Univerza na Primorskem
Fakulteta za matematiko, naravoslovje in informacijske tehnologije
Več informacij o projektu / More info about the project
Opis / Description
SLO:
Hitro širjenje interneta stvari (IoT) prinaša tako priložnosti kot izzive. Kljub ustvarjanju ogromnih količin dragocenih podatkov naprave IoT te podatke pogosto pustijo neizkoriščene zaradi skrbi glede varnosti, zasebnosti, zaupanja in pomanjkanja spodbud za deljenje. Ta projekt si prizadeva napredovati tehnologijo proti decentralizirani arhitekturi, ki omogoča lastnikom naprav IoT deljenje njihovih podatkovnih virov za analitiko, hkrati pa zagotavlja varnost, zasebnost in zaupanje med proizvajalci in porabniki podatkov.
Da bi to dosegli, naše raziskave temeljijo na protokolu za večstranska računanja (MPC), ki omogoča omrežnim vozliščem skupno računanje poljubnih funkcij brez razkritja njihovih zasebnih vhodov. Protokol uporablja večplastno šifriranje za zagotovitev enakomerno porazdeljenega omrežnega prometa in omejiti informacijo, ki lahko tuji akter pridobi z nadzorovanjem komunikacij. Z integracijo MPC z samostojno identiteto (SSI) in tehnologijo porazdeljene knjige (DLT) si prizadevamo ustvariti robustno arhitekturo, ki lastnikom IoT omogoča razkrivanje in monetizacijo njihovih podatkov za analitiko, hkrati pa ohranja surove podatke zasebne. Ključni raziskovalni cilji vključujejo razvoj mehanizmov zaupanja, izvedbo študij izvedljivosti za velike IoT mreže ter izvajanje celovitih varnostnih evalvacij. Z integracijo sistema, ki temelji na spodbudah z uporabo DLT, si prizadevamo spodbuditi deljenje podatkov in sodelovanje znotraj omrežja. Rezultati projekta bodo potrjeni s prototipno implementacijo in rigorozno evalvacijo, s čimer bomo zagotovili razširljivost, učinkovitost in robustnost rešitve v IoT okolju.
EN:
The rapid expansion of the Internet of Things (IoT) brings both opportunities and challenges. Despite generating vast amounts of valuable data, IoT devices often leave these data underutilized due to concerns regarding security, privacy, trust, and the lack of incentives for data sharing. This project aims to advance the technology toward a decentralized architecture that enables IoT device owners to share their data resources for analytics while ensuring security, privacy, and trust between data producers and consumers.
To achieve this, our research is based on a Multi-Party Computation (MPC) protocol that enables network nodes to jointly compute arbitrary functions without revealing their private inputs. The protocol employs multi-layer encryption to ensure evenly distributed network traffic and to limit the information that a foreign actor can obtain by monitoring communications. By integrating MPC with Self-Sovereign Identity (SSI) and Distributed Ledger Technology (DLT), we aim to create a robust architecture that enables IoT owners to disclose and monetize their data for analytics while keeping the raw data private. Key research objectives include the development of trust mechanisms, conducting feasibility studies for large-scale IoT networks, and performing comprehensive security evaluations. By integrating an incentive-based system using DLT, we aim to encourage data sharing and collaboration within the network. The project results will be validated through a prototype implementation and rigorous evaluation, ensuring the scalability, efficiency, and robustness of the solution in an IoT environment.
To achieve this, our research is based on a Multi-Party Computation (MPC) protocol that enables network nodes to jointly compute arbitrary functions without revealing their private inputs. The protocol employs multi-layer encryption to ensure evenly distributed network traffic and to limit the information that a foreign actor can obtain by monitoring communications. By integrating MPC with Self-Sovereign Identity (SSI) and Distributed Ledger Technology (DLT), we aim to create a robust architecture that enables IoT owners to disclose and monetize their data for analytics while keeping the raw data private. Key research objectives include the development of trust mechanisms, conducting feasibility studies for large-scale IoT networks, and performing comprehensive security evaluations. By integrating an incentive-based system using DLT, we aim to encourage data sharing and collaboration within the network. The project results will be validated through a prototype implementation and rigorous evaluation, ensuring the scalability, efficiency, and robustness of the solution in an IoT environment.