Wyniki wyszukiwania - BazTech

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System zarządzania zaufaniem dla mobilnych kognitywnych sieci radiowych organizowanych doraźnie

Głowacka J., Krygier J., Amanowicz M.

Przegląd Telekomunikacyjny + Wiadomości Telekomunikacyjne

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2016

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nr 8-9

756--760, CD

PL

W artykule przedstawiono propozycję systemu zarządzania zaufaniem dla mobilnych sieci organizowanych doraźnie wyposażonych w funkcjonalność budowania wiedzy o otoczeniu na podstawie tzw. cyklu kognitywnego. System ten umożliwia obserwację ruchu sygnalizacyjnego przez poszczególne węzły oraz klasyfikację pozostałych węzłów, która wyznacza poziom zaufania do otoczenia. Dzięki odpowiedniej reakcji możliwe jest zwiększenie poziomu bezpieczeństwa w sieciach kognitywnych.

EN

The paper presents the reputation system for mobile cognitive radio ad-hoc networks. The system is able to recognize the attacks both on cognitive signaling and reputation system. Based on the appropriate nodes classification and reaction the security of the network is increased.

2

Hidden and Indirect (Probabilistically Estimated) Reputations - Hiper Method

Leszczyński K., Zakrzewicz M.

Foundations of Computing and Decision Sciences

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2015

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Vol. 40, No. 1

35--51

EN

It is a challenge to design a well balanced reputation system for an environment with millions of users. A reputation system must also represent user reputation as a value which is simple and easy to compare and will give users straightforward suggestions who to trust. Since reputation systems rely on feedbacks given by users, it is necessary to collect unbiased feedbacks. In this paper we present a controversial, yet innovative reputation system. Hidden and Indirect (Probabilistically Estimated) Reputations - HIPER Method splits user reputation into two related values: Hidden Reputation (HR) is directly calculated from a set of feedbacks, Indirect Reputation (IR) is a probabilistically estimated projection of the hidden reputation and its value is public. Such indirect connection between received feedbacks and a visible reputation value allows users to provide unbiased feedbacks without fear of retaliation.

3

Asymptotic trust algorithm: extension for reputation systems in online auctions

Leszczyński K., Zakrzewicz M.

Control and Cybernetics

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2011

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Vol. 40, no 3

651-666

EN

Online auctions have become a big business and the number of auction site users is growing rapidly. These virtual marketplaces give traders a lot of opportunities to find a contracting party. However, lack of physical contact between users decreases the degree of trust. Auction portals require an efficient mechanism for building trust between participants, whereas most of them provide simple participation counts for reputation rating. Moreover, a single opinion has virtually no effect on a big online store that already has many reputation points, so buyers are very hesitant to give negative feedback for fear of retaliation. Consequently, almost no negative feedback is provided1. In this paper we introduce a new trust system called Asymptotic Trust Algorithm (ATA) which prevents many fraud attempts and still is both simple and easy to understand for most users. Our new method can be applied in addition to the participation counts systems currently used by Allegro, eBay and most of other online auction sites because it does not require any additional information other than positive, negative or neutral feedback on transactions. Most importantly, ATA encourages users to submit unbiased comments, regardless of the number of previous transactions.

4

A Framework for Detection of Selfishness in Multihop Mobile Ad Hoc Networks

Konorski J., Orlikowski R.

Journal of Telecommunications and Information Technology

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2009

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nr 2

34-40

EN

The paper discusses the need for a fully-distributed selfishness detection mechanism dedicated for multihop wireless ad hoc networks which nodes may exhibit selfish forwarding behavior. The main contribution of this paper is an introduction to a novel approach for detecting and coping with the selfish nodes. Paper describes a new framework based on Dempster-Shafer theory-based selfishness detection framework (DST-SDF) with some mathematical background and simulation analysis.