# Autonomous Mutual Authentication Protocol in the Edge Networks
## 2 Literature Survey  
The privacy preservation in the autonomous transportation system is presented by [PERSON] et al. [2], and similarly for [PERSON] et al. [12]. This work focuses on eliminating the pseudonym-based congestion and trusted authority dependency. Thus, the autonomous protocol to reduce dependency on trusted authority is implemented using bilinear maps, elliptic curve discrete logarithm problem (ECDLP), collusion attack algorithm (CAA), fiatshamir heuristics, and hash chains. The autonomous connectivity between multirobot systems is demonstrated by [PERSON] et al. [13]. This scheme uses trusted identity authentication and the hash-pool-based consensus algorithm. The operations include permuting hash functions in hash pool, random number generator, device IDs, public keys, private keys, and multiple signatures. The JTAG authentication using an autonomous algorithm is presented by [PERSON] et al. [14]. This work has a lightweight plug-and-play solution for automated test equipment with two cryptographic hashes algorithms and claims to be better than the SHA3 algorithm. An autonomous protocol for distributed IoT security by smart contract is demonstrated by [PERSON] et al. [15]. This work design consists of an ethereum smart-contract-based security model while keeping it independent of network connections and acts as a generic task creator with reporting. The peer-to-peer (P2P) autonomous authentication scheme is presented by [PERSON]. [16]. The anonymous access problem is resolved by using group identification and support vector machine-based classification. In a decentralized autonomous network, a blockchain-based authentication is demonstrated by [PERSON] et al. [17]. This work overcomes the complexity of cross-domain authentication by using multicertification authority (CA) and a distributed blockchain base for gaining trust. The artificial neural group key synchronization-based security within autonomous vehicles is presented by [PERSON] et al. [18]. The architecture consists of a vehicle-to-everything (V2X) heterogeneous network for information fusion, synchronization using ring framework, B-tree, and triple layer tree parity machines for key exchange processes. The device-to-device (D2D) security by multichannel authentication is demonstrated by [PERSON] et al. [19]. The Diffie-Hellman key exchange is used within optical-link communication with an LED light and camera in a D2D multichannel authentication having full and half duplex modes. The autonomous robot communication security within the shipping network is presented by [PERSON] et al. [20]. The robots are used for parcel delivery using QR codes, hash functions, and asymmetric encryption, whereas, the Siamese network performs noncooperative user identification and re-identification. The autonomous vehicle applications in smart farming are presented by [PERSON] et al. [21]. The complete automation of smart farming is achieved by ISO 7798-2 security specifications--heterogeneous swarms are used in cloud middleware to operate drones, autonomous vehicles, etc. Autonomous-vehicle secure connectivity using IoT devices and key management framework is demonstrated by [PERSON] et al. [22]. The vehicular network authentication is performed by blockchain based on hash graphs that can perform thousands of transactions per second and a framework designed using batch rekeying and logical key hierarchy (LKH). The 5G cooperative autonomous connectedness and driving is presented by [PERSON] et al. [23]. This system uses 5G-based extensive authentication protocol (EAP) supporting 3 GPP and non-3 GPP communication networks, independent access, and mobility management function with session management function. The autonomous communication within the P2P network is demonstrated by [PERSON] et al. [24]. A distributed hash table for agent lookup is shared by all the communicating agents and uses public-key cryptography for secure P2P communication with end-to-end encryption.