Detecting and preventing inference attacks in online social networks: A data-driven and holistic framework

IF 0.5 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

International Journal of Information Security and Privacy Pub Date : 2017-07-03 DOI:10.1080/15536548.2017.1357383

Xiaoyun He, Haibing Lu

引用次数: 0

Abstract

ABSTRACT With increasing user involvement, social networks nowadays serve as a repository of all kinds of information. While there have been various studies demonstrating that private information can be inferred from social networks, few have taken a holistic view on designing mechanisms to detect and alleviate the inference attacks. In this study, we present a framework that leverages the social network data and data mining techniques to proactively detect and prevent possible inference attacks against users. A novel method is proposed to minimize the modifications to user profiles in order to prevent inference attacks while preserving the utility.

查看原文本刊更多论文

在线社交网络中的推理攻击检测与预防:一个数据驱动的整体框架

随着用户参与度的提高，社交网络如今成为了各种信息的储存库。虽然有各种各样的研究表明，私人信息可以从社交网络中推断出来，但很少有人从整体上看待设计检测和减轻推理攻击的机制。在这项研究中，我们提出了一个框架，利用社交网络数据和数据挖掘技术来主动检测和防止可能的针对用户的推理攻击。提出了一种最小化用户配置文件修改的新方法，以防止推理攻击，同时保持实用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

International Journal of Information Security and Privacy COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

2.50

自引率

0.00%

发文量

期刊介绍： As information technology and the Internet become more and more ubiquitous and pervasive in our daily lives, there is an essential need for a more thorough understanding of information security and privacy issues and concerns. The International Journal of Information Security and Privacy (IJISP) creates and fosters a forum where research in the theory and practice of information security and privacy is advanced. IJISP publishes high quality papers dealing with a wide range of issues, ranging from technical, legal, regulatory, organizational, managerial, cultural, ethical and human aspects of information security and privacy, through a balanced mix of theoretical and empirical research articles, case studies, book reviews, tutorials, and editorials. This journal encourages submission of manuscripts that present research frameworks, methods, methodologies, theory development and validation, case studies, simulation results and analysis, technological architectures, infrastructure issues in design, and implementation and maintenance of secure and privacy preserving initiatives.