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Privacy and Utility of Inference Control Mechanisms for Social Computing Applications

Seyed Hossein Ahmadinejad, Philip W.L. Fong, Reihaneh Safavi-Naini
2016 Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security - ASIA CCS '16  
To the best of our knowledge, ours is the first work to articulate precise privacy and utility goals of inference control mechanisms for third-party applications in social computing platforms.  ...  Our notions of privacy and utility are highly targeted, mirroring the set up of social computing platforms, in which users specify their privacy preferences and third-party applications focus their accesses  ...  Acknowledgments This work is supported in part by an NSERC Discovery Grant (RGPIN-2014-06611) and a Canada Research Chair (950-229712).  ... 
doi:10.1145/2897845.2897878 dblp:conf/ccs/AhmadinejadFS16 fatcat:kux6h5qskvc7jegwgz33znzibi

A Mechanism to Preserve Private Data in Social Networking System

Lakshmi Vidyadharan, Karthigha M, Mary Treesa Thomas
2015 International Journal of Computer Applications  
Since millions of users are using these sites it will lead to privacy problems and leakage of private information.  ...  If it is an un-trusted server it will lead to inference attack and malicious user may use the information for unintended purposes and our data will be at risk.  ...  Access Control Mechanism for Third Party Application Individuals can create their own profiles and share their personal information through these profiles.  ... 
doi:10.5120/19617-1515 fatcat:w5dv4ylr3jbjvbwfv7nv6ps6ym

A framework for context-aware privacy of sensor data on mobile systems

Supriyo Chakraborty, Kasturi Rangan Raghavan, Matthew P. Johnson, Mani B. Srivastava
2013 Proceedings of the 14th Workshop on Mobile Computing Systems and Applications - HotMobile '13  
We study the competing goals of utility and privacy as they arise when a user shares personal sensor data with apps on a smartphone.  ...  On the one hand, there can be value to the user for sharing data in the form of various personalized services and recommendations; on the other hand, there is the risk of revealing behaviors to the app  ...  Ministry of Defense or the U.K. Government. The U.S. and U.K. Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.  ... 
doi:10.1145/2444776.2444791 dblp:conf/wmcsa/ChakrabortyRJS13 fatcat:gh7eu2rbj5cg3jfe2ryeolj65y

Social Inference Risk Modeling in Mobile and Social Applications

Sara Motahari, Sotirios Ziavras, Mor Naaman, Mohamed Ismail, Quentin Jones
2009 2009 International Conference on Computational Science and Engineering  
The work validates the theoretical model, highlights the seriousness of the social inference risk, and shows how the extent and nature of the risk differs for different classes of social computing applications  ...  In this paper, after analyzing the social inference problem theoretically, we assess the extent of the risk to users of computer-mediated communication and location based applications through 1) a laboratory  ...  Access control mechanisms for mobile and location-aware computing were introduced later [2, 12, 13]. 3.  ... 
doi:10.1109/cse.2009.237 dblp:conf/cse/MotahariZNIJ09 fatcat:4qm5nv7zmrap5hgagormtd5nbu

Trust and Privacy Enabled Service Composition Using Social Experience [chapter]

Shahab Mokarizadeh, Nima Dokoohaki, Mihhail Matskin, Peep Küngas
2010 IFIP Advances in Information and Communication Technology  
Using our privacy inference model we, first, prune social network to hide privacy sensitive contents and, then, utilize a trust inference based algorithm to measure reputation score of each individual  ...  In this paper, we present a framework for automatic selection and composition of services which exploits trustworthiness of services as a metric for measuring the quality of service composition.  ...  the social network for future utilization.  ... 
doi:10.1007/978-3-642-16283-1_26 fatcat:yptbheta2bhohowgw7brvtckla

Preserving Privacy in Context-Aware Systems

Pramod Jagtap, Anupam Joshi, Tim Finin, Laura Zavala
2011 2011 IEEE Fifth International Conference on Semantic Computing  
This introduces the need for privacy and security mechanisms.  ...  We show how our policy framework can be effectively used to devise better privacy control mechanisms to control information flow between users in such dynamic mobile systems.  ...  ACKNOWLEDGMENT The research described in this paper was partially supported by the National Science Foundation (award 0910838) and the Air Force Office of Scientific Research (MURI Grant FA9550-08-0265  ... 
doi:10.1109/icsc.2011.87 dblp:conf/semco/JagtapJFG11 fatcat:cwx6rwxoorgnbfncrrjp3pcimm

TIPPERS: A privacy cognizant IoT environment

Sharad Mehrotra, Alfred Kobsa, Nalini Venkatasubramanian, Siva Raj Rajagopalan
2016 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)  
IoT environments are important and challenging application domains for privacy studies, for two reasons: data collection about people is nearly invisible, and IoT environments typically do not support  ...  We present two systems that will support powerful mechanisms to embed and test a diverse set of privacy technologies in an IoT environment in a large School building.  ...  on optimizing and controlling the full data pipeline for both utility and privacy.  ... 
doi:10.1109/percomw.2016.7457158 dblp:conf/percom/MehrotraKVR16 fatcat:txvnxrcjxvfonlqxm7kw2tvx64

How did you know that about me? Protecting users against unwanted inferences

Sara Motahari, Julia Mayer, Quentin Jones
2011 EAI Endorsed Transactions on Security and Safety  
The widespread adoption of social computing applications is transforming our world. It has changed the way we routinely communicate and navigate our environment and enabled political revolutions.  ...  Challenges examined include how to address the computational complexity of social inference risk modeling and designing user interfaces that inform users about social inference opportunities.  ...  In this paper we discuss a rarely considered but very pervasive and serious privacy threat to users of social computing applications, namely the risk of people making unwanted social inferences.  ... 
doi:10.4108/trans.sesa.2011.e3 fatcat:mtjjpssykzf3vlxs76s75z66ny

Applications of Differential Privacy in Social Network Analysis: A Survey [article]

Honglu Jiang, Jian Pei, Dongxiao Yu, Jiguo Yu, Bei Gong, Xiuzhen Cheng
2021 arXiv   pre-print
As social network analysis has been extensively adopted in many applications, it opens a new arena for the application of differential privacy.  ...  In this article, we provide a comprehensive survey connecting the basic principles of differential privacy and applications in social network analysis.  ...  Application and implementation in cyber-physical systems Privacy of Social Networks [96, 97] [1, 76] Surveys on privacy risks and anonymization techniques for privacy preserving publishing of social  ... 
arXiv:2010.02973v2 fatcat:finuu7fjenhzzcfhplapwt37mi

Privacy Intelligence: A Survey on Image Privacy in Online Social Networks [article]

Chi Liu, Tianqing Zhu, Jun Zhang, Wanlei Zhou
2021 arXiv   pre-print
Image sharing on online social networks (OSNs) has become an indispensable part of daily social activities, but it has also led to an increased risk of privacy invasion.  ...  Specifically, we present a definition and a taxonomy of OSN image privacy, and a high-level privacy analysis framework based on the lifecycle of OSN image sharing.  ...  The images have been already accessed and controlled by the recipients for social usages and out of the control of the original owner.  ... 
arXiv:2008.12199v2 fatcat:vxv6rsnyavesjiw2bbnc4jzsiy

Identity Inference as a Privacy Risk in Computer-Mediated Communication

Sara Motahari, Sotirios G. Ziavras, Richard P. Schuler, Quentin Jones
2009 2009 42nd Hawaii International Conference on System Sciences  
New Web 2.0 applications, with their emphasis on collaboration and communication, hold the promise of major advances in social connectivity and coordination; however, they also increase the threats to  ...  An important, yet under-researched privacy risk results from social inferences about user identity, location, and activities. In this paper, we frame the 'social inference problem'.  ...  The opinions expressed are those of the authors and may not reflect those of the NSF.  ... 
doi:10.1109/hicss.2009.243 dblp:conf/hicss/MotahariZSJ09 fatcat:6anjhpg26zfu7dfnnmw63avspu

LinkMirage: How to Anonymize Links in Dynamic Social Systems [article]

Changhchang Liu, Prateek Mittal
2016 arXiv   pre-print
Second, we define metrics for quantifying the privacy and utility of a time series of social topologies with anonymized links.  ...  In this work, we focus on the challenge of preserving the privacy of users' social contacts, while still enabling the design of social trust based applications.  ...  For other applications that utilize coarse and macro structure of the social graphs, such as Sybil defense mechanisms, l can be set to a larger value (typically around 10 in [43] ).  ... 
arXiv:1501.01361v2 fatcat:dgztft5hjnh6lds4hkwq5m3sma

mPrivacy: A Privacy Policy Engine and Safeguard Mechanism in Mobile Devices

Zhong Zhang, Minho Shin
2021 Applied Sciences  
In this work. we describe the notion of Information Escalation Attack and propose a detection and protection mechanism using Inference Graph and Policy Engine for the user to control their policy on the  ...  The communication between applications can be used to violate permissions and access private information without asking for the user's authorization.  ...  .; Context inference of users’ social relationships and distributed policy management.  ... 
doi:10.3390/app112411629 fatcat:hs3vutx2mfbrrerbxai5nqwkdy

Big Data Privacy in Smart Farming: A Review

Mohammad Amiri-Zarandi, Rozita A. Dara, Emily Duncan, Evan D. G. Fraser
2022 Sustainability  
The paper utilizes a data lifecycle schema and describes privacy concerns and requirements in smart farming in each of the phases of this data lifecycle.  ...  The wide use of data collection and communication technologies has increased concerns about the privacy of farmers and their data.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/su14159120 fatcat:fepfby2wkbfelfgspq4dami4aq

On (The Lack Of) Location Privacy in Crowdsourcing Applications [article]

Spyros Boukoros, Mathias Humbert (Swiss Data Science Center, ETH Zurich and EPFL, Switzerland), Stefan Katzenbeisser
2019 arXiv   pre-print
The collection of geolocated data raises serious privacy concerns for users.  ...  Yet, despite the large research body on location privacy-preserving mechanisms (LPPMs), MCS developers implement little to no protection for data collection or publication.  ...  We evaluate the privacy gain and the utility loss of an LPPM as follows: 8 Step 1. We simulate an adversary's inference regarding the regions and points of interest for all users.  ... 
arXiv:1901.04923v3 fatcat:ws5qnshjtbaxleow6y62fckfeq
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