Autonomous vehicles (AV) have as one of their characteristics the constant exchange of data with other vehicles, radio base stations, pedestrians and infrastructure. Despite this data exchange using the most modern security techniques, vehicles have been the target of constant cyber-attacks. Emerging technologies such as quantum computing have been tested to minimize these attacks. Particularly, this work investigates the possibility of using post-quantum computing techniques in IoT (Internet of Things) devices, more specifically in AVs. Considering the functionalities of a vehicle nowadays, it is possible to say that a vehicle is composed of a set of IoT devices. Therefore, in this paper, we propose a post-quantum secure method to be used in IoT devices for data exchange between AVs and a 5G base station. In this method, the post-quantum algorithm NTRU is implemented in an edge computing IoT architecture between the source of the CVs data and the edge layer, which is a vulnerable spot for quantum-attacks. We simulated the implementation of the algorithm in a case study and monitored how the algorithm performed. The proposed methodology was capable of providing secure communication between IoT and edge layer. However, the message length and parameters from the algorithm can slow down the communication.
Autonomous vehicles (AV) have as one of their characteristics the constant exchange of data with other vehicles, radio base stations, pedestrians and infrastructure. Despite this data exchange using the most modern security techniques, vehicles have been the target of constant cyber-attacks. Emerging technologies such as quantum computing have been tested to minimize these attacks. Particularly, this work investigates the possibility of using post-quantum computing techniques in IoT (Internet of Things) devices, more specifically in AVs. Considering the functionalities of a vehicle nowadays, it is possible to say that a vehicle is composed of a set of IoT devices. Therefore, in this paper, we propose a post-quantum secure method to be used in IoT devices for data exchange between AVs and a 5G base station. In this method, the post-quantum algorithm NTRU is implemented in an edge computing IoT architecture between the source of the CVs data and the edge layer, which is a vulnerable spot for quantum-attacks. We simulated the implementation of the algorithm in a case study and monitored how the algorithm performed. The proposed methodology was capable of providing secure communication between IoT and edge layer. However, the message length and parameters from the algorithm can slow down the communication.
The Internet of Things (IoT) has revolutionized the way devices communicate and interact, enabling seamless integration into various aspects of daily life by billions of connected devices equipped with small, embedded controllers that monitor and manage our increasingly interconnected world. The swift growth of IoT devices has led to significant concerns about data security and privacy. Traditional cryptographic algorithms, usually lightweight cryptography, are effective against classical computing threats. However, they are vulnerable to attacks from emerging quantum computing technologies, which can quickly solve the mathematically hard problems used in classical cryptography. Post-Quantum Cryptography (PQC) offers promising solution by providing cryptographic primitives resistant to quantum attacks. This chapter addresses challenges posed by resource constrained IoT devices, like limited processing power and memory. It also explores the integration of PQC algorithms suitable for IoT environments, considering factors like computational efficiency and resistance to quantum attacks.
The rise of autonomous vehicles (AVs) has led to an increased reliance on vehicle-to-vehicle (V2V) communication networks to ensure real-time information sharing, situational awareness, and cooperative decision-making. However, the integration of quantum computing into cybersecurity threatens the cryptographic foundations upon which current V2V communication protocols rely. As quantum computers grow closer to practical implementation, traditional public-key encryption schemes—such as RSA and ECC—are rendered vulnerable to attacks from quantum algorithms like Shor’s and Grover’s. This review explores the necessity of adopting quantum-resistant cryptographic protocols to secure V2V communication frameworks. The study critically examines post-quantum cryptographic algorithms, including lattice-based, hash-based, code-based, multivariate polynomial, and isogeny-based schemes, with a focus on their applicability to latency-sensitive and resource-constrained vehicular environments. Furthermore, the paper evaluates the performance, scalability, and implementation challenges of integrating these cryptographic primitives into real-time autonomous systems. Case studies of pilot implementations and emerging research are reviewed to highlight the practicality of these protocols in vehicular edge computing and 5G-enabled automotive networks. The paper concludes by proposing a forward-looking roadmap for standardization and integration of quantum-resilient cryptography in intelligent transportation systems (ITS), ensuring long-term data integrity, authentication, and privacy across V2V infrastructures.
A recent trend in the IT world is the term Internet of Things (IoT). As more and more devices get connected to the internet, and with companies trying to lower production costs in order to stay competitive, security can easily be neglected. In this report traditional Transport Layer Security (TLS) implementations and post-quantum based TLS were evaluated and performance measurements were conducted. The initial attempt was to run post-quantum secure algorithms on an IoT device in order to see if an IoT device theoretically would be able to withstand an attack from a quantum computer. Due to memory constraints it was not possible to run the modified version of the cryptography library, PolarSSL, on the intended IoT device. For that reason we switched to another platform, namely a Raspberry Pi. The measurements were conducted on that platform and in-depth analysis was performed to determine if current implementations of post-quantum algorithms can be suitable for IoT devices or not. The conclusion was that post-quantum algorithms are more time-consuming than traditional algorithms used today. One of the experiments in this report shows that using a post-quantum algorithm for the key exchange is 2.5 times slower and needs 10 times as much RAM memory than a traditional solution with the same security level. There is therefore no apparent need to start using post-quantum algorithms today in terms of security level, when considering the duration and RAM usage for the key exchange. With time and optimization some of the algorithms evaluated in this report, or similar algorithms, could be good candidates the day large quantum computers are produced.
The Internet of Things (IoT) has grown rapidly, transforming various aspects of daily life into intelligent systems capable of collecting and exchanging data in real time. At the same time, advances in quantum computing have given rise to powerful quantum computers capable of processing complex tasks at unprecedented speed. This disparity between the limited resources of IoT devices and the capabilities of quantum computers poses significant security challenges. Quantum computers introduce new vulnerabilities that threaten IoT systems, particularly in critical applications such as connected healthcare, industrial networks, smart infrastructure, and secure embedded systems. This study reviews the existing literature on post-quantum cryptography (PQC) applied to IoT devices. It analyzes the characteristics and security requirements of IoT environments, current security technologies, and unresolved issues. It highlights the growing threat of post-quantum attacks and the need to adapt security strategies. Finally, the study explores post-quantum code-based cryptosystems as solutions to enhance the security of resource-constrained IoT applications and ensure their resilience against future challenges.
The emergence of quantum computing seriously threatens the security of legacy cryptographic protocols in consumer electronics devices based on the Internet of Things (IoT). These are essential components of mission-critical infrastructures, such as industrial control systems, smart grids, and healthcare. In particular, this work examines how to strengthen the resistance of the IoT to classical and quantum-based cyberattacks by combining deep learning methods with post-quantum cryptography (PQC). To protect key exchange, encryption, and authentication processes in IoT-consumer devices, we will continue to use quantum-resistant cryptographic algorithms, including lattice-based, hash-based, and code-based cryptography. To provide real-time anomaly detection and response capabilities, we suggest a hybrid security framework combining PQC with deep learning-based intrusion detection systems. Our methodology ensures secure communications and data exchanges linked to quantum attacks in the future within IoT systems while leveraging continuous learning over time to allow Intrusion Detection System (IDS) models to adapt to new attack vectors. We suggest optimized algorithms for PQC solutions that are lightweight and suitable for deployment in edge computing nodes and Internet of Things devices, considering the resource-constrained IoT situations where PQC implementation would be difficult. Through comparative studies and simulations, we demonstrate how our integrated PQC-deep learning framework offers an improved IoT security solution that could safeguard vital systems in a world powered by quantum technology. The results shows the key generation time which is 12.5ms, encryption/decryption time 25.3ms, latency 18.7ms, throughput 5000 operations/sec and energy consumption 2.4mJ.
The rapid integration of Internet of Things (IoT) technologies in Autonomous Vehicles (AVs) has significantly expanded the attack surface of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication systems.These networks exchange large volume of safety-critical data in realtime, which increases their exposure to attacks like message tampering, identity spoofing, and coordinated injection.Traditional cryptographic systems become more suspectable to emerging quantum computing threats, whereas the existing intrusion detection systems suffer from high latency, static encryption, and increased energy consumption due to frequent vehicular movement.These challenges restrict the ability of current systems to guarantee secure, real-time, energy-efficient, and sustainable communication for next-generation AVs.To address these challenges, this study introduced a novel Quantum-Enhanced Lightweight Protocol (QELP) that combines hybrid quantum-classical security mechanisms with adaptive encryption orchestration to improve security, real-time performance, and sustainable operation in IoT-enabled autonomous vehicle sensor networks.QELP combines BB84based Quantum Key Distribution (QKD) and lattice-based post-quantum cryptography (Kyber+) to establish quantum-resilient session keys.The context-aware encryption method dynamically adjusts the encryption intensity and key refresh rate based on residual energy, traffic density, anomaly score, and vehicular mobility to balance security strength and computational overhead.The model includes multi-layer error and attack detection techniques, including quantum-based intrusion alerts, digital signature validation, and behavioural deviation checks.The VeReMi and CARLA-NS3 datasets are employed for message-based V2X attack validation and to assess the networklevel behavior under real-time traffic scenarios.The performance is evaluated by simulations using Python (Qiskit) for quantum layers and NS3 for AV networks.The simulation results outperform with 98.76% attack detection rate, 0.015 false alarm rate, 13.7ms latency, 12.2% energy depletion score, 94.6% security risk score reduction towards a stronger quantumresilient defense and an encryption throughput improvement to 96.8%, handling encrypted data at high speed.The findings confirm that QELP provides a scalable, quantum-resilient, and energy-aware security architecture for next-generation autonomous vehicular communication systems.