While existing underwater image compression (UIC) methods optimize for human perception or basic redundancies, they neglect inter-image correlations and fail to prioritize machine-friendly features essential for automated analysis. This paper introduces a novel -quantized (VQ) codebook-driven framework for machine-centric UIC. We leverage VQ codebooks -- pre-trained as external priors on diverse underwater data -- to unify three critical stages: (1) Machine-friendly feature extraction via contrastive learning with high/low-quality codebooks, enhancing degradation robustness; (2) Compact compression using variable-size codebooks to map discriminative features to entropy-coded indices, enabling ultra-low bitrates (less than 0.04bpp); and (3) Feature refinement at the decoder, restoring semantic fidelity for downstream tasks. In addition, we contribute the first Underwater Visual Question Answering (UVQA) benchmark to holistically evaluate machine perception across object presence, counting, and localization. Extensive experiments demonstrate that our framework significantly outperforms state-of-the-art codecs in machine vision task performance at ultra-low bitrates. The VQ-codebook effectively harnesses inter-image redundancy, combats joint degradation, and delivers compact, analysis-friendly representations, establishing a new paradigm for machine-centric UIC.

Abstract KLEIN is a family of block ciphers whose lightweight features are suitable for resource‐constrained devices. However, the original design of KLEIN does not consider the potential attacks by power analysis methods. This paper presents power analysis attacks against an field‐programmable gate array (FPGA) implementation of KLEIN by the authors of KLEIN. The attacking strategy, attacking point, and complexity of our attacks via power analysis against KLEIN are discussed in detail. Besides, the implementation of the attacks is also described, and the experimental data is given. A lot of attacking experiments are launched by this paper; the best method in our experiment is Correlation Power Analysis (CPA) attack that requires only 4000 random plaintexts and 115 s to reveal the 64‐bit key of KLEIN, with the storage complexity nearly 212 and the success probability of attack nearly 100%. Finally, a defensive countermeasure against our attacks is proposed. Copyright © 2017 John Wiley & Sons, Ltd.