Katerina Mitrokotsa
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Prof. Dr.
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Mitrokotsa
First name
Katerina
Email
katerina.mitrokotsa@unisg.ch
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+41 71 224 7861
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https://twitter.com/mitrokat
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  • Publication
    A Delegated Proof of Proximity Scheme for Industrial Internet of Things Consensus
    (IEEE, 2020-10-18)
    Ledwaba, Lehlogonolo
    ;
    Hancke, Gerhard P.
    ;
    Mitrokotsa, Aikaterini
    ;
    Isaac, Sherrin J.
    Recently, work with Distributed Ledger Technologies (DLTs) has focussed on leveraging the decentralised, immutable ledger for use outside of cryptocurrency. One industry poised to benefit from DLTs is the Industrial Internet of Things (IIoT); as the inherent cryptographic mechanisms and alternative trust model make DLTs an attractive solution for distributed networks. Existing DLTs are unsuitable for the IIoT, owing to the large computational and energy requirements for consensus operations and the slow throughput of validated blocks. With limited processing, energy and storage resources and a deadline sensitive operational environment, DLTs in their current state could serve to introduce intolerable latency into IIoT processes and deplete constrained, device resources. Designed for the IIoT context, and based off Delegated Proof of Stake, this work serves to introduce a new consensus mechanism called Delegated Proof of Proximity (DPoP). Using existing location discovery processes, nodes in close proximity to a sensor event are elected as delegates; whose role is to handle consensus and block generation. In using information already known to IIoT devices, DPoP aims to reduce wasted effort, improve throughput by limiting the number of nodes required for consensus operations and improve scalability and flexibility of DLT solutions as the IIoT network continues to grow.
    Type: conference paper
    DOI: 10.1109/IECON43393.2020.9254661
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/111675
    Scopus© Citations 4
  • Publication
    Differential Privacy meets Verifiable Computation: Achieving Strong Privacy and Integrity Guarantees
    ( 2019)
    Tsaloli, Georgia
    ;
    Mitrokotsa, Aikaterini
    Often service providers need to outsource computations on sensitive datasets and subsequently publish statistical results over a population of users. In this setting, service providers want guarantees about the correctness of the computations, while individuals want guarantees that their sensitive information will remain private. Encryption mechanisms are not sufficient to avoid any leakage of information, since querying a database about individuals or requesting summary statistics can lead to leakage of information. Differential privacy addresses the paradox of learning nothing about an individual, while learning useful information about a population. Verifiable computation addresses the challenge of proving the correctness of computations. Although verifiable computation and differential privacy are important tools in this context, their interconnection has received limited attention. In this paper, we address the following question: How can we design a protocol that provides both differential privacy and verifiable computation guarantees for outsourced computations? We formally define the notion of verifiable differentially private computation (VDPC) and what are the minimal requirements needed to achieve VDPC. Furthermore, we propose a protocol that provides verifiable differentially private computation guarantees and discuss its security and privacy properties.
    Type: conference paper
    URL: https://doi.org/10.5220/0007919404250430
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/99692
  • Publication
    Sum It Up: Verifiable Additive Homomorphic Secret Sharing
    ( 2019)
    Tsaloli, Georgia
    ;
    Mitrokotsa, Aikaterini
    In many situations, clients (e.g., researchers, companies, hospitals) need to outsource joint computations based on joint inputs to external cloud servers in order to provide useful results. Often clients want to guarantee that the results are correct and thus, an output that can be publicly verified is required. However, important security and privacy challenges are raised, since clients may hold sensitive information and the cloud servers can be untrusted. Our goal is to allow the clients to protect their secret data, while providing public verifiability i.e., everyone should be able to verify the correctness of the computed result. In this paper, we propose three concrete constructions of verifiable additive homomorphic secret sharing (VAHSS) to solve this problem. Our instantiations combine an additive homomorphic secret sharing (HSS) scheme, which relies on Shamir’s secret sharing scheme over a finite field
    Type: conference paper
    URL: https://doi.org/10.1007/978-3-030-40921-0\_7
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/99693