The physical characteristics of the wireless channel can be exploited to secure communication within Internet-of-Things (IoT) networks. Several techniques have been proposed in the literature; however, the feasibility of such techniques in IoT environments remains unclear. 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. On the other hand, in some cases IoT devices are deployed in dynamic environments wherein the channel properties changes very fast over the time. Key generation schemes proposed for one environment are not directly applicable to the other. While low key generation rate (KGR) is an issue for static environments, higher values of bit error rate (BER) becomes a bottleneck in dynamic environments. This paper proposes a mapping-table based key distribution scheme for IoT networks deployed in both static and dynamic environments. In the proposed scheme, the channel magnitude is exploited in the key generation process. The proposed scheme is immune to channel estimation errors, while providing sufficient randomness in the static environment.
The physical characteristics of the wireless channel can be exploited to secure communication within Internet-of-Things (IoT) networks. Several techniques have been proposed in the literature; however, the feasibility of such techniques in IoT environments remains unclear. 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. On the other hand, in some cases IoT devices are deployed in dynamic environments wherein the channel properties changes very fast over the time. Key generation schemes proposed for one environment are not directly applicable to the other. While low key generation rate (KGR) is an issue for static environments, higher values of bit error rate (BER) becomes a bottleneck in dynamic environments. This paper proposes a mapping-table based key distribution scheme for IoT networks deployed in both static and dynamic environments. In the proposed scheme, the channel magnitude is exploited in the key generation process. The proposed scheme is immune to channel estimation errors, while providing sufficient randomness in the static environment.
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.
Secret key agreement in distributed low-power networks, such as Internet of Things (IoT) networks, is a major requirement for deploying cryptographic protocols to protect the security of sensitive data. However, due to the distributed nature of such networks, the devices need to be able to generate secret keys locally from some common source of randomness. The randomness in the characteristics of the physical layer channel provides such sources, however, this can be quite limited if the devices operate in a static environment and experience static or very slow fading channel. Therefore, fast secret key generation in such environments while keeping a low complexity architecture for the network nodes, such as IoT devices, remains a challenging task. We design a low-complexity protocol for fast secret key generation in static environments. To this end, we propose to use a limited number of random bits independently generated by the legitimate parties, referred to as Alice and Bob, in combination with the fading parameter to create a common source of randomness. In the proposed protocol, Alice and Bob share their random bits over the public channel, assumed to be a fading channel, and then construct a common random sequence. Then they perform several steps for recovery from errors in the shared sequence, privacy amplification to limit the chances of a successful attack, and consistency checking by exploiting universal hash functions. We characterize the reliability of the proposed protocol and provide an upper bound on the probability of accepting a mismatched key by Alice and Bob. The eavesdropper Eve is assumed to be passive and a successful attack by her is the event of guessing the key right based on her observations. We provide an analytical upper bound, that can be numerically evaluated, on the probability of a successful attack by Eve using the cryptographic notion of semantic security. In the simulations, the proposed protocol achieves a bit generation rate of 64-96 bits/packet, bit mismatch rate of 11-24%, bit error rate of 0.005%, 50% randomness efficiency, the probability of successful attack of at most 2-31, and the probability of consistency checking failure of at most 2-16.
The billions of IoT devices in our home, healthcare, and industry rely on cryptographic keys for security. Constrained by computing and power resources, their keys are often pre-shared and rarely updated, creating a major vulnerability. The physical-layer wireless key generation can efficiently update keys but requires fluctuating wireless channel conditions, which, however, are scarce in static deployments. Here we show a novel wireless key generation that produces secure keys for static IoT without hardware assistance or secret exchange. We propose a randomness that is composed of received signal strengths and locally selected transmit power levels; the latter are independently selected at both communication pairs and are never exchanged, resulting in distinctive received signal strengths to ensure secrecy. We propose quantization and entropy balancing to boost generation efficiency and consistency. Experiments on an IoT testbed across multiple static scenarios achieve a fast key generation rate of 9.47 bits per second and a low key disagreement rate of 0.05, while defending against eavesdropping attacks. Xintao Huan and colleagues report a physical-layer wireless key generation scheme for static IoT scenarios. This scheme does not require hardware assistance or secret exchange and achieves fast key generation in static IoT while defending against eavesdropping attacks.
The increasing use of Internet of Things (IoT) also make data security a very importance. Traditional cryptographic methods are often unsuitable for IoT due to limited processing power and memory capacity, creating a need for lightweight yet effective security solutions. Physical Layer Key Generation (PLKG) offers a promising approach by utilizing the unique characteristics of wireless communication channels to generate secret keys without overloaded system demands. This paper show a performance analysis of Group Secret Key Generation in outdoor environments. The challenges are interfrence, physical obstacles, and dynamic changes in the communication channel was also the part of this analysis. The test results show that group secret key generation achieved optimal performance in Scenario 2, which given a correlation coefficient of 63 %, indicating strong channel similarity between nodes and a bit retention rate of 97.9 % after quantization and error correction. Scenarios 1, 3, and 4 also show a good performance, with correlation coefficients of41%,14%, and 35 %, and corresponding bit retention rates of93.1%,90.9%, and 95.2 %, on each tests. All scenarios successfully met the entropy thresholds required for cryptographic applications, which include that randomness and security of the generated keys was confirmed.
Wireless communication systems are becoming increasingly important in our daily lives, especially with the rapid expansion of the Internet of Things (IoT). Secure and reliable communication is essential for the correct functioning of critical applications and use cases such as healthcare, finance, transportation, and industrial automation. However, the growing number of connected devices introduces significant challenges to data security and privacy due to the open nature of wireless networks. While traditional encryption methods are effective, they can be resource-intensive and impractical for resource-constrained IoT environments. Physical layer security (PLS) provides a lightweight alternative by leveraging the inherent characteristics of wireless channels to generate symmetric secret keys without requiring third-party infrastructure. The PLS key generation process involves four main stages: channel sampling, quantization, reconciliation, and privacy amplification. This paper provides a comprehensive survey of existing quantization schemes, as this step plays a crucial role in determining the key generation rate (KGR) and key disagreement rate (KDR). Additionally, the paper classifies quantization methods as either lossless or lossy, providing insights into the trade-offs between security and efficiency.
Physical layer secret key generation schemes can provide lightweight encryption for resource-constrained Internet of Things (IoT) devices. However, many IoT devices are stationary and the environment is usually static, which leads to ultra-low/zero secret key rates. To circumvent this problem, a novel secret key generation scheme based on Reconfigurable Intelligent Surface (RIS) is proposed for Multiple-Input Single-Output IoT communications. The RIS is introduced into the network, and the phase shifts at RIS are tuned randomly in each frame, which makes time-varying reflection channels superimposed on the original channels. And then, the secret key capacity of all nodes within the cell coverage area can be remarkably improved. Compared with the existing methods, the scheme is loosely coupled with the existing communication system. The closed-form expressions of secret key capacity taking into account eavesdropping are first derived for the case studies of independent and correlated channels. We can conclude that sharing the same phase shifts randomness will not bring key information leakage. Compared with existing user-introduced randomness schemes, the proposed scheme can maintain good performance as the number of eavesdropping nodes increases. Further, the impact of parameters, such as the number of reflecting units, the transmit antennas, and the Rician factor, on secret key performance are analyzed respectively, which can offer guidelines for system design. Finally, simulation results verify the theoretical analysis.