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    Rights statement: NOTICE: this is the author's version of a work that was accepted for publication in Engineering Applications of Artificial Intelligence. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published: Jose M. Such, Ana Garcia-Fornes, Agustin Espinosa and Joan Bellver. Magentix2: a Privacy-enhancing Agent Platform. Engineering Applications of Artificial Intelligence, Vol. 26 N. 1 pp. 96-109 (2013), © ELSEVIER.

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Magentix2: a privacy-enhancing agent platform

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Magentix2: a privacy-enhancing agent platform. / Such, Jose M.; Garcia-Fornes, Ana; Espinosa, Agustin et al.
In: Engineering Applications of Artificial Intelligence, Vol. 26, No. 1, 01.2013, p. 96-109.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Such, JM, Garcia-Fornes, A, Espinosa, A & Bellver, J 2013, 'Magentix2: a privacy-enhancing agent platform', Engineering Applications of Artificial Intelligence, vol. 26, no. 1, pp. 96-109. https://doi.org/10.1016/j.engappai.2012.06.009

APA

Such, J. M., Garcia-Fornes, A., Espinosa, A., & Bellver, J. (2013). Magentix2: a privacy-enhancing agent platform. Engineering Applications of Artificial Intelligence, 26(1), 96-109. https://doi.org/10.1016/j.engappai.2012.06.009

Vancouver

Such JM, Garcia-Fornes A, Espinosa A, Bellver J. Magentix2: a privacy-enhancing agent platform. Engineering Applications of Artificial Intelligence. 2013 Jan;26(1):96-109. doi: 10.1016/j.engappai.2012.06.009

Author

Such, Jose M. ; Garcia-Fornes, Ana ; Espinosa, Agustin et al. / Magentix2 : a privacy-enhancing agent platform. In: Engineering Applications of Artificial Intelligence. 2013 ; Vol. 26, No. 1. pp. 96-109.

Bibtex

@article{2cc222056d474802baa8388c75fd99f5,
title = "Magentix2: a privacy-enhancing agent platform",
abstract = "Agent Platforms are the software that supports the development and execution of Multi-agent Systems. There are many Agent Platforms developed by the agent community, but they hardly consider privacy. This leads to agent-based applications that invade users{\textquoteright} privacy. Privacy can be threatened by two main information activities: information collection and information processing. Information collection can be prevented using traditional security mechanisms. Information processing can be prevented by minimizing data identifiability, i.e., the degree by which personal information can be directly attributed to a particular individual. However, minimizing data identifiability may directly affect other crucial issues in Multi-agent Systems, such as accountability, trust, and reputation. In this paper, we present the support that the Magentix2 Agent Platform provides for preserving privacy. Specifically, it provides mechanisms to avoid information collection and information processing when they are not desired. Moreover, Magentix2 provides these mechanisms without compromising accountability, trust, and reputation. We also provide in this paper an application built on top of Magentix2 that exploits its support for preserving privacy. Finally, we provide an extensive evaluation of the support that Magentix2 provides for preserving privacy based on that application. We specifically test whether or not privacy loss can be minimized by using the support that Magentix2 provides, whether or not this support introduces a bearable performance overhead, and whether or not existing trust and reputation models can be implemented on top of Magentix2.",
keywords = "Privacy, Agent Platforms , Multi-agent Systems , Security , Trust , Reputation",
author = "Such, {Jose M.} and Ana Garcia-Fornes and Agustin Espinosa and Joan Bellver",
note = "NOTICE: this is the author's version of a work that was accepted for publication in Engineering Applications of Artificial Intelligence. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published: Jose M. Such, Ana Garcia-Fornes, Agustin Espinosa and Joan Bellver. Magentix2: a Privacy-enhancing Agent Platform. Engineering Applications of Artificial Intelligence, Vol. 26 N. 1 pp. 96-109 (2013), {\textcopyright} ELSEVIER.",
year = "2013",
month = jan,
doi = "10.1016/j.engappai.2012.06.009",
language = "English",
volume = "26",
pages = "96--109",
journal = "Engineering Applications of Artificial Intelligence",
issn = "0952-1976",
publisher = "Elsevier Limited",
number = "1",

}

RIS

TY - JOUR

T1 - Magentix2

T2 - a privacy-enhancing agent platform

AU - Such, Jose M.

AU - Garcia-Fornes, Ana

AU - Espinosa, Agustin

AU - Bellver, Joan

N1 - NOTICE: this is the author's version of a work that was accepted for publication in Engineering Applications of Artificial Intelligence. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published: Jose M. Such, Ana Garcia-Fornes, Agustin Espinosa and Joan Bellver. Magentix2: a Privacy-enhancing Agent Platform. Engineering Applications of Artificial Intelligence, Vol. 26 N. 1 pp. 96-109 (2013), © ELSEVIER.

PY - 2013/1

Y1 - 2013/1

N2 - Agent Platforms are the software that supports the development and execution of Multi-agent Systems. There are many Agent Platforms developed by the agent community, but they hardly consider privacy. This leads to agent-based applications that invade users’ privacy. Privacy can be threatened by two main information activities: information collection and information processing. Information collection can be prevented using traditional security mechanisms. Information processing can be prevented by minimizing data identifiability, i.e., the degree by which personal information can be directly attributed to a particular individual. However, minimizing data identifiability may directly affect other crucial issues in Multi-agent Systems, such as accountability, trust, and reputation. In this paper, we present the support that the Magentix2 Agent Platform provides for preserving privacy. Specifically, it provides mechanisms to avoid information collection and information processing when they are not desired. Moreover, Magentix2 provides these mechanisms without compromising accountability, trust, and reputation. We also provide in this paper an application built on top of Magentix2 that exploits its support for preserving privacy. Finally, we provide an extensive evaluation of the support that Magentix2 provides for preserving privacy based on that application. We specifically test whether or not privacy loss can be minimized by using the support that Magentix2 provides, whether or not this support introduces a bearable performance overhead, and whether or not existing trust and reputation models can be implemented on top of Magentix2.

AB - Agent Platforms are the software that supports the development and execution of Multi-agent Systems. There are many Agent Platforms developed by the agent community, but they hardly consider privacy. This leads to agent-based applications that invade users’ privacy. Privacy can be threatened by two main information activities: information collection and information processing. Information collection can be prevented using traditional security mechanisms. Information processing can be prevented by minimizing data identifiability, i.e., the degree by which personal information can be directly attributed to a particular individual. However, minimizing data identifiability may directly affect other crucial issues in Multi-agent Systems, such as accountability, trust, and reputation. In this paper, we present the support that the Magentix2 Agent Platform provides for preserving privacy. Specifically, it provides mechanisms to avoid information collection and information processing when they are not desired. Moreover, Magentix2 provides these mechanisms without compromising accountability, trust, and reputation. We also provide in this paper an application built on top of Magentix2 that exploits its support for preserving privacy. Finally, we provide an extensive evaluation of the support that Magentix2 provides for preserving privacy based on that application. We specifically test whether or not privacy loss can be minimized by using the support that Magentix2 provides, whether or not this support introduces a bearable performance overhead, and whether or not existing trust and reputation models can be implemented on top of Magentix2.

KW - Privacy

KW - Agent Platforms

KW - Multi-agent Systems

KW - Security

KW - Trust

KW - Reputation

U2 - 10.1016/j.engappai.2012.06.009

DO - 10.1016/j.engappai.2012.06.009

M3 - Journal article

VL - 26

SP - 96

EP - 109

JO - Engineering Applications of Artificial Intelligence

JF - Engineering Applications of Artificial Intelligence

SN - 0952-1976

IS - 1

ER -