## 4 Proposed Scheme
### Integration into Distributed Applications
#### 4.7.3 Application Example: IoT Authentication  
To secure communications and authenticate devices, it is necessary to stage three elements: creating a safe zone through security policies, authenticating the entities involved, and securing communications. In the particular case of IoT ecosystems, the centralization of calculations for cryptographic primitives is used. When interacting in distributed environments, such as blockchain, and certain centralizations are not possible, double authentication is necessary, with the generation of cryptographic primitives on each participating system. The proposed scheme allows device authentication and protects sensitive information by implementing customizable anonymity. At the same time, this can be achieved through multiple nodes, to create a degree of system scalability. Suppose a network of smart electricity meters is required to regularly transmit consumption data to a central server and then to a blockchain network for storage and verification. In this case, the meters must verify their authenticity without revealing individual consumer data. For this particular case, the customization of the proposed solution will be performed as follows:  
The authentication steps are  
1. Message generation \(M\): Each meter generates a message \(M\) that contains information about energy consumption (for example, \(M\) = consumption: 327 kWh). 2. Message obfuscation: To protect sensitive data, the meter applies obfuscation: \[M^{\prime}=M\cdot r(mod\ n),\] where \(r\) is a secret random factor, and \(n\) is the cryptographic modulus used by the signature scheme. 3. Transmitting the obfuscated message: The obfuscated message \(M^{\prime}\) is sent to the central server, which plays the role of signer. 4. Signing the blinded message: The server applies the signature using the private key \(K_{priv}\) : \[\sigma^{\prime}=(M^{\prime})^{K_{priv}}(mod\ n)\] The parameter \(T\) is adjusted to control the level of anonymity. For example, * \(T\) high: The signature ensures complete anonymity of the meter. * \(T\) low: The signature allows the device to be identified for auditing. 5. Transmitting the blinded signature: The server returns the signature \(\sigma^{\prime}\) to the meter. 6. Removing the blinded: The meter reverses the blinded signature to obtain the final signature: \[\sigma=\sigma^{\prime}\cdot r^{-1}(mod\ n).\] The signature \(\sigma\) is now valid for the original message \(M\). 7. Transmission to blockchain: The message \(M\) and the signature \(\sigma\) are transmitted to the blockchain for validation and distributed storage. Blockchain nodes verify the signature \(\sigma\) using the public key \(K_{pub}\):  
\[\sigma^{e}(mod\ n)=M.\]  
If the equation is satisfied, the message \(M\) is considered authentic and is recorded on the blockchain, the latter storing only the validated information, providing transparency and data integrity. IoT authentication benefits from the proposed method by the possibility of flexible functionality and security standards established in accordance with each subgroup of components participating in the protocol. By adjusting the parameter \(T\), IoT devices canregulate their data confidentiality. High levels of anonymity protect users in residential areas, while industrial applications benefit from transparent processes that allow auditing and monitoring. The computational power is based on basic cryptographic functions, such as blinding and signature operations, which makes the method suitable for devices with minimal computing power. Due to the properties of the distributed model of blockchain technology, a series of scalability features can be provided that allow the simultaneous management of multiple IoT devices. The security mechanism is based on a random factor \(r\) and message blinding to prevent attackers from accessing the original data or determining the signature without the private key \(K_{priv}\).