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.
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.
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.
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.
The traditional wireless communication security technology is based on cryptography at the network layer, which exploits computational complexity to make it difficult to crack to achieve encryption. With the ongoing advancement of computing power, computational security may be difficult to maintain. From the viewpoint of information theory, physical layer security technology is an essential instrument for integrating security and communication. This paper mainly studies the quantization steps in the key generation technology of wireless communication physical layer. In this paper, a quantization scheme with extremely low implementation complexity is proposed for key generation. Firstly, utilizing the reciprocity and randomness of the wireless channel, the communication parties conduct channel measurements to collect channel state information (CSI) and study the improvement of CSI extraction by incorporating intelligent reflection surfaces. Then, the proposed hybrid quantization scheme makes full use of CSI and quantizes the CSI and its phase information to obtain key bits. Numerical results show that the proposed scheme improves the quality of key generation and avoids information leakage during transmission, and passes the NIST randomness test.
Reliable communication over Wireless Body Area Networks (WBANs) is an essential aspect of Wireless Body Area Networks (WBANs) because the physiological data flows between wearable sensor nodes is sensitive data. The convectional cryptography methods usually apply a lot of computational complexity as well as energy overhead besides which they are not going to fit in the ultra-low-power WBANs. In the current paper a light-weight, energy-efficient Physical Layer Key Generation (PLKG) scheme the possibilities of which based on the native randomness and reciprocity of the wireless channel is used to generate secure symmetric keys is presented. With WBANs, there is a lot of temporal and spatial dynamics in the human body and its surrounding environment, which causes great variability in channel characteristics, in terms of Received Signal Strength Indicator (RSSI) and Channel State Information (CSI). Such physical layer parameters can be used as perfect entropy sources in generation of unique, unpredictable secret keys with whose knowledge, communication between nodes is possible and mutually exclusive only. The channel probing in the proposed framework is also robust, multi-bit quantization is performed adaptively, information reconciliation is performed through error correction codes, and privacy amplification is made through cryptographic hashing. We have developed a resilient system against bit mismatch and efficiently against passively eavesdropping, we guarantee the secrecy of the generated keys under adversary situation. With realistic WBAN models simulation and experiment validation shows that the proposed approach is capable of generating keystokes with very high key generation rate (50 bps) and a bit mismatch rate of lower than 3 percent as compared to existing schemes that solely relied on RSSI, making this protocol more secure and reliable to use. In addition, the framework meets the statistical randomness requirements specified by NIST and it does not leak mutual information to eavesdroppers. The scheme allows real-time use on resource-constrained devices, e.g., wearable medical devices and health-monitoring sensor, as it has low computational and memory overhead. The findings establish the feasibility of employing physical layer properties to achieve secure WBANs communication without any pre-shared keys or a centralized trust paradigm, thus, opening the way to scalable and privacy-preserving healthcare systems.
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 use of wireless networks for communication has grown significantly in recent times, and continues to develop further. The broadcast nature of wireless communications makes them susceptible to a wide variety of security attacks. Unlike traditional solutions, which usually handle security at the application layer, the primary concern of this dissertation is to analyse and develop solutions for secure communication using channel coding techniques at the physical-layer. \nThe topic of physical layer authenticated encryption using high rate key generation through shared randomness is investigated in this work. First, a physical layer secret key generation scheme is discussed exploiting channel reciprocity in wireless systems. In order to address the susceptibility of this family of schemes to active attacks, a novel physical layer authentication encryption protocol is presented along with its extension to multi-node networks in the presence of active adversaries. Unlike previous work in the area of generating secret keys through shared randomness, it is demonstrated that the proposed scheme is semantically secure with respect to chosen plaintext and chosen cipher text attacks. \nSecondly, in order to increase the rate in bits per seconds at which agreed cryptographic keys are been generated, a multi-level quantization algorithm with public feedback is discussed. It is demonstrated that the proposed scheme is superior to direct information distillation approaches and can substantially increase the key generation rates even at low and medium SNRs. Furthermore, the employment of this low-overhead feedback at the information distillation process can largely simplify the information reconciliation process. \nThe proposed secret key generation schemes are tested for randomness such as required for cryptographic keys. The validation test is perfomed with the aid of National Institute of Standards and Technology (NIST) statistical test suite. The P-values obtained in each of the test carried out indicates that the key sequence generated by our algorithm is random.