CONCEPTUAL ARCHITECTURE AND FORMAL MODEL OF SELF-SOVEREIGN DIGITAL TWINS IN IoT ECOSYSTEMS

The paper presents a conceptual architecture of self-sovereign digital twins (SSDT) for IoT ecosystems, which provides decentralized management of device identity and data without dependence on centralized providers. The proposed solution eliminates the main shortcomings of traditional IoT systems associated with centralized data storage, provider compromise risks, and lack of privacy guarantees. A three-tier architecture is developed: the physical layer ensures authentic data collection on IoT devices with cryptographic signing; the digital twin layer on the computing gateway implements decentralized identifier (DID) management, credential storage, access policy evaluation, and zero-disclosure evidence generation; the blockchain layer guarantees immutable audit through a private blockchain with fail-safe consensus, smart contracts for the DID registry, credential status management, and access operation logging. The SSDT model is formalized as a tuple that includes a decentralized identifier, a set of attributes, a state function, access policies, cryptographic keys, and transaction history, with clearly defined security invariants. A threat model based on the STRIDE methodology adapted to distributed IoT systems is analyzed. The analysis covers key assets (identities, credentials, telemetry, and private keys) and groups threats into areas: exchange integrity, identity threats, and confidentiality. Man-in-the-Middle attacks, replay attacks, device spoofing, credential forgery, access policy bypass, and key compromise are identified. A set of countermeasures is proposed that includes mutual TLS, cryptographic message signing, timestamps, mandatory DID registration in the blockchain, device attestation, revocation status checking, request frequency limitation, key rotation, and hardware security modules. Zero-disclosure proof mechanisms are used to ensure privacy. The results of the study confirm the possibility of creating scalable, private and self-sovereign IoT device management systems. The architecture provides horizontal scalability, low latency due to edge processing, and privacy by design. The practical value lies in the possibility of application in industrial IoT, personal monitoring systems, and smart cities. Further research directions include formal verification, optimization of ZKP for resource-dependent devices, and compatibility with existing IoT