Quantum computing does present a big threat to classic cryptography and hence endangers the security of Internet of Things devices. This paper is therefore concerned with proposing a Quantum-Resistant Homomorphic Encryption (QRHE) system tailored for Internet of Things (IoT) environments. The main view of this QRHE key system is basically protection against the quantum threat in the processing of information within Internet of Things network traffic. Aside from this, the system further allows the processing of data on encrypted information without prior decryption, which guarantees the confidentiality and integrity of the data processed. The lattice-based cryptography used in the system is based on the Learning With Errors (LWE) problem, which has already shown strength against classical and quantum attacks. In this paper, homomorphic encryption algorithm was introduced that allows both addition and multiplication between ciphertexts for the assurance of privacy during secure data aggregation and analysis. The experimental results demonstrated that even after several homomorphic operations, the proposed system maintained high accuracy of %98, proving its effectiveness in preserving data confidentiality and integrity. Although the computational cost for this proposed system was a little more compared to traditional methods, it still gave an all-rounded security solution suitable for Internet of Things applications in the quantum computing era.
Quantum computing does present a big threat to classic cryptography and hence endangers the security of Internet of Things devices. This paper is therefore concerned with proposing a Quantum-Resistant Homomorphic Encryption (QRHE) system tailored for Internet of Things (IoT) environments. The main view of this QRHE key system is basically protection against the quantum threat in the processing of information within Internet of Things network traffic. Aside from this, the system further allows the processing of data on encrypted information without prior decryption, which guarantees the confidentiality and integrity of the data processed. The lattice-based cryptography used in the system is based on the Learning With Errors (LWE) problem, which has already shown strength against classical and quantum attacks. In this paper, homomorphic encryption algorithm was introduced that allows both addition and multiplication between ciphertexts for the assurance of privacy during secure data aggregation and analysis. The experimental results demonstrated that even after several homomorphic operations, the proposed system maintained high accuracy of %98, proving its effectiveness in preserving data confidentiality and integrity. Although the computational cost for this proposed system was a little more compared to traditional methods, it still gave an all-rounded security solution suitable for Internet of Things applications in the quantum computing era.
Integrating the Internet of Things (IoT) in smart grids has revolutionized the energy sector, enabling real-time data collection and efficient energy distribution. However, this integration also introduces significant security challenges, particularly data encryption. Traditional encryption algorithms used in IoT are vulnerable to various attacks, and the advent of quantum computing exacerbates these vulnerabilities. To address the above challenges, this paper proposes a novel encryption mechanism, the Quantum-Resistant Hybrid Encryption for IoT (QRHE-IoT), designed to enhance the security of communications in IoT-enabled smart grids. QRHE-IoT combines the strengths of symmetric and asymmetric encryption algorithms and incorporates quantum-resistant algorithms to provide robust security. This paper explains the QRHE-IoT mechanism, its theoretical basis, and how it addresses the security challenges in smart grid communications. It also presents the results of tests conducted to evaluate the effectiveness of QRHE-IoT in a simulated smart grid environment. The proposed QRHE-IoT mechanism presents a promising solution to these challenges, offering robust security for smart grid communications in the face of emerging threats, including quantum computing.
In an era where securing Internet of Things (IoT) devices within Metaverse environments is increasingly critical, existing frameworks often lack robust, quantum-resistant protection suitable for resource-constrained devices. This study aims to develop a comprehensive quantum-resistant security framework designed for IoT-enabled Metaverse applications. Our multilayered architecture incorporates Ideal Coset Lattice Cryptography (ICLC) and a Hypercomplex Multivariate Encryption Scheme (HMES) across the Device, Network, and Metaverse layers. ICLC provides lightweight, quantum-resistant encryption for devices with limited computational resources, while HMES enhances security through complex algebraic structures resistant to quantum attacks. We implement a Zero-Knowledge Proof Authentication mechanism over Hypercomplex Algebras (ZKPHA) to authenticate devices without exposing private keys. An edge computing strategy that employs convex optimization minimizes latency and computational load, ensuring scalability and efficiency. Simulations over a 260-minute period compared our framework with six state-of-the-art methods under various conditions. The results show that our framework reduces the rate of successful cyberattacks on encrypted data to 0.15%, achieves encryption and decryption times of 2.2 milliseconds per operation, and maintains 98.5% system availability during attacks.
Abstract With the emergence of quantum computing, traditional cryptographic algorithms face the threat of being compromised, necessitating the development of quantum-resistant alternatives. The Internet of Things (IoT) paradigm presents unique security challenges due to its vast scale and resource-constrained devices. This research aims to address these challenges by proposing a novel quantum-resistant cryptographic algorithm QuantIoT specifically designed for securing IoT devices. The research begins by evaluating the vulnerabilities of existing cryptographic algorithms against quantum attacks and identifying the need for post-quantum solutions in the IoT context. Various families of post quantum cryptographic algorithms, including lattice based and hash based schemes, are examined to assess their suitability for securing IoT devices. Based on the analysis, a novel quantum-resistant cryptographic algorithm tailored for IoT devices is proposed. The algorithm takes into account the limited computational capabilities, power constraints, and communication requirements of IoT devices while offering strong defence against both conventional and quantum threats. The proposed algorithm is evaluated through simulations and practical experiments on a representative IoT platform. Performance metrics, including computation time, memory usage, and communication overhead, are measured and compared against traditional cryptographic algorithms. The results show that the suggested quantum-resistant technique for protecting IoT devices is workable and effective. This research contributes to the growing body of knowledge on post-quantum cryptography and provides valuable insights for the design and implementation of secure IoT systems in the face of quantum threats.
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 proliferation of Internet of Things (IoT) devices has introduced significant security challenges, particularly with the looming threat posed by quantum computing to classical cryptographic algorithms. This paper explores the integration of quantum-resistant cryptographic techniques to secure IoT ecosystems against future quantum attacks. We analyze the vulnerabilities inherent in traditional cryptographic approaches and discuss the implementation feasibility of post-quantum cryptography (PQC) in resource-constrained IoT devices. The study further highlights key PQC algorithms suitable for IoT and evaluates their performance impact. A comparative analysis graph of classical versus quantum-resistant algorithms in IoT environments is presented. This work aims to provide insights and recommendations for adopting quantum-resistant solutions to future-proof IoT security.
The resource limitations of IoT nodes and the vulnerability of wireless channels to cyberattacks and snooping, the quick spread of Internet of Things (IoT) devices in wireless surroundings has created serious challenges to data security and privacy. The development of quantum computing, which can meritoriously crack classical encryption, is posing a growing threat to recognized cryptographic techniques like RSA and ECC. By applying concepts from quantum mechanics like predicament cloning, quantum cryptography, in particular Quantum Key Distribution (QKD), provides tentatively unbreakable security. In order to integrate lightweight quantum key exchange with traditional IoT communication protocols, this paper proposes a comprehensive Quantum Cryptography Framework (QCF) exactly designed for Wireless IoT networks. The framework is made to preserve energy efficiency while certifying forward secrecy, confidentiality, integrity, and authentication. A performance evaluation in terms of latency, throughput, and resistance to quantum attacks supports our discussion of the architecture, working mechanism, and implementation deliberations. The findings show that, when compared to traditional encryption methods, the suggested QCF greatly improves the security of wireless IoT systems, certifying resilience against oppositional models of the future.