ANCHOR: A Vision for Secure Persistent Key-Value Stores in Disaggregated Data Centers
- URL: http://arxiv.org/abs/2608.27819v1
- Date: Fri, 28 Aug 2026 01:37:51 GMT
- Title: ANCHOR: A Vision for Secure Persistent Key-Value Stores in Disaggregated Data Centers
- Abstract summary: ANCHOR is a vision for end-to-end integrity and freshness in disaggregated PKVS.<n>This paper presents ANCHOR, a vision for end-to-end integrity and freshness in disaggregated PKVS.
- Score: 5.04954154165985
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Persistent key-value stores (PKVS) are increasingly deployed in disaggregated settings that split compute, memory, and storage across separate server pools. This shift redraws the trust boundary: data that would remain within a single machine is now transported, cached, and rewritten across multiple hosts, expanding exposure to both network attackers and intra-infrastructure adversaries. This paper presents ANCHOR, a vision for end-to-end integrity and freshness in disaggregated PKVS. ANCHOR proposes a two-part semantics-aware architecture: 1) Persistence path: ANCHOR outlines encrypting and authenticating PKVS persistent files and preventing rollback with manifest versioning. 2) Volatile path: ANCHOR treats caches, indexes, and filters as untrusted hints unless accompanied by verifiable provenance, enforced by a TEE-resident policy. Finally, we outline key invariants and discuss enclave-friendly batching and asynchronous I/O to amortize verification without undermining disaggregation's performance and elasticity benefits.
Related papers
- KeyPooling: Measuring Where LLM API Relay Paths Collapse Prompt Cache Isolation [53.952294884822955]
Large language model (LLM) API relays authenticate customers separately but often forward requests through shared provider credentials.<n>We present KeyPooling, a measurement method that traces customer identity through cache lookup and write.<n>We derive a defense contract: every customer must enter a provider-enforced domain.
arXiv Detail & Related papers (2026-08-18T08:12:34Z) - DiSCO: Defending text-to-image generation through distribution-guided contrastive prompt optimization [65.89030524420933]
DiSCO is a zero-shot, strictly black-box defense that operates entirely at the prompt level as a plug-and-play module.<n>We demonstrate that DiSCO consistently enhances the safety of both undefended and defended models.<n>As a black-box, architecture-agnostic module, DiSCO can be readily applied to any text-to-image system.
arXiv Detail & Related papers (2026-08-17T19:13:55Z) - Aborted but Not Forgotten: KV-Cache Retention Breaks Rollback Consistency in Language Agents [5.717981279944186]
Stateful language agents assume a rejected branch can be taken back by clearing it from the application transcript.<n>We show this breaks when the serving session retains key/value ( KV) state across the logical abort.<n>We show that transaction-local cache restoration closes the channel without requiring a global cache flush.
arXiv Detail & Related papers (2026-08-16T21:49:38Z) - SafeCA: Safe Cross-Attention Localization and Regulation for Text-to-Video Jailbreak Defense [77.70598852234149]
Text-to-Video (T2V) generative models are vulnerable to jailbreak attacks in real-world deployment.<n>We propose SafeCA, a feature-level defense mechanism for safe cross-attention localization and regularization.<n> Experimental results show that SafeCA reduces the jailbreak success rate by about 20% on mainstream T2V models.
arXiv Detail & Related papers (2026-08-11T14:01:24Z) - Position Rebinding Cache Reuse: Replay-Free Visual Revisiting for Interleaved Multimodal Reasoning [51.563653495547335]
multimodal reasoning improves visual grounding by revisiting visual evidence during multi-step generation.<n>We propose Position Rebinding Cache Reuse (PRCR), a cache-level framework for replay-free visual revisiting.<n>PRCR achieves replay-level or better performance, improving average accuracy by 5 percent and reducing visual-revisiting by up to tens of thousands of times.
arXiv Detail & Related papers (2026-06-25T05:47:52Z) - Agent-Assisted Side-Channel Attacks on Non-Prefix KV Cache in RAG [17.045113249152234]
We introduce the first end-to-end side-channel attack targeting non- KV cache fusion.<n>SpliceLeak executes a systematic two-phase privacy breach.<n>SpliceDefense effectively flattens the side-channel signal (Delta TTFT 0) with negligible throughput overhead.
arXiv Detail & Related papers (2026-06-20T02:28:28Z) - snaproot: Decentralized File Integrity Verification Using Blockchain-Anchored Cryptographic Hashing [0.0]
We present snaproot, a lightweight system that implements the hash-anchoring paradigm of Haber and Stornetta on the Solana blockchain.<n> snaproot generates a SHA-256 hash of a file and stores it immutably on-chain as a permanent reference record.<n>We present a formal threat model, a security analysis grounded in the second-preimage resistance of SHA-256, and an empirical evaluation on Solana Devnet across file sizes from 1 KB to 500 MB.
arXiv Detail & Related papers (2026-06-09T09:25:49Z) - VA-DAR: A PQC-Ready, Vendor-Agnostic Deterministic Artifact Resolution for Serverless, Enumeration-Resistant Wallet Recovery [1.7429038786735553]
VA-DAR is a keyed-discovery protocol for ACE-GF-based wallets.<n>It supports cross-device recovery using only a user-provided identifier and a single recovery passphrase.
arXiv Detail & Related papers (2026-03-03T07:33:10Z) - RedVisor: Reasoning-Aware Prompt Injection Defense via Zero-Copy KV Cache Reuse [47.85771791033142]
We propose RedVisor, a framework that synthesizes the explainability of detection systems with the seamless integration of prevention strategies.<n>RedVisor is the first approach to leverage fine-grained reasoning paths to simultaneously detect attacks and guide the model's safe response.<n> Experiments demonstrate that RedVisor outperforms state-of-the-art defenses in detection accuracy and throughput while incurring negligible utility loss.
arXiv Detail & Related papers (2026-02-02T08:26:51Z) - Towards Bidirectional Protection in Federated Learning [70.36925233356335]
F2ED-LEARNING offers bidirectional defense against malicious centralized server and Byzantine malicious clients.
F2ED-LEARNING securely aggregates each shard's update and launches FilterL2 on updates from different shards.
evaluation shows that F2ED-LEARNING consistently achieves optimal or close-to-optimal performance.
arXiv Detail & Related papers (2020-10-02T19:37:02Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.