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PoSME: Proof of Sequential Memory Execution via Latency-Bound Pointer Chasing with Causal Hash Binding

arXiv Security Archived Apr 20, 2026 ✓ Full text saved

arXiv:2604.15751v1 Announce Type: new Abstract: We introduce PoSME (Proof of Sequential Memory Execution), a cryptographic primitive that enforces sustained sequential computation via latency-bound pointer chasing over a mutable arena. Each step reads data-dependent addresses, writes a block whose value and causal hash are mutually dependent (symbiotic binding), and chains the result into a global transcript. This yields three properties: (1) strict linear sequential memory-step enforcement, (2)

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    Computer Science > Cryptography and Security [Submitted on 17 Apr 2026] PoSME: Proof of Sequential Memory Execution via Latency-Bound Pointer Chasing with Causal Hash Binding David L. Condrey We introduce PoSME (Proof of Sequential Memory Execution), a cryptographic primitive that enforces sustained sequential computation via latency-bound pointer chasing over a mutable arena. Each step reads data-dependent addresses, writes a block whose value and causal hash are mutually dependent (symbiotic binding), and chains the result into a global transcript. This yields three properties: (1) strict linear sequential memory-step enforcement, (2) high time-memory trade-off resistance (a tenfold penalty at a write density of 4, with a formal space-time lower bound that scales quadratically with the number of steps), and (3) a tight ASIC advantage bound by DRAM random-access latency rather than bandwidth. Benchmarks across 17 CPU platforms and 4 GPU architectures demonstrate that hash computation is under 3.5 percent of step cost and GPU hardware is 14 to 19 times slower than a consumer CPU. POSME requires no trusted setup and provides a foundation for verifiable delay, authorship attestation, and Sybil resistance. Comments: 10 pages, 6 algorithms, 9 tables, 2 figures Subjects: Cryptography and Security (cs.CR); Distributed, Parallel, and Cluster Computing (cs.DC) MSC classes: 94A60, 68Q17, 68Q25, 05C20 ACM classes: E.3; F.2.2; B.3.3; D.4.6 Cite as: arXiv:2604.15751 [cs.CR]   (or arXiv:2604.15751v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2604.15751 Focus to learn more Submission history From: David Condrey [view email] [v1] Fri, 17 Apr 2026 06:53:32 UTC (41 KB) Access Paper: HTML (experimental) view license Ancillary files (details): README.md fold_bench.py mixing_analysis.py posme-bench-colab.ipynb posme-bench.rs (5 additional files not shown) Current browse context: cs.CR < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.DC References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Apr 20, 2026
    Archived
    Apr 20, 2026
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