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Secret key generation exploits the unique random features of wireless channels, hence it is eminently suitable for the resource constrained Internet of Things applications. However, it has only been involved for single links between a pair of users, whilst there is a paucity of literature on group and multi-user key generation. This paper proposes...
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... shown in Fig. 2(a), OFDM allocates all the available subcarriers to a single user, which can then achieve a high data rate within the given bandwidth. Duplexing is handled in a TDD mode. Therefore, OFDM has been employed for improving the key generation rate by exploiting the randomness both in the time-and in the frequency-domains [27]- ...
Context 2
... the other hand, OFDMA allows multiple users to simultaneously access the spectrum by transmitting in orthogonal non-overlapping bands, as illustrated in Fig. 2(b). Since the OFDM subcarriers are orthogonal, there is no interference amongst them. This allows the AP to simultaneously obtain channel measurements of multiple users. Surprisingly, however, this feature has never been exploited for key generation, mainly because OFDMA has never been adopted in Wi-Fi standardization until the recent ...
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Citations
... A useful key generation protocol was presented forth by Hershey [41] in 1995 and was based on the three properties of wireless channels-reciprocity, uniqueness, and randomness. Since then, many researchers have further studied the PKG in various scenarios from different angles [28,[42][43][44][45], which will be introduced later. ...
... In recent years, there are many practical protocols have been proposed to optimize the performance of PKG and meet the constraints of different scenarios, such as maximizing the sum key generation rate (KGR) and reducing the pilot overhead. However, they are generally composed of four steps: channel probing, quantization, information reconciliation, and privacy amplification [25,29,42,47,48], which are portrayed in Figure 3. As depicted in Figure 3, there are two legitimate users, namely Alice and Bob, and their PKG process can be summarized as follows: Alice and Bob perform channel probing firstly to obtain channel information, such as obtaining Y A and Y B by sending pilot signals S A and S B to the other party respectively and performing channel estimation based on the received signals, and often a preprocessing method is used to eliminate interference from non-reciprocal factors. ...
As the development of next-generation (NextG) communication networks continues, tremendous devices are accessing the network and the amount of information is exploding. However, with the increase of sensitive data that requires confidentiality to be transmitted and stored in the network, wireless network security risks are further amplified. Physical-layer key generation (PKG) has received extensive attention in security research due to its solid information-theoretic security proof, ease of implementation, and low cost. Nevertheless, the applications of PKG in the NextG networks are still in the preliminary exploration stage. Therefore, we survey existing research and discuss (1) the performance advantages of PKG compared to cryptography schemes, (2) the principles and processes of PKG, as well as research progresses in previous network environments, and (3) new application scenarios and development potential for PKG in NextG communication networks, particularly analyzing the effect and prospects of PKG in massive multiple-input multiple-output (MIMO), reconfigurable intelligent surfaces (RISs), artificial intelligence (AI) enabled networks, integrated space-air-ground network, and quantum communication. Moreover, we summarize open issues and provide new insights into the development trends of PKG in NextG networks.
... These studies target relatively small networks and require impractical communication times in dense networks. In the second category [9]- [13], the methods are purely based on broadcasting and are suitable for dense networks. In [9], the authors consider a new metric where, instead of raw RSSI values, difference of two received signal strength indicator (RSSI) values from two different channels is used. ...
... As main drawbacks, these algorithms either assume a noiseless channel or apply channel coding to provide a noiseless channel between the nodes for information exchange. In [13], an orthogonal frequency-division multiple access (OFDMA)-based key generation model is proposed. The method aims to reduce the duration of channel estimation phase by exploiting OFDMA. ...
... Zhang et al. [13] Reduces the load of channel estimation process for OFDMA networks. ...
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 the
analog function computation
technique 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 is
linearly proportional
to 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.
... Hence, those works related to PKG among multiple nodes through the optimization of probing rates at individual node pair and channel probing schedule do not scale in this context [14]. In the multi-user key generation, Zhang et al cleverly exploited the multi-user mechanism of OFDMA modulation by assigning non-overlapping subcarriers to different users [15]. However, there is no work exploiting the spatial diversity of massive MIMO to enable multi-user key generation. ...
Physical-layer key generation (PKG) based on channel reciprocity has recently emerged as a new technique to establish secret keys between devices. Most works focus on pairwise communication scenarios with single or small-scale antennas. However, the fifth generation (5G) wireless communications employ massive multiple-input multiple-output (MIMO) to support multiple users simultaneously, bringing serious overhead of reciprocal channel acquisition. This paper presents a multi-user secret key generation in massive MIMO wireless networks. We provide a beam domain channel model, in which different elements represent the channel gains from different transmit directions to different receive directions. Based on this channel model, we analyze the secret key rate and derive a closed-form expression under independent channel conditions. To maximize the sum secret key rate, we provide the optimal conditions for the Kronecker product of the precoding and receiving matrices and propose an algorithm to generate these matrices with pilot reuse. The proposed optimization design can significantly reduce the pilot overhead of the reciprocal channel state information acquisition. Furthermore, we analyze the security under the channel correlation between user terminals (UTs), and propose a low overhead multi-user secret key generation with non-overlapping beams between UTs. Simulation results demonstrate the near optimal performance of the proposed precoding and receiving matrices design and the advantages of the non-overlapping beam allocation.
... Alice and Bob keep probing until they collect sufficient measurements, and , respectively. [72,135,154,159]. ...
... Since then, numerous studies have been conducted to investigate CSI-based key generation systems from different application scenarios and perspectives [135,154,159,162,164]. ...
... Zhang et al. [159] modelled and analysed the time and frequency correlation of the OFDM by using Wi-Fi as a case study. Zhang et al. [154] took a step further by extending key generation to multiple users. In particular, they leveraged the Orthogonal Frequency-Division Multiplexing Access (OFDMA) for enabling the access point to communicate with multiple users simultaneously. ...
Key generation is a promising technique to bootstrap secure communications for the Internet of Things (IoT) devices that have no prior knowledge between each other. In the past few years, a variety of key generation protocols and systems have been proposed. In this survey, we review and categorise recent key generation systems based on a novel taxonomy. Then, we provide both quantitative and qualitative comparisons of existing approaches. We also discuss the security vulnerabilities of key generation schemes and possible countermeasures. Finally, we discuss the current challenges and point out several potential research directions.
... Key generation has then been applied to numerous wireless techniques, including IEEE 802. 15 [75], Bluetooth (since 2014) [76], LoRa/LoRaWAN (since 2018) [77]- [79]. ...
... All the WiFi features, namely the frequency diversity of OFDM [60], spatial diversity of MIMO [72] and multi-user access capability of OFDMA [75], have been leveraged to enhance the key generation performance. Explicitly, [69], [70] represent the seminal key generation research, which uses IEEE 802.11a/g and extracts keys from the RSSI. ...
... The KGR can be further enhanced by using OFDM for exploiting the frequency diversity [73], [178]; Liu et al. achieved a KGR as high as 360 bit/pkt employing a 2 × 2 MIMO OFDM system (3-bit quantization is used) [73]. Finally, Zhang et al. [75] leveraged the multi-user access feature in the latest IEEE 802.11ax amendment, which enables the AP to simultaneously establish keys with multiple users. ...
The Internet of Things (IoT) is a transformative technology, which is revolutionizing our everyday life by connecting everyone and everything together. The massive number of devices are preferably connected wirelessly because of the easy installment and flexible deployment. However, the broadcast nature of the wireless medium makes the information accessible to everyone including malicious users, which should hence be protected by encryption. Unfortunately the secure and efficient provision of cryptographic keys for low-cost IoT devices is challenging; weak keys have resulted in severe security breaches, as evidenced by numerous notorious cyberattacks. This paper provides a comprehensive survey of lightweight security solutions conceived for IoT, relying on key generation from wireless channels. We first introduce the key generation fundamentals and protocols. We then examine how to apply this emerging technique to secure IoT and demonstrate that key generation relying on the randomness of wireless channels is eminently suitable for IoT. This paper reviews the extensive research efforts in the areas of theoretical modelling, simulation based validation and experimental exploration. We finally discuss the hurdles and challenges that key generation is facing and suggest future work to make key generation a reliable and secure solution to safeguard the IoT.
... Hence, those works related to PKG among multiple nodes through the optimization of probing rates at individual node pair and channel probing schedule do not scale in this context. Exceptionally, Zhang et al. designed a multi-user key generation protocol by leveraging the multi-user access of OFDMA modulation, which is achieved by assigning nonoverlapping subcarriers to different users [5]. However, no work has been devoted to exploiting the spatial diversity of massive MIMO to enable multi-user key generation. ...
Physical-layer key generation (PKG) in multi-user massive MIMO networks faces great challenges due to the large length of pilots and the high dimension of channel matrix. To tackle these problems, we propose a novel massive MIMO key generation scheme with pilot reuse based on the beam domain channel model and derive close-form expression of secret key rate. Specifically, we present two algorithms, i.e., beam-domain based channel probing (BCP) algorithm and interference neutralization based multi-user beam allocation (IMBA) algorithm for the purpose of channel dimension reduction and multi-user pilot reuse, respectively. Numerical results verify that the proposed PKG scheme can achieve the secret key rate that approximates the perfect case, and significantly reduce the dimension of the channel estimation and pilot overhead.
... The group key generation approaches have been investigated in [8], [24]- [26], regarding different network topologies of star, ring, chain, mesh, etc. Individual multi-user key generation has been studied in [27], [28], with different time and frequency resources allocated to different users, respectively. Jin et al. has proposed a multi-user PKG approach which optimized probing rates at individual node pair and channel probing schedule to minimize the overall waiting time. ...
... Jin et al. has proposed a multi-user PKG approach which optimized probing rates at individual node pair and channel probing schedule to minimize the overall waiting time. Zhang et al. exploited the multi-user mechanism of orthogonal frequency division multiplexing (OFDM) modulation to assign non-overlapping subcarriers to different users [27]. However, the occupied time/frequency resources grow linearly with the number of users in these schemes. ...
Secret key generation in multi-user massive multiple-input multiple-output (MIMO) communication suffers from high computation complexity, pilot overhead, and inter-user interference caused by the large dimension of the massive MIMO channel. To address these problems, this paper proposes a novel key generation approach that exploits the beam domain channel for channel feature extraction. The proposed approach can effectively reduce the channel feature dimension and mitigate the inter-user interference, via the well-designed power allocation and beam scheduling algorithms. Specifically, the multi-user key generation model is built and the design problem of channel feature extraction matrices is formulated as a sum key rate maximization problem. To tackle this problem, we derive an upper bound of the secret key rate and prove that the upper bound maximization is a convex optimization. After solving the upper bound maximization, the base station (BS) obtains the sum beams for all the users. To allocate the selected beams to each user, an efficient beam scheduling algorithm is proposed, which converges to a locally optimal solution with low computational complexity. Numerical results illustrate that in the proposed scheme, the bit disagreement ratio (BDR) of legitimate users achieves 10
<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup>
, while that of the eavesdropper tends to 0.5, confirming the feasibility and security of the proposed scheme.
Backscatter communication (BC) is an emerging radio technology for achieving sustainable wireless communications. However, the literature still lacks an effective secret group key generation scheme for safeguarding communications among multiple resource-constrained backscatter devices (BDs). In this paper, we propose a novel physical layer group key generation framework, BGKey, for securing backscatter communications among multiple BDs. BGKey contains three schemes: Centralized Group Key Generation (CGKG), Decentralized Group Key Generation (DGKG), and Decentralized Hierarchical Group Key Generation (DHGKG). Each scheme has its own advantages, applicable in different scenarios. We analyze the performance of BGKey schemes regarding computation and communication complexity and security under eavesdropping and three active attacks. We conduct extensive simulations with different system parameters to evaluate their performance. CGKG is the most efficient and accurate for generating a group key, but it depends on a trusted radio frequency source (RFS) and is the least secure under eavesdropping and three active attacks among three schemes. DGKG exhibits better security and higher key generation rate (KGR) against eavesdropping and three active attacks compared with CGKG. However, the bit disagreement ratio (BDR) of group key increases when the size of BD group increases. DHGKG dramatically enhances the performance of group key generation compared with DGKG and retains its excellent security against eavesdropping and three active attacks.
Physical layer key generation is a lightweight technique to establish secret keys securely between resource-constrained devices, but it is ineffective when wireless channels are static or blocked. Physical layer key generation is improved by the use of reconfigurable intelligent surfaces (RISs) to control massive reflecting elements. The channel coefficients of massive reflecting elements serve as a source of randomness for generating secret keys. However, the correlation between the channel coefficients of reflecting elements and OFDM subcarriers causes measurement redundancy, which poses a threat to secret keys. We analyze the secret key rate (SKR) and construct analytical expressions for it. Furthermore, we propose a preprocessing method for decorrelating the measurements, which greatly reduces the computational complexity. Simulation results validate the SKR, bit disagreement ratio (BDR), and randomness. Compared to existing schemes, the proposed scheme greatly improves the SKR.
