With rapid advances made in quantum computing, information theoretic security is of paramount importance for Internet of Things (IoT), particularly for low-powered devices like sensors and actuators, where there is generally little to no room for complex security features. Common Randomness (CR) can be considered as a resource, that can be used for adding information theoretic security to the IoT systems. The most desired CR is a lengthy CR with uniform distribution. In this study, we design and implement channel reciprocity based CR using a Software Defined Radio (SDR). Furthermore, we also implement Quantum Entanglement (QE) assisted CR generation scheme and compare it against the classical channel reciprocity based scheme. The evaluation of both CR generation schemes has been carried out on the basis of National Institute for Statistical Tests (NIST) and bit discrepancy results. We show that QE assisted CR generation is more efficient compared to channel reciprocity based CR, in terms of generating uniformly distributed CR, if the latter is observing slow fading channel.
With rapid advances made in quantum computing, information theoretic security is of paramount importance for Internet of Things (IoT), particularly for low-powered devices like sensors and actuators, where there is generally little to no room for complex security features. Common Randomness (CR) can be considered as a resource, that can be used for adding information theoretic security to the IoT systems. The most desired CR is a lengthy CR with uniform distribution. In this study, we design and implement channel reciprocity based CR using a Software Defined Radio (SDR). Furthermore, we also implement Quantum Entanglement (QE) assisted CR generation scheme and compare it against the classical channel reciprocity based scheme. The evaluation of both CR generation schemes has been carried out on the basis of National Institute for Statistical Tests (NIST) and bit discrepancy results. We show that QE assisted CR generation is more efficient compared to channel reciprocity based CR, in terms of generating uniformly distributed CR, if the latter is observing slow fading channel.
Common Randomness (CR) can be considered as a resource for future communication devices and systems that not only improve the transmission capacity of identification systems but also provide robust information theoretical security. To achieve this, CR must be generated such that the reconciliation cost must be lower than the size of the key that is being generated. This can be achieved by using filters. In this live demonstration, we prepare a CR generation mechanism using Software Defined Radio (SDR) and achieve this tradeoff using multi-bit quantization and Savitzky Golay filter.
Common randomness (CR), as a resource, is not commonly used in existing practical communication systems. In the common randomness framework, both sender and receiver, often described as terminals, aim to generate a common random variable observable to both, perhaps with low error probability. The knowledge of this CR allows to implement correlated random protocols that could lead to faster and more efficient algorithms. We characterize CR over Gaussian channels for their practical relevance in many communication situations by deriving the CR capacity for both Gaussian Single-Input Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO) cases. Furthermore, CR plays a key role in the identification scheme. In many new applications such as several machine-to-machine and human-to-machine systems and the tactile internet, which demand ultra-reliable low latency, the identification or also called post-Shannon scheme is proved to be more efficient than the classical transmission. It has been proved that through CR generation, the post-Shannon communication task allows to achieve an enormous performance gain. We consider a correlation-assisted secure identification scheme over Gaussian wiretap channels (GWC) and develop a lower bound on the corresponding secure identification capacity.
Identification is a new paradigm introduced for goal-oriented communication that verifies the semantics of the intended message rather than just transmitting the message bits, which is traditionally done in classical communication systems. One of the key techniques to improve randomized identification capacity is by introducing Common Randomness (CR). Physical Layer Secret Key (PLSK) is one such CR generation technique, where terminals generate secret keys based on changes in channel reciprocity between the wireless terminals and are mainly used for PHY layer encryption. However, the traditional way of evaluating PLSK techniques through bit discrepancies, bit generation rate, and entropy is not sufficient for evaluating their usefulness for identification. This paper proposes three key novel information theory paradigms that can be used alongside other mentioned parameters to evaluate key PLSK techniques for their usefulness in identification, i.e., CR rate, CR capacity, and cost function, followed by a supporting implementation using Software Defined Radio (SDR)s.
Common randomness (CR) is a valuable resource for enhancing the trustworthiness of 6G communication systems. This article highlights the role of CR in improving scalability, security, and resilience in distributed 6G architectures. It provides an overview of information-theoretic two-source models for CR generation and summarizes known capacity results, together with their implications for practical systems under different communication settings, including one-way, two-way, helper-assisted, and interactive scenarios. Furthermore, the article explores CR-assisted secure identification over Gaussian channels as an application and highlights selected open research problems in CR generation for next-generation wireless systems. The article targets researchers and practitioners interested in bridging information-theoretic tools with emerging 6G communication systems.
Internet-of-Things (IoT) networks generally contain resource-constrained devices that require an energy-efficient key generation procedure to producing secure keys at a faster rate. The physical characteristics of the wireless channel can be exploited to secure communication within IoT networks. In particular, secret keys can be generated by leveraging on the randomness of the wireless physical channel between two communicating parties. The conventional mechanism of generating keys at the physical layer, i.e., using channel probing, quantization, information reconciliation, and privacy amplification, may not be preferable for IoT devices. In addition, in some cases IoT devices may be deployed in static environments, wherein the channel coherence time is too high to generate keys at a faster rate and with the desired randomness. This study proposes a mapping table-based key distribution scheme for IoT environments, wherein multiple characteristics of the random channel are combined to improve not only the key generation rate (KGR) but also the key agreement rate (KAR) and bit error rate (BER). In the proposed scheme, both the channel magnitude and the phase are exploited in the key generation process. The proposed scheme is immune to channel estimation errors while providing sufficient randomness in the static environment. Additionally, the scheme is thoroughly investigated for different scenarios including the case of a smarter eavesdropper, which attempts to estimate the channel between the legitimate nodes. This case verifies the robustness of the proposed scheme in different settings and attack models.
The rapid development of Internet of Things (IoT) applications has led to the large-scale deployment of wireless sensor networks (WSNs) that incessantly generate and transmit sensitive data over wireless networks.Although the current mostly used symmetric encryption algorithm for securing such networks is the Advanced Encryption Standard (AES), the advent of quantum computing threatens the long-term security of AES, as well as the weaknesses inherent to the key generation, distribution, and lifecycle management.This research paper proposes a Quantum Enhanced AES framework for IoT based WSNs which integrates the use of Quantum Random Number Generator (QRNG) based high entropy key generation, key injection against side channel attacks and dynamic session-based rekeying.Compared with classical AES and two state-of-the-art security frameworks based on quantum computing, i.e., QKDassisted AES scheme and lightweight post-quantum security hybrid AES framework, the proposed scheme increases the entropy of the key by about 20% (from 0.82 to 0.99), and lowers the key exposure risk by more than 60% by using session-based rekeying.Simulation results indicate that the proposed method can achieve up to 8 to10% higher throughput and 22% lower end-to-end delay than post-quantum AES schemes, and also prolongs the network lifetime by almost 15% under realistic IoT-WSN workloads.The framework maintains and does not alter the AES standard compliance and does not make any changes to the AES core, thus it ensures practical applicability.These results show that the proposed approach offers a good quantum resilience with low performance and energy overhead, which is suitable for long-lived and security-critical IoT-WSN deployment.