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University of South Florida

Academic institutionnorthamerica · us
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Research library331linked papers
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Selected work

Representative Papers

Lightweight and Resilient Signatures for Cloud-Assisted Embedded IoT Systems

Sep 20, 2024arXiv.org

Resource-constrained embedded IoT devices in cloud-assisted systems face severe key-exposure risks, yet existing forward-secure signature schemes incur prohibitive computational and storage overheads, while cloud-assisted approaches rely on centralized or non-colluding semi-honest server assumptions. Method: We propose a lightweight, high-resilience digital signature framework featuring (i) the novel LRSHA/FLRSHA dual-mechanism with commitment separation to drastically reduce signing cost; (ii) a hardware-assisted distributed server architecture eliminating reliance on trusted central authorities or non-collusion assumptions; and (iii) tight integration of HSM coordination, secret key sharding, lightweight elliptic curves, and AVR assembly-level optimization. Contribution/Results: Our implementation achieves millisecond-scale forward-secure signing on 8-bit AVR microcontrollers, with both keys and signatures compressed to the hundred-byte level. We provide formal security proofs and open-source the implementation, demonstrating cross-platform efficiency and practicality.

2 citationsRead paper

Bayes with No Shame: Admissibility Geometries of Predictive Inference

Mar 05, 2026

This work clarifies the relationships and boundaries among four admissibility criteria in predictive inference—Blackwell risk dominance, anytime-valid supermartingale cones, marginal coverage validity, and Cesàro approximability—and resolves their geometric incompatibility. By integrating Blackwell’s decision theory, nonnegative supermartingales, exchangeable prediction sets, and Cesàro approximation techniques, the paper constructs a unified multi-space constrained analytical framework. Its central contribution is a discriminative theorem establishing that the four classes of admissible procedures are mutually non-nested, revealing their fundamental incommensurability. The study further characterizes the optimality certificates and necessary and sufficient conditions for each criterion, elucidating the divergent roles of martingale consistency across these frameworks and thereby laying a geometric foundation for predictive inference.

1 citationsRead paper

A New Look at Bayesian Testing

Feb 11, 2026

This study addresses the theoretical gap between classical hypothesis testing with fixed significance levels and Bayesian methods, particularly in light of the Lindley paradox. By leveraging moderate deviation theory, the authors develop a unified Bayesian framework for hypothesis testing. Through Bayesian risk analysis and asymptotic expansions, they show that the optimal test threshold operates on the scale of √(log n / n), naturally yielding Jeffreys’ threshold, the BIC penalty term, and the Chernoff–Stein error exponent. This framework not only resolves the Lindley paradox but also extends Rubin’s (1965) program to modern settings such as high-dimensional sparse inference, goodness-of-fit testing, and model selection. Moreover, it establishes the superiority of Bayesian procedures over classical Neyman–Pearson tests in terms of statistical risk.

1 citationsRead paper
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