## 1 Introduction  
The Internet of Things (IoT) represents a modern internet phenomenon. Device recognition achieves intelligence through establishing or facilitating context-related decisions via the device transceiving information about itself. The rise of cloud computing capabilities leads to an unlimited addressing capacity. The IoT's purpose is to allow device connectivity with anybody and anything at anytime, anywhere, and via any path/network and service. The IoT can be used in different applications such as transportation, healthcare, power grids, entertainment and smart buildings [1]. Encrypting IoT data before transferring it over wireless networks is one of the simplest and most effective ways to prevent it from being intercepted and altered. Data are converted into an unreadable format by the process of encryption, which can only be decrypted by authorized persons with the right key. IoT services require security to be at the core of everything. Physical layer security (PLS), one of the providing methods for communication security, has attracted a lot of interest from both academics and business since it can provide uncrackable, demonstrable, and quantifiable secrecy. PLS has a significant advantage over encryption since it is not dependent on computational complexity. Consequently, the degree of security attained will not be high, even if the listener has advanced computing capabilities. In contrast to a technique based on encryption, this is founded on the notion that an observer has a constrained computational ability to tackle challenging mathematical puzzles for brief intervals. For the PLS protocol design in IoT, the unique characteristics of IoT, such as cheap cost, wide-range coverage, enormous connection, and varied services impose significant problems [2]. The development of PLS solutions for IoT applications remains difficult despite the success of PLS technique research. The IoT is distinguished by four special characteristics in particular: low cost, broad coverage, high connectivity, and a variety of services. How to design PLS strategies that well match these four features remains an open problem [2]. Recently, [3] have enhanced the dynamics of constellation fluctuations between neighboring frames by utilizing the randomness in the data. The constellation is then dynamically rotated while using analog-based encryption rather than digital-based encryption, which lowers quantization loss and increases robustness to channel phase problems. The others in [4] offer an asymmetric multi-level physical layer security (PLS) scheme in which each transmitted symbol is subjected to two different types of distortion: multi-reception amplitude randomization and channel-based phase distortion. Additionally, the technique streamlines receiver design while providing a significant security advantage for authentic links. The study makes several doable, reasonable, and access-controlled suggestions in [5] for safeguarding the physical layer of the Internet of Things (IoT). The study is still going on with a specific focus on the difficulties with encrypted data. To achieve this goal, a secure approach at the physical layer that provides cryptographic features for usage in conjunction with a flexible RC6 encryption/decryption method is described. The chaos-based PLS transmission scheme for IoT is introduced in [6]. The suggested approach successfully addresses the concerns with the extremely high PAPR of the OFDM symbols in addition to providing confidentiality of physical layer information transfer by encrypting the Discrete Fourier Transform (DFT) matrix. Additionally, it has no need for additional sideband information and, in theory, has a minimal computing complexity. A physical layer security scheme for OFDM-based IoT systems with compressed sensing is proposed in [7]. The others use a combination of compressed sensing (CS) and OFDM to increase security. Therefore, using compressed sensing, we suggest the PLSSCS physical layer security strategy for OFDM-based IoT systems.