Evaluating Lightweight Block Cipher Payload Encryption for Real-Time CAN Traffic

• URL: http://arxiv.org/abs/2604.11853v1
• Date: Mon, 13 Apr 2026 04:14:52 GMT
• Title: Evaluating Lightweight Block Cipher Payload Encryption for Real-Time CAN Traffic
• Abstract summary: This work seeks to determine whether the use of a block cipher can prevent semantic taxonomy-based reverse engineering.<n>Lightweight payload encryption can reduce passive, observation based inference of CAN signal semantics on resource-constrained hardware.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This study evaluates the feasibility of integrating lightweight block cipher payload encryption into a real-time embedded controller area network (CAN) node using a QT PY ESP32-S2 microcontroller. This work seeks to determine whether the use of a block cipher can prevent semantic taxonomy-based reverse engineering, which infers signal meaning from unencrypted CAN traffic using observation and statistical analysis. CAN payloads are encrypted using a lightweight block cipher and evaluated through experiments that measure timing impact, payload pattern observability, and correlation-based inference. Results indicate that encryption masks constant values and predictable signal patterns while preserving a 100 Hz transmission schedule. These findings suggest that lightweight payload encryption can reduce passive, observation based inference of CAN signal semantics on resource-constrained hardware with limited timing overhead impact.

Related papers

• WISV: Wireless-Informed Semantic Verification for Distributed Speculative Decoding in Device-Edge LLM Inference [56.297697169678095]
  WISV (Wireless-Informed Semantic Verification) is a novel distributed speculative decoding framework.<n>We show that WISV achieves up to a 60.8% increase in accepted length, a 37.3% reduction in interaction rounds, and a 31.4% improvement in end-to-end latency.<n>We validate WISV on a hardware testbed comprising an NVIDIA Jetson AGX Orin and an A40-equipped server.
  arXiv  Detail & Related papers  (2026-04-20T01:29:56Z)
• CANDoSA: A Hardware Performance Counter-Based Intrusion Detection System for DoS Attacks on Automotive CAN bus [45.24207460381396]
  This paper presents a novel Intrusion Detection System (IDS) designed for the Controller Area Network (CAN) environment.<n>A RISC-V-based CAN receiver is simulated using the gem5 simulator, processing CAN frame payloads with AES-128 encryption as FreeRTOS tasks.<n>Results indicate that this approach could significantly improve CAN security and address emerging challenges in automotive cybersecurity.
  arXiv  Detail & Related papers  (2025-07-19T20:09:52Z)
• Reflectance Prediction-based Knowledge Distillation for Robust 3D Object Detection in Compressed Point Clouds [47.62228030835151]
  In existing compression transmission systems, the sender lossily compresses point coordinates and reflectance to generate a transmission code stream.<n>This paper proposes a 3D object detection framework with reflectance prediction-based knowledge distillation (RPKD)<n> Experimental results on the KITTI and DAIR-V2X-V datasets demonstrate that our method can boost detection accuracy for compressed point clouds across multiple code rates.
  arXiv  Detail & Related papers  (2025-05-23T03:52:27Z)
• Post Quantum Migration of Tor [0.40964539027092917]
  This dissertation proposes an overview of the cryptographic schemes used by Tor.<n>It highlights the non-quantum-resistant ones and introduces theoretical performance assessment methods of a local Tor network.
  arXiv  Detail & Related papers  (2025-03-13T10:28:03Z)
• CipherGuard: Compiler-aided Mitigation against Ciphertext Side-channel Attacks [26.849878609957386]
  CipherGuard is a compiler-based mitigation tool to counteract ciphertext side channels with high efficiency and security guarantees.<n>In its most efficient strategy, CipherGuard incurs an average performance overhead of only 1.41X, with a maximum of 1.95X.
  arXiv  Detail & Related papers  (2025-02-19T03:22:36Z)
• Cryptanalysis via Machine Learning Based Information Theoretic Metrics [58.96805474751668]
  We propose two novel applications of machine learning (ML) algorithms to perform cryptanalysis on any cryptosystem.<n>These algorithms can be readily applied in an audit setting to evaluate the robustness of a cryptosystem.<n>We show that our classification model correctly identifies the encryption schemes that are not IND-CPA secure, such as DES, RSA, and AES ECB, with high accuracy.
  arXiv  Detail & Related papers  (2025-01-25T04:53:36Z)
• CryptoFormalEval: Integrating LLMs and Formal Verification for Automated Cryptographic Protocol Vulnerability Detection [41.94295877935867]
  We introduce a benchmark to assess the ability of Large Language Models to autonomously identify vulnerabilities in new cryptographic protocols. We created a dataset of novel, flawed, communication protocols and designed a method to automatically verify the vulnerabilities found by the AI agents.
  arXiv  Detail & Related papers  (2024-11-20T14:16:55Z)
• A Machine Learning-Based Framework for Assessing Cryptographic Indistinguishability of Lightweight Block Ciphers [1.5953412143328967]
  Indistinguishability is a fundamental principle of cryptographic security, crucial for securing data transmitted between Internet of Things (IoT) devices.<n>This research investigates the ability of machine learning (ML) in assessing indistinguishability property in encryption systems.<n>We introduce MIND-Crypt, a novel ML-based framework designed to assess the cryptographic indistinguishability of lightweight block ciphers.
  arXiv  Detail & Related papers  (2024-05-30T04:40:13Z)
• Oblivious Monitoring for Discrete-Time STL via Fully Homomorphic Encryption [3.4764840969876722]
  We propose a protocol for online monitoring that keeps arithmetic data concealed from the server. We build on this protocol to allow operations over encrypted values, e.g., to compute a safety measurement combining distance, velocity, and so forth. Overall, our protocol enables oblivious online monitoring of discrete-time real-valued signals against signal temporal logic (STL) formulas.
  arXiv  Detail & Related papers  (2024-05-27T02:32:16Z)
• A Quantum of QUIC: Dissecting Cryptography with Post-Quantum Insights [2.522402937703098]
  QUIC is a new network protocol standardized in 2021. It was designed to replace the TCP/TLS stack and is based on UDP. This paper presents a detailed evaluation of the impact of cryptography on QUIC performance.
  arXiv  Detail & Related papers  (2024-05-15T11:27:28Z)
• Lightweight Cryptanalysis of IoT Encryption Algorithms : Is Quota Sampling the Answer? [0.0]
  Two well-known lightweight algorithms are SIMON and SIMECK which have been specifically designed for use on resource-constrained IoT devices. It is necessary to test these algorithms for resilience against differential cryptanalysis attacks. In this paper, we introduce Versatile Investigative Sampling Technique for Advanced Cryptanalysis.
  arXiv  Detail & Related papers  (2024-04-12T00:08:39Z)
• CRYPTO-MINE: Cryptanalysis via Mutual Information Neural Estimation [42.481750913003204]
  Mutual Information (MI) is a measure to evaluate the efficiency of cryptosystems. Recent advances in machine learning have enabled progress in estimating MI using neural networks. This work presents a novel application of MI estimation in the field of cryptography.
  arXiv  Detail & Related papers  (2023-09-14T20:30:04Z)
• CryptoSPN: Privacy-preserving Sum-Product Network Inference [84.88362774693914]
  We present a framework for privacy-preserving inference of sum-product networks (SPNs) CryptoSPN achieves highly efficient and accurate inference in the order of seconds for medium-sized SPNs.
  arXiv  Detail & Related papers  (2020-02-03T14:49:18Z)

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.