Towards attack-resistant Aggregate Computing using trust mechanisms.
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| Title: | Towards attack-resistant Aggregate Computing using trust mechanisms. |
|---|---|
| Authors: | Casadei, Roberto1 roby.casadei@unibo.it, Aldini, Alessandro2, Viroli, Mirko1 |
| Source: | Science of Computer Programming. Dec2018, Vol. 167, p114-137. 24p. |
| Subjects: | Cyberterrorism, Internet of things, Computer software execution, Algorithms, Pattern recognition systems, Peer-to-peer architecture (Computer networks) |
| Abstract: | Abstract Recent trends such as the Internet of Things and pervasive computing demand for novel engineering approaches able to support the specification and scalable runtime execution of adaptive behaviour for large collections of interacting devices. Aggregate Computing is one such approach, formally founded in the field calculus, which enables programming of device aggregates by a global stance, through functional composition of self-organisation patterns that is turned automatically into repetitive local computations and gossip-like interactions. However, the logically decentralised and open nature of such algorithms and systems presumes a fundamental cooperation of the devices involved: an error in a device or a focused attack may significantly compromise the computation outcome and hence the algorithms built on top. For this reason, in this paper, we move the first steps towards attack-resistant aggregate computations. We propose trust as a framework to detect, ponder or isolate voluntary/involuntary misbehaviours, with the goal of mitigating the influence on the overall computation. On top of this, we consider recommendations in order to provide more reactivity and stability through the sharing of individual perceptions. To better understand the fragility of aggregate systems in face of attacks and investigate the extent of the mitigation afforded by the adoption of trust mechanisms, we consider the paradigmatic case of the gradient algorithm. Experiments are carried out to analyse the sensitivity of the adopted trust framework to malevolent actions and to study the impact of different factors on the error committed by trust-based gradients under attack. Finally, in a case study of the spatial channel algorithm, it is shown how the protection afforded by attack-resistant gradients can be effectively propagated to higher-level building blocks. Highlights • We consider the problem of security in the context of Aggregate Computing. • We propose trust as a framework to build attack-resistant aggregate computations. • We analyse the proposed approach for the case of the self-healing gradient algorithm. • We describe a field-calculus implementation of trust and recommendations. • We show that protection can be extended downstream to higher-level building blocks. [ABSTRACT FROM AUTHOR] |
| Copyright of Science of Computer Programming is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 132199401 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Towards attack-resistant Aggregate Computing using trust mechanisms. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Casadei%2C+Roberto%22">Casadei, Roberto</searchLink><relatesTo>1</relatesTo><i> roby.casadei@unibo.it</i><br /><searchLink fieldCode="AR" term="%22Aldini%2C+Alessandro%22">Aldini, Alessandro</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Viroli%2C+Mirko%22">Viroli, Mirko</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Science+of+Computer+Programming%22">Science of Computer Programming</searchLink>. Dec2018, Vol. 167, p114-137. 24p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Cyberterrorism%22">Cyberterrorism</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+of+things%22">Internet of things</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software+execution%22">Computer software execution</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Pattern+recognition+systems%22">Pattern recognition systems</searchLink><br /><searchLink fieldCode="DE" term="%22Peer-to-peer+architecture+%28Computer+networks%29%22">Peer-to-peer architecture (Computer networks)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract Recent trends such as the Internet of Things and pervasive computing demand for novel engineering approaches able to support the specification and scalable runtime execution of adaptive behaviour for large collections of interacting devices. Aggregate Computing is one such approach, formally founded in the field calculus, which enables programming of device aggregates by a global stance, through functional composition of self-organisation patterns that is turned automatically into repetitive local computations and gossip-like interactions. However, the logically decentralised and open nature of such algorithms and systems presumes a fundamental cooperation of the devices involved: an error in a device or a focused attack may significantly compromise the computation outcome and hence the algorithms built on top. For this reason, in this paper, we move the first steps towards attack-resistant aggregate computations. We propose trust as a framework to detect, ponder or isolate voluntary/involuntary misbehaviours, with the goal of mitigating the influence on the overall computation. On top of this, we consider recommendations in order to provide more reactivity and stability through the sharing of individual perceptions. To better understand the fragility of aggregate systems in face of attacks and investigate the extent of the mitigation afforded by the adoption of trust mechanisms, we consider the paradigmatic case of the gradient algorithm. Experiments are carried out to analyse the sensitivity of the adopted trust framework to malevolent actions and to study the impact of different factors on the error committed by trust-based gradients under attack. Finally, in a case study of the spatial channel algorithm, it is shown how the protection afforded by attack-resistant gradients can be effectively propagated to higher-level building blocks. Highlights • We consider the problem of security in the context of Aggregate Computing. • We propose trust as a framework to build attack-resistant aggregate computations. • We analyse the proposed approach for the case of the self-healing gradient algorithm. • We describe a field-calculus implementation of trust and recommendations. • We show that protection can be extended downstream to higher-level building blocks. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Science of Computer Programming is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.scico.2018.07.006 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 114 Subjects: – SubjectFull: Cyberterrorism Type: general – SubjectFull: Internet of things Type: general – SubjectFull: Computer software execution Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Pattern recognition systems Type: general – SubjectFull: Peer-to-peer architecture (Computer networks) Type: general Titles: – TitleFull: Towards attack-resistant Aggregate Computing using trust mechanisms. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Casadei, Roberto – PersonEntity: Name: NameFull: Aldini, Alessandro – PersonEntity: Name: NameFull: Viroli, Mirko IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 01676423 Numbering: – Type: volume Value: 167 Titles: – TitleFull: Science of Computer Programming Type: main |
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