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3rd acm conference on data and application security and privacy, codaspy 2013

ISBN: (纸本)9781450318907

The proceedings contain 41 papers. The topics discussed include: for some eyes only: protecting online information sharing;do online social network friends still threaten my privacy?;exploring dependency for query privacy protection in location-based services;expression rewriting for optimizing secure computation;efficient discovery of de-identification policy options through a risk-utility frontier;data usage control enforcement in distributed systems;privacy by design: a formal framework for the analysis of architectural choices;comparative eye tracking of experts and novices in web single sign-on;cross-layer detection of malicious websites;a file provenance system;enhancing performance of searchable encryption in cloud computing;a fine-grained access control model for key-value systems;emulating Internet topology snapshots in deterlab;and a study of user password strategy for multiple accounts.

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A message authentication scheme for VANETs based on trapdoor hash function 3

A message authentication scheme for VANETs based on trapdoor...

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3rd IEEE International conference on Big data Analysis, ICBDA 2018

作者： Yang, Xiaodong An, Faying Yang, Ping Xiao, Likun Li, Yutong Ma, Tingchun Wang, Caifen College of Computer Science and Engineering Northwest Normal University Lanzhou China

ISBN: (纸本)9781538647936

Vehicle ad-hoc networks (VANETs) is an important area of big data application. Big data can help VANETs to solve the traffic safety and congestion problems faced by many cities. In this paper, based on proxy re-signature and trapdoor hash function, a new message authentication scheme for VANETs is proposed. Our scheme can solve the problems of identity privacy and excessive overhead of message authentication in VANETs. The proposed scheme can also transform the signature on the message from the roadside into the signature on the same message signed by the trusted authentication center by using the proxy re-signature technology, and realizes the anonymity of vehicle identity and traceability of the communication message. At the same time, the trapdoor hash function is introduced into the signature generation of the message, which effectively improves the real-time performance of signature verification on communication message. Compared with the existing similar schemes, our scheme has higher security and lower computation overhead. © 2018 IEEE.

关键词： Hash functions

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"If You Can't Beat them, Join them": A Usability Approach to Interdependent privacy in Cloud Apps 17

"If You Can't Beat them, Join them": A Usability Approach to...

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7th acm conference on data and application security and privacy (codaspy)

作者： Harkous, Hamza Aberer, Karl Ecole Polytech Fed Lausanne Lausanne Switzerland

ISBN: (纸本)9781450345231

Cloud storage services, like Dropbox and Google Drive, have growing ecosystems of 3rd party apps that are designed to work with users' cloud files. Such apps often request full access to users' files, including files shared with collaborators. Hence, whenever a user grants access to a new vendor, she is inflicting a privacy loss on herself and on her collaborators too. Based on analyzing a real dataset of 183 Google Drive users and 131 third party apps, we discover that collaborators inflict a privacy loss which is at least 39% higher than what users themselves cause. We take a step toward minimizing this loss by introducing the concept of History-based decisions. Simply put, users are informed at decision time about the vendors which have been previously granted access to their data. Thus, they can reduce their privacy loss by not installing apps from new vendors whenever possible. Next, we realize this concept by introducing a new privacy indicator, which can be integrated within the cloud apps' authorization interface. Via a web experiment with 141 participants recruited from CrowdFlower, we show that our privacy indicator can significantly increase the user's likelihood of choosing the app that minimizes her privacy loss. Finally, we explore the network effect of History-based decisions via a simulation on top of large collaboration networks. We demonstrate that adopting such a decision-making process is capable of reducing the growth of user privacy loss by 40% in a Google Drive-based network and by 70% in an author collaboration network. This is despite the fact that we neither assume that users cooperate nor that they exhibit altruistic behavior. To our knowledge, our work is the first to provide quantifiable evidence of the privacy risk that collaborators pose in cloud apps. We are also the first to mitigate this problem via a usable privacy approach.

关键词： interdependent privacy 3rd party apps privacy cloud computing usability google drive DropBox

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A novel attack to track users based on the behavior patterns

A novel attack to track users based on the behavior patterns

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3rd International conference on Advanced Cloud and Big data (CBD)

作者： Gu, Xiaodan Yang, Ming Shi, Congcong Ling, Zhen Luo, Junzhou Southeast Univ Sch Comp Sci & Engn Nanjing Jiangsu Peoples R China Global Energy Interconnect Res Inst Nanjing Jiangsu Peoples R China

Currently, people around the world daily use the Internet to access various services, such as e-mail and online shopping. However, the behavior-based tracking attacks have posed a considerable threat to users' privacy. Relying on characteristic patterns within the Internet activities, this attack can link a user's multiple sessions. In this paper, we investigate the behavior-based tracking attack and propose some countermeasures to mitigate the threat. We preprocess the raw traffic data and then extract features ranging from lower layer network packets to high-level application-related traffic. Specifically, we focus on four types of application-level traffic to infer users' habits, including HTTP, IM, e-mail, and P2P. In addition, we extract the web queries entered into shopping websites and classify them to infer users' preferences. Then, we construct the preference models and propose an improved method. For evaluation, we collect traffic in the real-world environment to construct a large-scale dataset. Five hundred and nine users are selected in terms of the user's active degree. When the term frequency-inverse document frequency transformation is used, the improved method can identify an average of 93.79% instances correctly. Our extensive empirical experiments demonstrate the effectiveness and efficiency of our approaches. Finally, we discuss and evaluate several countermeasures. Copyright (C) 2016 John Wiley & Sons, Ltd.

关键词： behavior-based tracking privacy traffic analysis pattern recognition preference model

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A novel attack to track users based on the behavior patterns

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2017年第6期29卷

关键词： behavior-based tracking privacy traffic analysis pattern recognition preference model

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A Novel Behavior-based Tracking Attack for User Identification 3

A Novel Behavior-based Tracking Attack for User Identificati...

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3rd International conference on Advanced Cloud and Big data (CBD)

作者： Gu, Xiaodan Yang, Ming Fei, Jiaxuan Ling, Zhen Luo, Junzhou Southeast Univ Sch Comp Sci & Engn Nanjing Jiangsu Peoples R China State Grid Smart Grid Res Inst Beijing Peoples R China

ISBN: (纸本)9781467385374

Currently, people around the world daily use the Internet to access various services, such as, email and online shopping. However, the behavior-based tracking attacks have posed a considerable threat to users' privacy. Relying on characteristic patterns within the Internet activities, this attack can link a user's multiple sessions which are composed of a period of user's traffic. Once a user's personally identifiable information is disclosed in some session, the attacker can obtain the user's other network activities according to the linked sessions. In this paper, we investigate this behavior-based tracking attack and discuss the possible countermeasures. We preprocess the raw traffic data and then extract features ranging from lower layer network packets to high level application related traffic. Specifically, we focuses on four types of application-level traffic to infer users' habits, including HTTP, IM, Email, and P2P. A Multinomial Naive Bayes Classifier is employed to correlate users' sessions in distinct period. To evaluate the feasibility of our approach, we collect traffic in real-world environment to construct two distinct sizes of datasets. In the first dataset, we have 55 users' traffic during five weeks and the accuracy of our approach could reach 100%. To further illustrate the scalability of this approach, 509 users are selected from the second dataset in terms of the user's active degree. Finally, we can correctly correlate average 85.61% instances. Our extensive empirical experiments demonstrate the effectiveness and efficiency of our approach.

关键词： behavior-based tracking traffic analysis pattern recognition privacy

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An extensible platform for the forensic analysis of social media data 3rd

An extensible platform for the forensic analysis of social m...

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3rd International conference on Human Aspects of Information security, privacy and Trust, HAS 2015 Held as Part of 17th International conference on Human-Computer Interaction, HCI International 2015

作者： Read, Huw Xynos, Konstantinos Sutherland, Iain Roarson, Frode Andriotis, Panagiotis Oikonomou, George University of South Wales PontypriddCF37 1DL United Kingdom Noroff University College 4608 Kristiansand S Vest Agder Norway University of Bristol BristolBS8 1TH United Kingdom Security Research Institute Edith Cowan University Perth Australia

ISBN: (纸本)9783319203751

Visualising data is an important part of the forensic analysis process. Many cell phone forensic tools have specialised visualisation components, but are as of yet able to tackle questions concerning the broad spectrum of social media communication sources. Visualisation tools tend to be stove-piped, it is difficult to take information seen in one visualisation tool and obtain a different perspective in another tool. If an interesting relationship is observed, needing to be explored in more depth, the process has to be reiterated by manually generating a subset of the data, converting it into the correct format, and invoking the new application. This paper describes a cloud-based data storage architecture and a set of interactive visualisation tools developed to allow for a more straightforward exploratory analysis. This approach developed in this tool suite is demonstrated using a case study consisting of social media data extracted from two mobile devices. © Springer International Publishing Switzerland 2015.

关键词： Visualization

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AppsPlayground: Automatic security analysis of smartphone applications 13

AppsPlayground: Automatic security analysis of smartphone ap...

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3rd acm conference on data and application security and privacy, codaspy 2013

作者： Rastogi, Vaibhav Chen, Yan Enck, William Northwestern University United States North Carolina State University United States

ISBN: (纸本)9781450318907

Today's smartphone application markets host an ever in- creasing number of applications. The sheer number of ap- plications makes their review a daunting task. We propose AppsPlayground for Android, a framework that automates the analysis smartphone applications. AppsPlayground in- tegrates multiple components comprising different detection and automatic exploration techniques for this purpose. We evaluated the system using multiple large scale and small scale experiments involving real benign and malicious ap- plications. Our evaluation shows that AppsPlayground is quite effective at automatically detecting privacy leaks and malicious functionality in applications. Copyright 2013 acm.

关键词： Android (operating system)

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TamperProof: A server-agnostic defense for parameter tampering attacks on web applications 13

TamperProof: A server-agnostic defense for parameter tamperi...

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3rd acm conference on data and application security and privacy, codaspy 2013

作者： Skrupsky, Nazari Bisht, Prithvi Hinrichs, Timothy Venkatakrishnan, V.N. Zuck, Lenore University of Illinois Chicago United States

ISBN: (纸本)9781450318907

Parameter tampering attacks are dangerous to a web application whose server performs weaker data sanitization than its client. This paper presents TamperProof, a methodology and tool that offers a novel and efficient mechanism to protectWeb applications from parameter tampering attacks. TamperProof is an online defense deployed in a trusted environment between the client and server and requires no access to, or knowledge of, the server side codebase, making it effective for both new and legacy applications. The paper reports on experiments that demonstrate TamperProof's power in efficiently preventing all known parameter tampering vulnerabilities on ten different applications. Copyright 2013 acm.

关键词： Network security

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privacy by design: Formal framework for the analysis of architectural choices

Privacy by design: Formal framework for the analysis of arch...

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3rd acm conference on data and application security and privacy, codaspy 2013

作者： Le Métayer, Daniel CITI Domaine Scientifique de La Doua Inria University of Lyon 6 avenue des Arts 69621 Villeurbanne France

ISBN: (纸本)9781450318907

The privacy by design approach has already been applied in different areas. We believe that the next challenge in this area today is to go beyond individual cases and to provide methodologies to explore the design space in a systematic way. As a first step in this direction, we focus in this paper on the data minimization principle and consider difierent options using decentralized architectures in which actors do not necessarily trust each other. We propose a framework to express the parameters to be taken into account (the service to be performed, the actors involved, their respective requirements, etc.) and an inference system to derive properties such as the possibility for an actor to detect potential errors (or frauds) in the computation of a variable. This inference system can be used in the design phase to check if an architecture meets the requirements of the parties or to point out conicting requirements. Copyright 2013 acm.

关键词： data privacy

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