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 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.
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.
Modern networking technologies involve the interconnection of smart and intelligent physical objects to provide advanced services. These physical objects may be part of various network technologies like WLAN, wireless sensor network (WSN), Internet of Things (IoT), etc., and share data in wireless mode, which should be secured from threats. These physical devices possess many constraints like power, computational complexity and storage, and are required to have lightweight security algorithms. Traditionally, security is achieved by the higher layers of the communication model, which has high computational complexity and consumes more power. In this chapter, a secure-key-generation scheme from physical layer characteristics is introduced as a possible lightweight security alternative to traditional upper-layer security approaches. The proposed scheme is based on the wiretap-channel model and security is achieved by generating keys at both communicating ends independently, based on inherent common-channel characteristics like randomness. It is mainly based on the principle of spatial decorrelation and channel reciprocity for identical carrier frequency. There is no provision for sharing keys as in public-key cryptography, so physical-layer key generation is not vulnerable to threats like key leakage. The generated key at the transmitter encrypts plain text; the generated cipher is transmitted on the common channel and is decrypted at the receiver end using the key generated by the receiver. Key generation consists of fundamental blocks like channel probing and quantization followed by information reconciliation and privacy amplification. The physical-layer key generation is already a power-efficient security solution; this chapter aims to enhance this capacity further. This is done by introducing low-end signal conditioning in the channel-probing step using moving-window averaging. This solution not only improves system performance but also makes it suitable for limited- power applications. The performance of the key-generation system is characterised in terms of the bit-disagreement rate between the generated key sequences of communicating parties and the key randomness by means of the NIST statistical test suite.
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.
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.
There is a growing interest in physical layer security. Recent work has demonstrated that wireless devices can generate a shared secret key by exploiting variations in their channel. The rate at which the secret bits are generated, however, depends heavily on how fast the channel changes. As a result, existing schemes have a low secrecy rate and are mainly applicable to mobile environments. In contrast, this paper presents a new physical-layer approach to secret key generation that is both fast and independent of channel variations. Our approach makes a receiver jam the signal in a manner that still allows it to decode the data, yet prevents other nodes from decoding. Results from a testbed implementation show that our method is significantly faster and more accurate than state of the art physical-layer secret key generation protocols. Specifically, while past work generates up to 44 secret bits/s with a 4% bit disagreement between the two devices, our design has a secrecy rate of 3-18 Kb/s with 0% bit disagreement.
Devices in the Internet of Things (IoT) are usually limited in computing resources and energy capacity, which means that encryption schemes with higher complexity are not suitable for them to ensure secure communication. As a promising solution to this problem, physical layer key generation suggests that shared secret keys can be generated from noisy wireless channel measurements to enhance the security of wireless communications. In this article, we propose a key generation scheme with extremely low implementation complexity, which allows physical layer key generation to be implemented on IoT nodes. First, we preprocess the channel measurements with simple moving average filtering before quantization to improve channel reciprocity. Next, a bidirectional difference quantization scheme is proposed to realize reliable quantization of channel measurements, which is ingenious in that the quantization process does not depend on quantization thresholds, and thus, the mismatched key bits caused by measurements close to quantization thresholds can be effectively avoided. Then, we propose an improved Cascade protocol to achieve lightweight and efficient information reconciliation. The simulation results show that our scheme can well balance the reliability and efficiency of key generation, and has excellent performance in terms of implementation complexity and key randomness.