problem-solving at scale. One of the most popular OS projects in computer vision is YOLO (You Only Look Once). YOLO is an efficient real-time object detection algorithm, first described in the seminal 2015 paper by Joseph Redmon et al.

The promise of immersive, sharp and dense worlds to explore feels real when roaming the streets of Yokohama in "Yakuza: Like a Dragon." The characters and city explode in color and detail in ways I had never seen in past "Yakuza" titles and locations. The series struggled to hit both high-resolution, high framerate gameplay in the last console generation. That is now achievable on both Series X and S; both versions feature "performance" and "fidelity" modes, offering 60-frames gameplay under the "performance" option. There's parity in the "Yakuza" experiences not found in "Valhalla," and that's some comfort when comparing the X and S.