# Resource Management and Secure Data Exchange for Mobile Sensors Using Ethereum Blockchain
## 4 Methodology
### Validation of MS Identity
\[[s(pub_{j}),\;s(incog_{j})]=[h_{4},h_{5}] \tag{6}\]  
Equation (6) shows that the generation of the updated public key of the mobile sensor, i.e., \(s(pub_{j})\), is carried out by considering attribute \(h_{4}\), which represents the product of the private key of the mobile sensor \(s\big{(}priv_{j}\big{)}\) and the reference variable of the finite field \(\Omega\). Furthermore, it is shown that the generation of the incognito coefficient \(s(incog_{j})\) of the mobile sensor is performed using attribute \(h_{5}\), which represents a hashing method applied to the value obtained from the concatenation of the identity of sensor \(s(iden_{j})\) and an arbitrary number of sensors \(\pi_{j}\). The incognito coefficient is a substitute or alternative name adopted in the proposed system to hide an entity's true identity and susceptible information using mobile sensors. Its purpose is to provide anonymity and privacy in digital transactions and communications. The incognito coefficient can be useful when individuals want to interact with others while keeping their real identities concealed. Furthermore, incognito coefficients can be generated using cryptographic techniques to prevent traceability, which can be linked to the original identity. This allows individuals to participate in transactions or communications without revealing personal information. The incognito coefficient can also be crucial in various cryptographic systems, including anonymous cryptocurrencies, privacy-preserving communication protocols, and secure authentication schemes. Figure 3 shows the complete process of enrolling and validating the mobile sensors, which mainly exhibits the process of enrolling AP (Figure 3a), the process of enrolling mobile sensors (Figure 3b), and the validation process of each mobile sensor (Figure 3c). A digital certificate \(sc_{i}\) is generated by GN, followed by configuring the preliminary trust score \(tr_{j}^{prelim}\). This means that there are various ranges of security information embedded in the form of the trust score \(tr_{j}\), digital certificate \(sc_{i}\), incognito coefficient \(s(incog_{j})\), public key \(s(pub_{j})\), and private key \(s(priv_{j})\). GN disseminates the embedded information to each mobile sensor. The content of the information can be acquired by the mobile sensor either using the N2N or the N2S mode of communication. The mobile sensors perform validation checks for other nodes before communicating concerning their identities. When the mobile sensor \(s_{j}\) is interested in communicating with another node, a request must be made for this intended communication to the \(AP_{j}\) and the target mobile sensor. In such cases, the source mobile sensor encrypts its incognito coefficient \(s(incog_{j})\) using a one-way hash function. A similar hashing operation is performed for a digital certificate \(sc_{i}\) and public key \(s(pub_{j})\) that forms a security token \(tok_{j}\) followed by the application of a digital signature to generate a security token \(tok_{j}\) to generate a user signature \(s(sig_{j})\). The  
Figure 3: Enrollment and validation of sensor. digital signature \(s(sig_{j})\) can be opened by the access point \(AP_{j}\) with the aid of the extracted public key \(s(pub_{j})\). Using this procedure, the security token \(tok_{ji}\) is obtained, followed by authentication of the equivalency of the security token \(tok_{ji}\) with \(tok_{j}\). However, the authenticity of the digital certificate \(sc_{i}\) is determined by the access point \(AP_{j}\) in Ethereum. Concurrently, it responds with either successful or failed authentication flags to the user, i.e., mobile sensor \(s\). Similarly, the other sensor node decrypts the digital signature \(s(sig_{j})\) using its public key \(s(pub)\) to acquire the security token \(tok_{j}\). The system further checks the equivalency of \(s(tok_{j})\) to be the same as \(s(tok_{jo})\).