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Details

  • Name

    Patrícia Raquel Sousa
  • Cluster

    Computer Science
  • Role

    Research Assistant
  • Since

    01st May 2016
001
Publications

2019

pTASC: trustable autonomous secure communications

Authors
Sousa, PR; Cirne, A; Resende, JS; Martins, R; Antunes, L;

Publication
Proceedings of the 20th International Conference on Distributed Computing and Networking, ICDCN 2019, Bangalore, India, January 04-07, 2019

Abstract

2019

pTASC

Authors
Sousa, PR; Cirne, A; Resende, JS; Martins, R; Antunes, L;

Publication
Proceedings of the 20th International Conference on Distributed Computing and Networking - ICDCN '19

Abstract

2019

PTASC: Trustable autonomous secure communications

Authors
Sousa, PR; Cirne, A; Resende, JS; Martins, R; Antunes, L;

Publication
ACM International Conference Proceeding Series

Abstract
The number of devices connected to the Internet has been increasing exponentially. There is a substantial amount of data being exchanged among numerous connected devices. The added convenience brought by these devices spans across multiple facets of everyday life, such as drivers reporting an accident through dash cams, patients monitoring their own health, and companies controlling the safety of their facilities. However, it is critical to increase safety and privacy across the data generated and propagated by these devices. Previous works have focused mainly on device management and relied on centralized solutions namely Public Key Infrastructure (PKI). This paper describes a novel mechanism that ensures secure autonomous communication between Internet of Things (IoT) devices, while using a completely decentralized solution that mitigates the classical single points-of-failure problem. This is accomplished by a new peer-to-peer protocol using Short Authentication Strings (SAS), in which verification is made through a Limited-Location Channel (LLC). © 2019 Association for Computing Machinery.

2019

Breaking MPC implementations through compression

Authors
Resende, JS; Sousa, PR; Martins, R; Antunes, L;

Publication
International Journal of Information Security

Abstract
There are many cryptographic protocols in the literature that are scientifically and mathematically sound. By extension, cryptography today seeks to respond to numerous properties of the communication process beyond confidentiality (secrecy), such as integrity, authenticity, and anonymity. In addition to the theoretical evidence, implementations must be equally secure. Due to the ever-increasing intrusion from governments and other groups, citizens are now seeking alternatives ways of communication that do not leak information. In this paper, we analyze multiparty computation (MPC), which is a sub-field of cryptography with the goal of creating methods for parties to jointly compute a function over their inputs while keeping those inputs private. This is a very useful method that can be used, for example, to carry out computations on anonymous data without having to leak that data. Thus, due to the importance of confidentiality in this type of technique, we analyze active and passive attacks using complexity measures (compression and entropy). We start by obtaining network traces and syscalls, then we analyze them using compression and entropy techniques. Finally, we cluster the traces and syscalls using standard clustering techniques. This approach does not need any deep specific knowledge of the implementations being analyzed. This paper presents a security analysis for four MPC frameworks, where three were identified as insecure. These insecure libraries leak information about the inputs provided by each party of the communication. Additionally, we have detected, through a careful analysis of its source code, that SPDZ-2’s secret sharing schema always produces the same results. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

2018

Evaluating the Privacy Properties of Secure VoIP Metadata

Authors
Resende, JS; Sousa, PR; Antunes, L;

Publication
Trust, Privacy and Security in Digital Business - Lecture Notes in Computer Science

Abstract