# Defense and Security Mechanisms in the Internet of Things: A Review
## 4 Security Mechanisms in IoT Environments
### Authentication and Key Agreement Protocols for IoT Environments  
[PERSON] et al. in [121] provided a deep learning-powered authentication and key agreement protocol dedicated to IoT and LTE systems. This protocol employs a Deep Residual Network-based dynamic shared secret key creation method. The authors confirmed that the proposed protocol ensures privacy protection, avoids signalling congestion issues, and protects from redirection, MITM, replay, and DoS attacks. Using deep learning techniques may improve the detection rates of attacks and decrease the time it takes to respond to them. Nevertheless, satellite-based systems may encounter scalability and resource availability limitations, which could result in substantial additional costs. [PERSON] et al. proposed in [15] a protocol for user authentication and key agreement in multi-gateway environments. This protocol relied on fuzzy extraction technology for biometric verification. Through formal and informal analysis, the authors showed that their protocol is secure against theft of smart cards, internal impersonation, resilience against sensor capture, and MITM or temporary secret leakage attacks. In the study by [PERSON] et al. [122], the authors proposed an anonymous authentication and key agreement mechanism to minimise the delay in sending IoT data. The proposed scheme involved the use of hash functions and bitwise XOR operations. The protocol ensures that there is always strong mutual authentication between the IoT devices and the fog servers without needing a registration authority. It also establishes secure session keys created from unique random numbers without the involvement of the registration authority. The authors validated their solution and affirmed its resilience against MITM, replay, key exposure, known session key, IoT device impersonation, fog server impersonation, IoT device physical capture, fog server physical capture, IoT device traceability, unknown key-share, and privileged insider attacks. [PERSON] et al. [123] proposed a new authentication and key agreement protocol for smart home applications in the context of software-defined IoT. The protocol has registration, authentication, and key selection phases. The authors used a Software-Defined Network controller to encrypt low-power IoT devices. The security of the proposed protocol was validated with the AVISPA tool. Their system withstands replay, impersonation, modification, man-in-the-middle, and traceability assaults. Furthermore, it guarantees non-traceability, user anonymity, clock synchronisation, and absolute secrecy. Additionally, they simulated the protocol's operations to evaluate running time, computational complexity, and energy consumption compared to alternative methods. In [124] by [PERSON] et al., the focus was placed on the security of IoT devices in smart hospitals, digital health, and automated pathology laboratories. They proposed a mutual authentication and key agreement protocol to establish a shared and secured channel for authenticated devices, thus ensuring that only the authorised devices can access the channel. The suggested architecture includes the Hyperledger Fabric blockchain and fog servers as blockchain peers. This protocol comprises four phases: Initial System Setup, Blockchain Initialization, Device Registration, and Mutual Authentication and Key Exchange. The authors proved the effectiveness of their protocol with the help of formal and informal security and performance analyses, which were conducted on Hyperledger Fabric and with the usage of cryptographic libraries. Their confirmation affirmed the protocol's ability to counter impersonation, man-in-the-middle, replay, and device capture threats. Also, they ensured that the proposed protocol meets the following security requirements: anonymity, untraceability, and session key agreement. [PERSON] et al. indicated in their article [125] that an enhanced authentication and key agreement mechanism has been devised for healthcare applications.