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arXiv:2610.41032v1 Announce Type: new Abstract: The interoperability between permissioned and public blockchains is hampered by asymmetric privacy, trust, and governance assumptions. We propose a coordination architecture that decouples cross-domain trust management and privacy enforcement from underlying blockchain protocols, requiring no protocol-level modifications. The framework integrates cryptographic unlinkability mechanisms with incentive-compatible relay selection, combining stake-weighted participation and temporally accumulated reputation to align economic commitment with sustained correctness. We formalize the adversarial model and derive security and privacy properties for cross-domain coordination, demonstrating robustness against Sybil infiltration, collusion, and strategic stake concentration. Simulation-based analysis characterizes key design trade-offs between quorum thresholds, reputation memory, and anonymity parameters, indicating that privacy-preserving coordination can be achieved without degrading responsiveness or incentive stability when parameters are properly tuned.

arXiv:2610.41055v1 Announce Type: cross Abstract: Federated reinforcement learning supports cooperative vehicular routing without centralizing trajectory data, but model updates may reveal private information and incur communication overhead over intermittent vehicle-to-infrastructure links, particularly when post-quantum authentication is required. We study correlated private quantization, using complementary shared randomness between paired vehicles to reduce aggregation mean squared error while preserving the marginal parameter-level local differential privacy and one-bit communication cost of independent quantization. A tunable extension mixes shared and independent randomness to bound privacy leakage given paired outputs and shared-randomness side information. For this extension, R\'enyi differential privacy accounting establishes vector-level local differential privacy for one model upload even when pairings are revealed. Under matched vector-level privacy and identical local and global parameters, the extension yields 16.5% lower analytical aggregation mean squared error than independent quantization. We evaluate cooperative routing by coupling traffic simulation with packet…

arXiv:2610.41579v1 Announce Type: cross Abstract: Coordinated high-altitude platform station (HAPS) networks need to authenticate group responses and protect private data under shared power constraints. This paper studies joint group physical-layer authentication (PLA) and confidential beamforming using a fresh secret tag superimposed on private data. For received attacks independent of the current tag, we derive exact finite-block expressions for false acceptance and legitimate rejection. These expressions translate authentication error targets into a required tag signal-to-interference-plus-noise ratio (SINR). We establish a nonzero asymptotic tag-energy floor and analyze residual frequency offset and peak-power restrictions. The legitimate receiver removes the tag by orthogonal projection, which discards one temporal dimension. For colluding eavesdroppers, we identify the spatial coverage condition under which artificial noise (AN) keeps their SINR bounded as data and AN powers increase together. We jointly optimize the private beams, tag beam, and AN covariance to minimize transmit power under authentication, secrecy, and per-HAPS power constraints. The method combines semidefi…

arXiv:2610.41888v1 Announce Type: cross Abstract: Centralized exchanges (CEXs) are key gateways between traditional finance and digital asset markets, yet identifying their blockchain addresses remains challenging. Existing approaches often rely on opaque attribution labels or treat exchanges as secondary classification targets, leaving generalization to unseen exchanges insufficiently examined. This study develops a classification framework using Proof-of-Reserves (PoR) disclosures, with 3,033,857 Ethereum addresses from 15 CEXs and five Non-CEX categories. We derive 58 on-chain behavioral features and evaluate LightGBM against logistic regression (LR) under a leave-one-exchange-out protocol. Across five lookback windows (30-730 days), LightGBM consistently outperformed LR, with macro PR-AUC increasing from 0.6611 to 0.9594 using the selected 17 features, compared with 0.7697 for LR at 730 days. Robustness checks showed comparable performance when feature selection and hyperparameter optimization were repeated across splits and held-out exchanges, while exchange-balanced reweighting improved macro PR-AUC. SHAP analysis and feature-group ablation identified gas behavior, ERC-20 tok…

Article URL: https://www.science.org/content/article/bones-may-release-proteins-slow-aging-and-extend-life-span Comments URL: https://news.ycombinator.com/item?id=50331957 Points: 7 # Comments: 0

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