Transparent Protection of Aggregate Computations from Byzantine Behaviours via Blockchain


Danilo Pianini, Giovanni Ciatto, Roberto Casadei, Stefano Mariani, Mirko Viroli, Andrea Omicini

GOODTECHS'18 – Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good, pages 271–276
ACM, New Work, NY, USA
November 2018

Aggregate Computing is a promising paradigm for coordinating large numbers of possibly situated devices.
It is used, in particular, in scenarios related to the Internet of Things, smart cities, drone fleet coordination, and mass urban events.
Currently, however, little work has been devoted to study and improve security in aggregate programs.
Existing works only focus on application-level countermeasures, typically introducing trust metrics to detect misbehaving devices.
Those security systems work under the assumption that the underlying computational model is respected; however, so-called Byzantine  behaviour violates such assumption.
In this paper, we discuss how Byzantine behaviours can hinder an aggregate program, and exploit application-level protection for creating bigger disruption.
We discuss how the Blockchain technology can mitigate these attacks by enforcing behaviours consistent with the expected operational semantics, with no impact on the application logic.

(keywords) Aggregate Programming, blockchain, security, Byzantine fault tolerance

Events

  • 4th EAI International Conference on Smart Objects and Technologies for Social Good (GOODTECHS 2018) — 28/11/2018–30/11/2018

Tags:

Publication

— authors

— status

published

— sort

paper in proceedings

— publication date

November 2018

— volume

GOODTECHS'18 – Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good

— pages

271–276

— address

New Work, NY, USA

— location

Bologna, Italy

URLs

original page

identifiers

— DOI

10.1145/3284869.3284870

— ACM

10.1145/3284869.3284870

— DBLP

conf/goodtechs/PianiniCC0VO18

— IRIS

11585/655097

— Scholar

3798219571928546753

— Scopus

2-s2.0-85061088949

— WoS / ISI

000470918900046

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