Privacy Leakage of Location Sharing in Mobile Social Networks: Attacks and Defense

Li, Huaxin; Zhu, Haojin; Du, Suguo; Liang, Xiaohui; Shen, Xuemin

doi:10.1109/tdsc.2016.2604383

Cited by 174 publications

(89 citation statements)

References 36 publications

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“…a nearby restaurant, can exposes its location. From location data and timestamps, a person's demographic information, home and work addresses, commute routes and other habits can be derived [22,23,24] The footprint privacy is about the risks involved with the combination of little pieces of information that are left in a system. For example, when using a web browser to access a web page, the cookie left on a device is a footprint of the web page that can reveal individual's preferences.…”

Section: Privacy In Crowdsensingmentioning

confidence: 99%

Crowdsensing and Privacy in Smart City Applications

Gaire

Ghosh

Kim

et al. 2019

Smart Cities Cybersecurity and Privacy

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Smartness in smart cities is achieved by sensing phenomena of interest and using them to make smart decisions. Since the decision makers may not own all the necessary sensing infrastructures, crowdsourced sensing, can help collect important information of the city in near real-time. However, involving people brings of the risk of exposing their private information.This chapter explores crowdsensing in smart city applications and its privacy implications.

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Section: Privacy In Crowdsensingmentioning

confidence: 99%

Crowdsensing and Privacy in Smart City Applications

Gaire

Ghosh

Kim

et al. 2019

Smart Cities Cybersecurity and Privacy

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show abstract

“…(2) Location trailing attack: Location attacks generally target the privacy of a user in vehicular network by continuously tracking the location of a user. In this attack, position of the vehicle at a given moment or path trace along certain period of time can be used to map out the user [52,59]. (3) Identity revealing: Attacker may try to reveal identity of vehicle's owner.…”

Section: Attacks Related To User's Privacymentioning

confidence: 99%

Lightweight Cryptographic Techniques for Automotive Cybersecurity

Jadoon

Wang

et al. 2018

Wireless Communications and Mobile Computing

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A new integration of wireless communication technologies into the automobile industry has instigated a momentous research interest in the field of Vehicular Ad Hoc Network (VANET) security. Intelligent Transportation Systems (ITS) are set up, aiming to offer promising applications for efficient and safe communication for future automotive technology. Vehicular networks are unique in terms of characteristics, challenges, architecture, and applications. Consequently, security requirements related to vehicular networks are more complex as compared to mobile networks and conventional wireless networks. This article presents a survey about developments in vehicular networks from the perspective of lightweight cryptographic protocols and privacy preserving algorithms. Unique characteristics of vehicular networks are presented which make the embedded security applications computationally hard as well as memory constrained. The current study also deals with the fundamental security requirements, essential for vehicular communication. Furthermore, awareness of security threats and their cryptographic solutions in terms of future automotive industry are discussed. In addition, asymmetric, symmetric, and lightweight cryptographic solutions are summarized. These strategies can be enhanced or incorporated all in all to meet the security perquisites of future cars security.

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“…In MSNs, there are two papers dealing the location privacy [19], [32]. Liang et al [19] proposes a proximity measurement with morality-driven data forwarding.…”

Section: A Location Privacymentioning

confidence: 99%

Privacy-Preserving Schemes for Ad Hoc Social Networks: A Survey

Ferrag

Μαγλαράς

Ahmim

2017

IEEE Commun. Surv. Tutorials

120

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In this paper, we review the state of the art of privacy-preserving schemes for ad hoc social networks, including, mobile social networks (MSNs) and vehicular social networks (VSNs). Specifically, we select and in-detail examine thirty-three privacypreserving schemes developed for or applied in the context of ad hoc social networks. These schemes are published between 2008 and 2016. Based on this existing privacy preservation schemes, we survey privacy preservation models, including location privacy, identity privacy, anonymity, traceability, interest privacy, backward privacy, and content oriented privacy. The recent important attacks of leaking privacy, countermeasures, and game theoretic approaches in VSNs and MSNs are summarized in form of tables. In addition, an overview of recommendations for further research is also provided. With this survey, readers can have a more thorough understanding of research trends in privacy-preserving schemes for ad hoc social networks.

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Privacy Leakage of Location Sharing in Mobile Social Networks: Attacks and Defense

Cited by 174 publications

References 36 publications

Crowdsensing and Privacy in Smart City Applications

Crowdsensing and Privacy in Smart City Applications

Lightweight Cryptographic Techniques for Automotive Cybersecurity

Privacy-Preserving Schemes for Ad Hoc Social Networks: A Survey

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