Secure Processor Consistent with Both Foreign Software Protection and User Privacy Protection (Transcript of Discussion)

2006 ◽  
pp. 287-290
Author(s):  
Mikio Hashimoto
Keyword(s):  
Privacy Protection ◽  
Software Protection ◽  
User Privacy

Secure Processor Consistent with Both Foreign Software Protection and User Privacy Protection

2006 ◽  
pp. 276-286 ◽  
Author(s):  
Mikio Hashimoto ◽  
Hiroyoshi Haruki ◽  
Takeshi Kawabata
Keyword(s):  
Privacy Protection ◽  
Software Protection ◽  
User Privacy

The Protection of User Preference Privacy in Personalized Information Retrieval: Challenges and Overviews

Libri ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Zongda Wu ◽  
Chenglang Lu ◽  
Youlin Zhao ◽  
Jian Xie ◽  
Dongdong Zou ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Privacy Protection ◽  
User Preference ◽  
User Privacy ◽  
Server Side ◽  
Algorithm Efficiency ◽  
Important Study ◽  
Basic Reference ◽  
Complete Set ◽  
Technical Features

Abstract This paper reviews a large number of research achievements relevant to user privacy protection in an untrusted network environment, and then analyzes and evaluates their application limitations in personalized information retrieval, to establish the conditional constraints that an effective approach for user preference privacy protection in personalized information retrieval should meet, thus providing a basic reference for the solution of this problem. First, based on the basic framework of a personalized information retrieval platform, we establish a complete set of constraints for user preference privacy protection in terms of security, usability, efficiency, and accuracy. Then, we comprehensively review the technical features for all kinds of popular methods for user privacy protection, and analyze their application limitations in personalized information retrieval, according to the constraints of preference privacy protection. The results show that personalized information retrieval has higher requirements for users’ privacy protection, i.e., it is required to comprehensively improve the security of users’ preference privacy on the untrusted server-side, under the precondition of not changing the platform, algorithm, efficiency, and accuracy of personalized information retrieval. However, all kinds of existing privacy methods still cannot meet the above requirements. This paper is an important study attempt to the problem of user preference privacy protection of personalized information retrieval, which can provide a basic reference and direction for the further study of the problem.

A dummy-based user privacy protection approach for text information retrieval

2020 ◽  
Vol 195 ◽  
pp. 105679
Author(s):  
Zongda Wu ◽  
Shigen Shen ◽  
Xinze Lian ◽  
Xinning Su ◽  
Enhong Chen
Keyword(s):  
Information Retrieval ◽  
Privacy Protection ◽  
User Privacy ◽  
Text Information ◽  
Text Information Retrieval

Social Networking Site Privacy Assurance and User Privacy Protection Behavior--Model

2020 ◽  
Author(s):  
Reza Mousavi ◽  
Rui Chen ◽  
Dan J. Kim ◽  
Kuanchin Chen
Keyword(s):  
Social Networking ◽  
Privacy Protection ◽  
Social Networking Site ◽  
Behavior Model ◽  
User Privacy

Cache-Aware Query Processing with User Privacy Protection in Location-Based Services

2014 ◽  
pp. 247-258
Author(s):  
Zhengang Wu ◽  
Liangwen Yu ◽  
Huiping Sun ◽  
Zhi Guan ◽  
Zhong Chen
Keyword(s):  
Query Processing ◽  
Privacy Protection ◽  
Location Based Services ◽  
User Privacy

The Unheard Story of Organizational Motivations Towards User Privacy

2020 ◽  
pp. 280-303
Author(s):  
Awanthika Senarath ◽  
Nalin Asanka Gamagedara Arachchilage
Keyword(s):  
Privacy Protection ◽  
End Users ◽  
User Privacy ◽  
Software Applications ◽  
Organizational Perspective ◽  
Scale Of Operation

There could be numerous reasons that drive organizations to provide privacy protections to end users in the applications they develop and maintain. Organizational motivations towards privacy affects the quality of privacy received by end users. Understanding these motivations and the approaches taken by organizations towards privacy protection would assist the policymakers and regulators to define effective frameworks encouraging organizational privacy practices. This study focuses on understanding the motivations behind organizational decisions and the approaches they take to embed privacy into the software applications. The authors analyzed 40 organizations different in size, scope, scale of operation, nature of data used, and revenue. they identified four groups of organizations characterized by the approach taken to provide privacy protection to their users. The taxonomy contributes to the organizational perspective of privacy. The knowledge presented here would help addressing the challenges in the domain of user privacy in software applications and services.

Privacy-Preserving Spatial Trajectory Prediction Based on a Novel Matrix Representation

2016 ◽  
pp. 1693-1717
Author(s):  
Wen-Chen Hu ◽  
Naima Kaabouch ◽  
Hung-Jen Yang ◽  
S. Hossein Mousavinezhad
Keyword(s):  
Traffic Control ◽  
Privacy Protection ◽  
Matrix Representation ◽  
High Mobility ◽  
Location Based Services ◽  
Privacy Concern ◽  
User Privacy ◽  
Trajectory Prediction ◽  
Spatial Trajectory ◽  
Human Behavior Recognition

Since the introduction of iPhone in 2007, smartphones have become very popular (e.g., the number of worldwide smartphone sales has surpassed the number of PC sales in 2011). The feature of high mobility and small size of smartphones has created many applications that are not possible or inconvenient for PCs and servers, even laptops. Location-based services (LBS), one of mobile applications, have attracted a great attention recently. This research proposes a location-based service, which predicts a spatial trajectory based on the current and previous trajectories by using a novel matrix representation. Spatial trajectory prediction can be used in a variety of purposes such as travel recommendations and traffic control and planning, but at the same time, just like most location-based services, the user privacy concern is a major issue. Without rigorous privacy protection, users would be reluctant to use the service. The proposed method is simple but effective and user privacy is rigorously preserved at the same time because the trajectory prediction is performed at the user-side. Additionally, this research is not only useful but also pedagogical because it involves a variety of topics like (i) mobile computing, (ii) mobile security, and (iii) human behavior recognition.

Query-Aware User Privacy Protection for LBS over Query-Feature-based Attacks

2018 ◽  
Author(s):  
Mingming Guo ◽  
Kianoosh G. Boroojeni ◽  
Niki Pissinou ◽  
Kia Makki ◽  
Jerry Miller ◽  
...  
Keyword(s):  
Privacy Protection ◽  
User Privacy ◽  
Feature Based

Triggers and motivators of privacy protection behavior on Facebook

2019 ◽  
Vol 33 (1) ◽  
pp. 57-72 ◽  
Author(s):  
Linda Alkire ◽  
Johannes Pohlmann ◽  
Willy Barnett
Keyword(s):  
Social Media ◽  
Privacy Protection ◽  
Well Being ◽  
Social Recognition ◽  
Research Approach ◽  
Exploratory Research ◽  
User Privacy ◽  
Content Type ◽  
Area Of Interest ◽  
The Impact

Purpose Internet user privacy risks have been a topical subject with respect to consumers, corporations and governments. In line with the recent privacy scandals linked to social media, the aim of this study is to explore users’ privacy protection behaviors (PPB) on Facebook through the actions they take to protect their privacy, their underlying motives and the values behind these protective actions. Moreover, this study aims to address an unintended consequence of Facebook usage. Despite Facebook’s positive and uplifting goal of connecting people, consumers are forced to resort to specific behaviors to protect their privacy and well-being. Design/methodology/approach This study adopts an exploratory research approach by using a well-established qualitative technique: structured laddering interviews. In total, 20 in-depth personal interviews were conducted with the Millennials. Findings Results show that the process of privacy protection is initiated by experiences, uncertainty and literacy, rather than threats, which leads to concerns that trigger PPBs. The most common PPBs include: “Reflection,” “Avoidance,” “Intervention,” “Restriction,” “Control,” and “Restraint.” The underlying motives for the adoption of these strategies include: “Success,” “Security,” “Social Recognition,” “A World of Peace,” “Exclusivity of Self,” “Being in Control,” “Meaning” and “True Friendship”. Originality/value The present research adopts a transdisciplinary framework to help fill the gap regarding the interplay of PPBs on Facebook, the triggers of those behaviors and their underlying motives. It contributes to the service literature and practice as it provides insights into a growing area of interest, whereas more social media channels are being created and more services are using social media strategies to engage and interact with their customers. Finally, it addresses the growing need to consider the impact of technological services, including internet and social media, on consumers’ and societies’ well-being.

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