High-profile speech videos are prime targets for falsification, owing to their accessibility and influence. This work proposes VeriLight, a low-overhead and unobtrusive system for protecting speech videos from visual manipulations of speaker identity and lip and facial motion. Unlike the predominant purely digital falsification detection methods, VeriLight creates dynamic physical signatures at the event site and embeds them into all video recordings via imperceptible modulated light. These physical signatures encode semantically-meaningful features unique to the speech event, including the speaker's identity and facial motion, and are cryptographically-secured to prevent spoofing. The signatures can be extracted from any video downstream and validated against the portrayed speech content to check its integrity. Key elements of VeriLight include (1) a framework for generating extremely compact (i.e., 150-bit), pose-invariant speech video features, based on locality-sensitive hashing; and (2) an optical modulation scheme that embeds $>$200 bps into video while remaining imperceptible both in video and live. Experiments on extensive video datasets show VeriLight achieves AUCs $\geq$ 0.99 and a true positive rate of 100% in detecting falsified videos. Further, VeriLight is highly robust across recording conditions, video post-processing techniques, and white-box adversarial attacks on its feature extraction methods. A demonstration of VeriLight is available at https://mobilex.cs.columbia.edu/verilight.

Byzantine fault tolerant (BFT) consensus protocols are becoming an appealing solution to blockchains. As most blockchain systems are deployed on Wide Area Networks (WANs), with each node acting on behalf of its entity, partially synchronous BFT protocols that rely on network synchrony to elect a single leader can be ill-suited. In contrast, asynchronous protocols have no such timing assumptions. Existing asynchronous protocols confront challenges in terms of both flexibility and performance.

Polar code has been proven to achieve the symmetric capacity of memoryless channels. However, the successive cancellation decoding algorithm is inherent serial in nature, which will lead to high latency and low throughput. In order to obtain high throughput, we design a deeply pipelined polar decoder and optimize the processing elements and storage structure. We also propose an improved fixed‐point nonuniform quantization scheme, and it is close to the floating‐point performance. Two‐level control strategy is presented to simplify the controller. In addition, we adopt FIFO structure to implement the α _memory and β _memory and propose the 348‐stage pipeline decoder.