Abstract

The ubiquitous networks bring lots of convenience to consumers and service providers for their service communications but have strong privacy issues. Such network environments are unobtrusive and imperceptible to the consumer, where services are provided through an omnipresent way in smart environments. It raises numerous privacy and security issues for consumers. Privacy of service communicating entities needs to be preserved from malicious entities in the context of three-fold privacy threat - identity, location, behavioural privacy threat of legitimate entities in ubiquitous environment. In this paper, privacy preservation is explored with two levels of anonymization by a 2-degree anonymity approach through trust circle of one service entity in service communication. Our proposal provides the personalization in-between anonymity and trust. Simulation results exhibit the effectiveness of our proposal in the considered environment with the “ADULT” database and “Facebook” data set of two Universities, Amherst, and Colgate.

Highlights

  • Ubiquitous networks [39] has been integrated with our daily life due to its dynamic nature and communicable platform

  • In a ubiquitous network environment [39], one service is served by the service provider after service discovery [38] that initiated by consumers, and sometimes initiated by the advertisement of service providers

  • We have focused on the hop-by-hop progressive trust model so that trust or belief level does not decay with the increase of hop-count with the non-interactive recommended entities

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Summary

INTRODUCTION

Ubiquitous networks [39] has been integrated with our daily life due to its dynamic nature and communicable platform. For preserving privacy from malicious activity, two levels of anonymization are introduced by our proposed 2-degree anonymity through the trust circle of every service entity in ubiquitous networks. In [41], authors introduced a centralized global reputation system that computes the global reputation of the caller by weighted aggregation of the local reputation scores provided by the respective collaborating SPs without compromising the privacy They strip off some private information of call record and uses k anonymized out-degree along with pseudo-identity of users to preserve the privacy. An improved k-value is proposed in [7] to overcome the difficulties of choosing suitable k in personalized k-anonymity approaches This model connects the user and location-based service provider, based on the trusted third-party model. Our context-dependent direct and indirect trust evaluation is used to create, expand, and modify their trust circle concerning time

CONTRIBUTIONS The main contributions of our work are summarized as follows
TRUST CIRCLE ESTABLISHMENT
1: Initialize Hcur to 0 2
2: Decides Afactor based on ambiguity requirement
3: AlO Select WI
VIII. COMPLEXITY ANALYSIS
SIMULATION
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