cs.CR · 2026-08-07 · No. 77

Cryptography and Security, 2026-08-07.

3 new papers in cs.CR. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

3 entries
  1. 01

    Hardware Keystores for AI Agent Signing Workflows: A Zero-Trust MCP Enforcement Architecture

    Leo Sambrook, Sampo Sovio

    cs.CR · cs.AI · cs.LG

    AI agents performing cryptographic operations (signing Git commits, authenticating API calls, issuing certificates) currently store private keys in software-accessible locations: plaintext files, environment variables, or container memory. Any process with sufficient read privileges can extract the raw key material. A recent production incident demonstrated the practical severity: private keys were exfiltrated from a widely deployed framework...

    arxiv.org/abs/2608.06130 · PDF

  2. 02

    ABC: Numerical Data Collection under Local Differential Privacy without Prior Knowledge

    Incheol Baek, Hyungbin Kim, Yon Dohn Chung

    cs.CR · cs.AI · cs.LG

    Local Differential Privacy (LDP) provides strong privacy guarantees for collecting numerical data. A fundamental challenge, however, is that existing LDP mechanisms require a predefined data domain, which is often unknown in practice. This lack of prior knowledge creates a critical dilemma for the data collector: if the chosen domain is too narrow, values outside the range are clipped, leading to information loss. Conversely, if the domain is...

    arxiv.org/abs/2608.05737 · PDF

  3. 03

    Enhancing Anomaly Resilience in Research Networks: A Large-Scale Forecasting Benchmark for Dynamic Security Baselining

    Mohammad Arafath Uddin Shariff, Byrav Ramamurthy

    cs.CR · cs.LG · cs.NI

    Research and Education Networks (RENs) serve as critical infrastructure for scientific discovery, yet they face a unique security paradox: their normal traffic patterns which are characterized by massive, bursty "elephant flows" are statistically indistinguishable from volumetric attacks such as DDoS to conventional monitoring systems. This similarity leads to high false-positive rates in anomaly detection, blinding security operators to...

    arxiv.org/abs/2608.05605 · PDF

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