Wireless sensor networks (WSNs) are resource-constrained and highly vulnerable to eavesdropping due to their broadcast nature. Traditional symmetric key cryptography provides strong security but imposes excessive computational and energy demands on sensor nodes. Physical layer–based secret key generation (SKG) offers a lightweight alternative by exploiting channel reciprocity and randomness; however, existing methods are mostly limited to two-user scenarios and lack scalability in multi-user settings. This paper introduces two scalable multi-user SKG frameworks: a sequential method and a star topology-based method. In the sequential method, users cooperatively relay random signals to derive a shared key, while the star topology leverages a central node for signal aggregation and redistribution. A comparative analysis reveals trade-offs between the proposed methods. The sequential method is more computationally efficient but sensitive to node failures, while the star topology offers lower delay at the cost of requiring a fully connected central node. Analyses and simulations confirm both methods’ effectiveness in key mismatch probability, key generation rate, and key randomness validated by the National Institute of Standards and Technology test suite.
Wireless sensor networks (WSNs) are resource-constrained and highly vulnerable to eavesdropping due to their broadcast nature. Traditional symmetric key cryptography provides strong security but imposes excessive computational and energy demands on sensor nodes. Physical layer–based secret key generation (SKG) offers a lightweight alternative by exploiting channel reciprocity and randomness; however, existing methods are mostly limited to two-user scenarios and lack scalability in multi-user settings. This paper introduces two scalable multi-user SKG frameworks: a sequential method and a star topology-based method. In the sequential method, users cooperatively relay random signals to derive a shared key, while the star topology leverages a central node for signal aggregation and redistribution. A comparative analysis reveals trade-offs between the proposed methods. The sequential method is more computationally efficient but sensitive to node failures, while the star topology offers lower delay at the cost of requiring a fully connected central node. Analyses and simulations confirm both methods’ effectiveness in key mismatch probability, key generation rate, and key randomness validated by the National Institute of Standards and Technology test suite.
Wireless sensor networks are indispensable across various applications, from environmental surveillance to indus-trial automation, owing to their ability to collect and transmit data autonomously. However, due to the broadcast nature of wireless systems, these systems are vulnerable to eavesdropping attacks. Recently, channel-based secret key generation methods have been widely used in the literature. In these methods, Alice and Bob generate random signals and share these signals with each other. Then, using the secret key paired multiplication with the channel between them, a secret key is shared between legitimate users, while illegitimate nodes cannot access the key. However, these methods consider only two users. This paper proposes a novel method for multiple users. Extensive simulation proves the effectiveness of the proposed method. However, when the number of users increases, the performance of the proposed method decreases.
This paper presents a novel group secret key generation (GSKG) protocol for multi-user wireless systems with a star topology. In contrast to conventional methods relying on pairwise key derivation followed by reconciliation, the proposed approach enables the central node to directly select a group secret key uniformly at random across the full quantization space. This eliminates the need for intermediate pairwise keys, significantly reducing computational complexity, communication overhead, and latency. To ensure consistent group key reconstruction, we introduce two lightweight, non-coding reconciliation techniques: One-Sided Centering (OSC) and Quantization Pattern Alternation (QPA). Unlike coding-based reconciliation in conventional schemes, OSC and QPA allow the central node to transmit helper data – derived from adjusted measurements or shifted quantization grids – to peripheral nodes. This helper data not only aligns their channel observations with the selected quantization region, but also implicitly distributes the group key. Thus, reconciliation and distribution are seamlessly integrated into a unified protocol. The proposed GSKG framework supports both fully and partially cooperative scenarios and remains robust against unreliable or compromised nodes by selectively omitting or perturbing helper data. Furthermore, a concatenation-based group key construction method exploits existing bidirectional channel measurements to generate multiple key segments, enhancing throughput without additional channel probing. Extensive simulations validate the scheme’s performance in terms of key disagreement rate, key generation rate, computational efficiency, and robustness against eavesdropping. The results confirm that the protocol offers high scalability and security, making it a practical and efficient solution for group key establishment in IoT and other resource-constrained wireless applications.
Physical layer security (PLS) techniques hold promise for augmenting secure communications in the 5thgeneration of mobile wireless networks. Secret key generation (SKG) is a PLS technique which exploits the wireless propagation channel's randomness to generate symmetric key bits for information encryption and decryption. This work proposes symmetric key generation based on non-uniform quantization of the received signal strength (RSS) samples of a Nakagami-m fading channel. The proposed strategy for non-uniform quantization for SKG aims to set quantization thresholds for maximal key randomness and high values of key generation rate (KGR) and key agreement probability (KAP). Finally, a framework is proposed to use single node RSS measurements, readily available in the literature, to generate RSS samples at the other link end. This framework facilitates the testing of new SKG algorithms that require simultaneous RSS measurements by the legitimate nodes, which are not readily available in the open literature. The effectiveness of the proposed SKG scheme is validated through Monte Carlo methods and the National Institute of Standards and Technology (NIST) test suite for assessing the randomness of the generated key sequence.
Future sensor networks require energy and bandwidth efficient designs to support the growing number of nodes. The security aspect is often neglected due to the extra computational burden imposed on the sensor nodes. In this article, we propose a secret key generation method for wireless sensor networks by using the physical layer features. This key generation method is based on the superposition property of wireless channels. The proposed method exploits the multiple access property of the wireless channel with simultaneous transmissions as in theanalog function computationtechnique to solve the latency and scarce bandwidth problems of highly populated dense networks. All nodes use the same time and frequency block to provide scalability that islinearly proportionalto the number of nodes. The proposed method also benefits from the network density to provide security against eavesdroppers that aim to sniff the secret key from the channel. The security of the proposed method against eavesdroppers is analytically studied. Moreover, their application in multiple layers is investigated. The presented results have shown that there is a tradeoff between the total power consumption and total used bandwidth for secret key generation. Lastly, the error probability of the generated keys due to thermal noise and channel estimation error is investigated with computer simulations and compared with broadcasting-based benchmark model.
Due to the broadcast nature of wireless channels, wireless communication is vulnerable to eavesdropping, message modification, and node impersonation. Securing the wireless communication requires the shared secret keys between the communicating entities. Traditional security schemes rely on public key infrastructures and cryptographic algorithms to manage secret keys. Recently, many physical-layer-based methods have been proposed as alternative solutions for key generation in wireless networks. These methods exploit the inherent randomness of the wireless fading channel to generate secret keys while providing information-theoretical security without intensive cryptographic computations. This article provides an overview of the existing PHY-based key generation schemes exploiting the randomness of the wireless channels. Specifically, we first introduce the fundamental and general framework of the PHY-based key generation schemes and then categorize them into two classes: received-signal-strength-based and channel- phase-based protocols. Finally, we present a performance comparison of them in terms of key disagreement probability, key generation rate, key bit randomness, scalability, and implementation issues.
In the rapidly evolving landscape of wireless communication, securing transmitted information remains a critical challenge. This study provides a comprehensive review of secret key generation (SKG) techniques designed to secure physical layer wireless communication channels. We focus on key generation methods that exploit physical layer characteristics such as channel state information, received signal strength, and bit error rate. The computational complexity of these techniques is also examined, emphasizing the trade-offs between security and efficiency for real-world implementations. The review identifies open challenges such as developing low-cost, resource-efficient systems, managing artificial noise, and addressing the impact of mobility and multiuser massive MIMO systems on SKG rates. Our findings aim to guide the development of more efficient, scalable SKG methods for next-generation wireless networks. Additionally, we propose a method for securely generating identical secret keys between nodes using Cuckoo filters and a Map-Reduce model for frame hashing, ensuring long-term security in IoT environments.