Exploring and Exploiting Synchrony Limitations of Time-Triggered Network-Agnostic Guardians

• URL: http://arxiv.org/abs/2606.27819v1
• Date: Fri, 26 Jun 2026 08:00:44 GMT
• Title: Exploring and Exploiting Synchrony Limitations of Time-Triggered Network-Agnostic Guardians
• Abstract summary: Time-triggered communication protocols rely on trusted components known as guardians to enforce network schedules.<n>A malicious node can exploit this dependency to launch timing attacks against its guardian.<n>We introduce a timing attack that leverages the unavoidably imperfect clock synchrony to cause undetected de-synchronization of the guardian.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Time-triggered communication protocols rely on trusted components known as guardians to enforce adherence to predetermined network schedules. Network-agnostic guardians offer an efficient and scalable distributed solution with reduced implementation cost and complexity compared to network-aware alternatives. However, this efficiency is based on the guardian's dependence on the controlled node for clock synchronization, which introduces a vulnerability: a malicious node can exploit this dependency to launch timing attacks against its guardian and eventually interfere with messages from other nodes on the network. In this paper, we establish a theoretical lower bound on the attainable clock synchronization precision between a node and its network-agnostic guardian. Building on this result, we introduce a timing attack that leverages the unavoidably imperfect clock synchrony to cause controlled and undetected de-synchronization of the guardian. The attack enables a malicious node to cause collisions with targeted critical network messages. We evaluate the effectiveness of the attack using a FlexRay field bus network model implemented in the OMNeT++ simulation framework. Our results show that the attack is able to remain undetected with 100% success and disrupts the transmission of the critical messages of the target node by causing collisions with them with 100% success.

Related papers

• Link-Free Multi-Node Timing Synchronization for Scalable Quantum Networking [4.10690294530525]
  We demonstrate link-free synchronization of quantum network nodes using miniature rubidium atomic clocks and computational post-processing.<n>We observe Hong-Ou-Mandel interference across spatially separated nodes with visibility exceeding 70%, statistically equivalent to that obtained using dedicated White Rabbit timing links.
  arXiv  Detail & Related papers  (2026-06-12T03:51:55Z)
• TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning [60.68349524623048]
  Decompositional jailbreaks pose a critical threat to large language models.<n>We present TwinGate, a stateful dual-encoder defense framework.<n>We construct a comprehensive dataset of over 3.62 million instructions spanning 8,600 distinct malicious intents.
  arXiv  Detail & Related papers  (2026-04-30T13:44:01Z)
• HadAgent: Harness-Aware Decentralized Agentic AI Serving with Proof-of-Inference Blockchain Consensus [4.693243537924961]
  We present HadAgent, a decentralized agentic AI serving system that replaces hash-based mining with Proof-of-Inference (PoI)<n>HadAgent organizes validated records into a three-lane block body with dedicated DATA, MODEL, and PROOF channels.<n>Experiments on a prototype implementation demonstrate 100% detection rate and 0% false positive rate for tampered records.
  arXiv  Detail & Related papers  (2026-04-15T14:46:29Z)
• HALO: Semantic-Aware Distributed LLM Inference in Lossy Edge Network [50.33808558714122]
  Large language models' (LLMs) inference at the edge can facilitate prompt service responsiveness while protecting user privacy.<n>We propose HALO, a novel framework that can boost the distributed LLM inference in lossy edge network.<n> Experimental results from a Raspberry Pi cluster demonstrate that HALO achieves a 3.41x end-to-end speedup for LLaMA-series LLMs under unreliable network conditions.
  arXiv  Detail & Related papers  (2026-01-16T07:37:23Z)
• Multi-Agent-Driven Cognitive Secure Communications in Satellite-Terrestrial Networks [58.70163955407538]
  Malicious eavesdroppers pose a serious threat to private information via satellite-terrestrial networks (STNs)<n>We propose a cognitive secure communication framework driven by multiple agents that coordinates spectrum scheduling and protection through real-time sensing.<n>We exploit generative adversarial networks to produce adversarial matrices, and employ learning-aided power control to set real and adversarial signal powers for protection layer.
  arXiv  Detail & Related papers  (2026-01-06T10:30:41Z)
• Tunable Asymmetric Delay Attack in Quantum Clock Synchronization [6.742670890660517]
  Current attack strategies rely on static delays, limiting their ability to target application-specific stability requirements.<n>We propose a tunable asymmetric delay attack (T-ADA) that dynamically controls delay parameters to induce manipulate synchronization accuracy.
  arXiv  Detail & Related papers  (2025-10-24T02:30:01Z)
• Privacy Preserving Semi-Decentralized Mean Estimation over Intermittently-Connected Networks [59.43433767253956]
  We consider the problem of privately estimating the mean of vectors distributed across different nodes of an unreliable wireless network. In a semi-decentralized setup, nodes can collaborate with their neighbors to compute a local consensus, which they relay to a central server. We study the tradeoff between collaborative relaying and privacy leakage due to the data sharing among nodes.
  arXiv  Detail & Related papers  (2024-06-06T06:12:15Z)
• Graph Agent Network: Empowering Nodes with Inference Capabilities for Adversarial Resilience [50.460555688927826]
  We propose the Graph Agent Network (GAgN) to address the vulnerabilities of graph neural networks (GNNs)<n>GAgN is a graph-structured agent network in which each node is designed as an 1-hop-view agent.<n>Agents' limited view prevents malicious messages from propagating globally in GAgN, thereby resisting global-optimization-based secondary attacks.
  arXiv  Detail & Related papers  (2023-06-12T07:27:31Z)
• LGTBIDS: Layer-wise Graph Theory Based Intrusion Detection System in Beyond 5G [9.63617966257402]
  Intrusion detection signifies a central approach to ensuring the security of the communication network. A Layerwise Graph Theory-Based Intrusion Detection System (LGTBIDS) algorithm is designed to detect the attacked node. Results validate the better performance, low time computations, and low complexity.
  arXiv  Detail & Related papers  (2022-10-06T05:32:03Z)
• AN-GCN: An Anonymous Graph Convolutional Network Defense Against Edge-Perturbing Attack [53.06334363586119]
  Recent studies have revealed the vulnerability of graph convolutional networks (GCNs) to edge-perturbing attacks. We first generalize the formulation of edge-perturbing attacks and strictly prove the vulnerability of GCNs to such attacks in node classification tasks. Following this, an anonymous graph convolutional network, named AN-GCN, is proposed to counter edge-perturbing attacks.
  arXiv  Detail & Related papers  (2020-05-06T08:15:24Z)

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.