In quantum communication era, where quantum computing capabilities can be used in cyber attacks, it is important that Internet of Things (IoT) devices, which have limited energy and computing power compared to central devices, can communicate securely with control devices. In our study, we performed a simulation based on two scenarios for quantum key distribution (QKD) with the absence and presence of attack between server and IoT device. Security of communication for IoT device is achieved by detecting the attacks on QKD process with a machine learning (ML) algorithm. Unlike traditional cyber security methods, the ML algorithm helped to detect attacks with 100% probability without interrupting the flow of information between the server and the IoT device. The proposed simulation can also be generalised for being suitable for other applications where quantum communications are used.
In quantum communication era, where quantum computing capabilities can be used in cyber attacks, it is important that Internet of Things (IoT) devices, which have limited energy and computing power compared to central devices, can communicate securely with control devices. In our study, we performed a simulation based on two scenarios for quantum key distribution (QKD) with the absence and presence of attack between server and IoT device. Security of communication for IoT device is achieved by detecting the attacks on QKD process with a machine learning (ML) algorithm. Unlike traditional cyber security methods, the ML algorithm helped to detect attacks with 100% probability without interrupting the flow of information between the server and the IoT device. The proposed simulation can also be generalised for being suitable for other applications where quantum communications are used.
Internet of Things (IoT) deployments face significant security challenges due to the limited energy and computational power of IoT devices. These challenges are more serious in the quantum communications era, where certain attackers might have quantum computing capabilities, which renders IoT devices more vulnerable. This paper addresses the problem of IoT security by investigating quantum key distribution (QKD) in beyond 5G networks. An algorithm for detecting an attacker between a transmitter and receiver is proposed, with the side effect of interrupting the QKD process while detecting the attacker. Afterwards, Artificial neural network (ANN) and deep learning (DL) techniques are proposed in order to detect the presence of an attacker during QKD without the need to disrupt the key distribution process. An architecture for implementing QKD in beyond 5G IoT networks is proposed, offloading the heavy computational tasks to IoT controllers. In addition, an implementation scenario for securing IoT communications for sensors deployed in railroad networks is described. The results show that the proposed ML techniques can reach 99% accuracy in detecting attackers.
Internet of Things (IoT) deployments face significant security challenges due to the limited energy and computational power of IoT devices. These challenges are more serious in the quantum communications era, where certain attackers might have quantum computing capabilities, which renders IoT devices more vulnerable. This paper addresses the problem of IoT security by investigating quantum key distribution (QKD) in beyond 5G networks. An architecture for implementing QKD in beyond 5G IoT networks is proposed, offloading the heavy computational tasks to IoT controllers, while considering the use case of sensors deployed in railroad networks. Neural Network (NN) techniques are proposed in order to detect the presence of an attacker during QKD without the need to disrupt the key distribution process. The results show that the proposed techniques can reach 99% accuracy.
The Internet of Things (IoT) connects billions of machines that can interact with each other. IoT is one of the fastest-growing areas in the history of computing, and will continue in this direction in the 6G era. New security problems have been raised, however, since implementing protection mechanisms for IoT devices, such as encryption, authentication, and so on, is inefficient, due to their inherent flaws. Therefore, a new method of protecting IoT devices needs to be sought. Quantum security depends on the natural physical phenomenon (quantum mechanics) and offers an appropriate and powerful security technique. This paper suggests a new approach for simulating the quantum key distribution between IoT devices and a server to encrypt the data sent to the server. It also demonstrates the simplicity of this new method, and its efficiency in producing a quantum key distribution (QKD) simulation. In addition, it describes the use of the final length key for symmetrical security for IoT devices. Moreover, the simulation of the attacker between the server and IoT devices is performed.
The rapid implementation of the Internet of Things (IoT) has raised security concerns, therefore revealing significant vulnerabilities in many sectors, including smart cities, healthcare, and agriculture. This extensive analysis of quantum computing and IoT security devices delineates the advantages of quantum algorithms and the potential for securing communication. Protocols including quantum concepts such as superposition, entanglement, and quantum interference, leading to safe key distribution and authentication procedures, are examined. This paper introduces a novel strategy to reduce the risks that quantum computing presents to IoT systems, which current cryptography solutions fail to adequately address. Quantum computers may use these vulnerabilities to undermine key-pair formation and get private keys from transaction signatures. These transaction signatures are optimized for low-power, cost-effective microcontrollers, such as the ESP32, making the solution accessible for a diverse array of IoT devices. The report features a case study on a post-quantum secure portable device for detecting blood oxygen levels and heart rate, demonstrating the practical advantages and efficacy of the suggested method in improving IoT security against quantum threats. The review addresses quantum key distribution (QKD) protocols, quantum authentication methods proposed as solutions, and the difficulties associated with implementing quantum cryptography techniques in IoT systems. This review assesses the feasibility of quantum-enabled communication, explores its applications across several industries, and examines existing quantum software tools. The objective is to provide a basis for future research and effective practical solutions in the dynamic realm of IoT security.
The Internet of Things (IoT) is a constantly expanding system connecting countless devices for seamless data collection and exchange. This has transformed decision-making with data-driven insights across different domains. However, challenges arise concerning security and computational limitations. To strengthen IoT against cyber threats and optimize resource usage, combining quantum computing (QC) with machine learning (ML) is a promising approach. ML enables computers to learn from data and detect patterns without explicit programming. By leveraging ML algorithms, vast datasets from IoT devices can be analyzed, identifying anomalies and forecasting potential security breaches. Yet, conventional ML algorithms may need help with the complexity and scale of IoT data. QC, based on quantum mechanics, offers unparalleled computational speed and scale. Quantum ML algorithms can quickly analyze IoT datasets, identifying patterns and potential threats. This study examines the ideas behind ML, QC, and their potential collaboration within IoT networks. The research focuses on the possibility of improving the security of IoT networks by integrating QC approaches with ML. It also addresses the challenges and limitations of integrating ML and QC in the context of IoT networks. These obstacles include hardware constraints, algorithm complexities, and the need for specialized knowledge.
The rapid proliferation of Internet of Things devices (IoT) across healthcare, smart homes, transportation, and industrial automation has led to an unprecedented exchange of sensitive data over wireless channels, exposing these networks to cyberattacks, eavesdropping, and unauthorized access.Conventional cryptographic techniques, which rely on computational hardness assumptions, are increasingly vulnerable to the emerging capabilities of quantum computing.This paper explores the application of Quantum Key Distribution (QKD) as a means of enabling secure and dependable data communication for IoT devices.By exploiting the fundamental principles of quantum mechanics, QKD allows two communicating parties to generate a shared secret key while inherently detecting any attempt at interception.The proposed approach aims to enhance data privacy, ensure secure authentication, preserve confidentiality, and safeguard IoT systems against present and future quantum enabled threats.The integration of quantum based security techniques into existing IoT infrastructure is examined, along with its implications for improving the reliability and trustworthiness of wireless IoT communication systems.This work positions Quantum Enhanced Secure Data Communication as a forward looking security solution for next generation IoT networks.