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A Robinson list protects phone subscribers against commercial spam calls. Its least basic functionality is to collect the denial of the subscribers to be contacted by market operators. Nowadays, Robinson lists run as centralised services, which implies that citizens should trust third parties for the management of their choices. In this paper, we show a design that allows us to realise a Robinson list as a decentralised service. Our work leverages the experience developed by Fondazione Ugo Bordoni as the manager of the Italian Robinson list. We present a general solution and a proof-of-concept (PoC) adopting the Algorand technology. We evaluate the performances of our PoC in terms of its scalability and of the latency perceived by the involved actors. We also discuss aspects related to identity management and privacy., This article has been accepted for publication in International Journal of Computers and Applications, published by Taylor & Francis

In many applications, identity management (IdM) is used to associate a subject public key with an endpoint at which the subject can be contacted (telephone number, email, etc.). In decentralized applications based on blockchains, it is desirable for the IdM to be decentralized as well. In certain applications, it is paramount to be certain that an endpoint actually belong to a specific subject. Currently, when this is needed, endpoints are either verified by who needs it, which is impractical in blockchain-based applications, or by a centralized authority, which contrasts with the spirit of the blockchain.In this paper, we show two layer-two blockchain-based protocols to prove the association between a subject and an endpoint in a decentralized manner. Our protocols are compatible with a wide variety of endpoints and contribute to fill the gap of the current self sovereign IdM approaches with respect to decentralization. We analyze the security of our proposals and evaluate performances and costs against the common approaches.

Commercial off-the-shelf DataBase Management Systems (DBMSes) are highly optimized to process a wide range of queries by means of carefully designed indexing and query planning. However, many aggregate range queries are usually performed by DBMSes using sequential scans, and certain needs, like storing Authenticated Data Structures (ADS), are not supported at all. Theoretically, these needs could be efficiently fulfilled adopting specific kinds of indexing, which however are normally ruled-out in DBMSes design. We introduce the concept of overlay index: an index that is meant to be stored in a standard database, alongside regular data and managed by regular software, to complement DBMS capabilities. We show a data structure, that we call DB-tree, that realizes an overlay index to support a wide range of custom aggregate range queries as well as ADSes, efficiently. All DB-trees operations can be performed by executing a small number of queries to the DBMS, that can be issued in parallel in one or two query rounds, and involves a logarithmic amount of data. We experimentally evaluate the efficiency of DB-trees showing that our approach is effective, especially if data updates are limited.

A Robinson list protects users' privacy against the always more frequent spam calls by allowing them to express a consent or a denial about market operator calls. Nowadays, Robinson lists run as centralised services. In this paper we discuss the possibility of implementing this valuable tool as a decentralised service. We identify the requirements of a decentralised Robinson list and the characteristics of a blockchain technology needed to support an implementation. Then, we present a general solution and a proof-of-concept implementation based on the Algorand technology. A preliminary performance evaluation suggest that also in terms of performance we can achieve satisfactory results. The paper is concluded discussing some fundamental aspects related to privacy and identity management and presenting a number of open research challenges that need to be addressed for a successful development of our solution.

Public cloud storage services are widely adopted for their scalability and low cost. However, delegating the management of the storage has serious implications from the security point of view. We focus on integrity verification of query results based on the use of Authenticated Data Structures (ADS). An ADS enables efficient updates of a cryptographic digest, when data changes, and efficient query verification against this digest. Since, the digest can be updated (and usually signed) exclusively with the intervention of a trusted party, the adoption of this approach is source of a serious performance degradation, in particular when the trusted party is far from the server that stores the ADS. In this paper, we show a protocol for a key–value storage service that provides ADS-enabled integrity-protected queries and updates without impairing scalability, even in the presence of large network latencies between trusted clients and an untrusted server. Our solution complies with the principle of the cloud paradigm in which services should be able to arbitrarily scale with respect to number of clients, requests rates, and data size keeping response time limited. We formally prove that our approach is able to detect server misbehaviour in a setting whose consistency rules are only slightly weaker than those guaranteed by previous results. We provide experimental evidence for the feasibility and scalability of our approach.