Ambient Power-enabled Internet of Things (AIoT) is expected to be a key technology for future 6G to support green and sustainable development. Developing lightweight security mechanisms to accommodate the extremely low power consumption of AIoT devices is of vital importance. Physical layer key generation (PLKG) is expected to be a promising security technology for AIoT. Considering the widespread application of one-to-many communication paradigm in AIoT systems, in this paper, we propose a physical layer group key generation (PLGKG) scheme to support the secure group communications among multiple AIoT devices. By designing the precoding weight coefficient of the reader, multiple AIoT devices can receive the same key source at the same time, and thus obtain the common group key. The system security is analyzed and the achievable group key rate (GKR) is also derived. Simulation results show that the proposed scheme not only reduces the time overhead of group key generation, but also achieves the lower group key disagreement ratio (GKDR).
Ambient Power-enabled Internet of Things (AIoT) is expected to be a key technology for future 6G to support green and sustainable development. Developing lightweight security mechanisms to accommodate the extremely low power consumption of AIoT devices is of vital importance. Physical layer key generation (PLKG) is expected to be a promising security technology for AIoT. Considering the widespread application of one-to-many communication paradigm in AIoT systems, in this paper, we propose a physical layer group key generation (PLGKG) scheme to support the secure group communications among multiple AIoT devices. By designing the precoding weight coefficient of the reader, multiple AIoT devices can receive the same key source at the same time, and thus obtain the common group key. The system security is analyzed and the achievable group key rate (GKR) is also derived. Simulation results show that the proposed scheme not only reduces the time overhead of group key generation, but also achieves the lower group key disagreement ratio (GKDR).
With the increasing demands for sharing confidential information among massive Internet of Things (IoT) devices in 5G and beyond wireless networks, many applications require the common secret key generation for a group of IoT devices. However, most of the existing works on physical layer secret key generation (PLKG) only focus on the pairwise key generation between two users, which is a low efficient and high cost to be extended to the scenarios of group key generation. In this work, we propose a new efficient multiple-input–multiple-output (MIMO) physical layer group secret key generation scheme to reduce the consumption of channel probing and improve the efficiency for group key generation. Different from current schemes, in the proposed scheme, the transmitter randomly generates the group secret key and directly broadcasts the downlink data symbols to the group users. At the receiver end, each group user can efficiently “observe” the common group key through the downlink broadcasting data symbols, while keeping perfect secrecy of the shared group key against eavesdroppers. The performance of reliability, security, and the group key generation rate is fully investigated, which shows the advantages of high efficiency, low consumption, and strong robustness of the proposed scheme. Extensive simulations are conducted to validate the effectiveness of the proposed scheme.
The necessity for ultra-low-power consumption devices that enable the Internet of Things (IoT) networks to be more energy efficient, leads to considering Ambient Backscatter Communication (AmBC). Such devices exploit ambient radio-frequency signals to communicate and harvest energy. Though, the physical layer key generation (PLKG) scheme that enables AmBC to generate a secret key for data encryption, is vulnerable to injection attacks. Under such a menace, an attacker injects predefined signals and contributes to the PLKG. Thereby, it possesses a part of the generated bits and uses brute force attack to compromise the entire key. Inspired by that, we carefully prove the vulnerability of the existing PLKG approach in AmBC to injection attack. Then, we propose the employment of a smart device that aims at detecting the attack and canceling the malicious signal. Furthermore, we propose a new strategy that enables legitimate devices to utilize the entire received ambient signal for PLKG while exploiting the malicious signal for energy harvesting. Hence, the attacker becomes the victim. Finally, we provide numerical simulations that accentuate the consequence of the menace and the effectiveness of our security method, even though only 80% of the injected signal is removed. Besides, we prove the efficacy of our energy harvesting strategy.
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.
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.
The security of the Internet of Things (IoT) is receiving considerable interest as the low power constraints and complexity features of many IoT devices are limiting the use of conventional cryptographic techniques. This article provides an overview of recent research efforts on alternative approaches for securing IoT wireless communications at the physical layer, specifically the key topics of key generation and physical layer encryption. These schemes can be implemented and are lightweight, and thus offer practical solutions for providing effective IoT wireless security. Future research to make IoT-based physical layer security more robust and pervasive is also covered.
Since the emergence of Internet of Things (IoT) technology on the surface a few years ago, this IoT technology has been advancing. It has attracted the attention of cybercriminals. One of the cybercrime targets is the security of key management systems and their distribution schemes. This paper offers a solution to this issue by using a physical layer key generation (PLKG) scheme which utilizes the received signal strength indicator (RSSI) from a Long Range (LoRa) device as a key extraction source. The proposed scheme utilizes several methods. Polynomial fitting is used for the initial fitting process, 2-Ary quantization for conversion of RSSI to multibit, BCH to correct the difference in bits obtained between the two authorized users, privacy amplification for increased randomness, and AES-128 for encryption of sent messages. The expected outcome of this paper is that the scheme developed can generate keys with high approximate entropy and fulfills randomness requirements so that there is no need to distribute keys between authorized users. Testing the success of the scheme will be carried out in indoor and outdoor environments with static user positions. The test results show that the keys generated in all scenarios meet the randomness requirements with approximate entropy values above 0.01.