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检索条件"任意字段=Proceedings of the Tenth ACM Conference on Data and Application Security and Privacy"

共 560 条记录，以下是331-340 订阅

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Automatic Summarization of privacy Policies using Ensemble Learning 16

Automatic Summarization of Privacy Policies using Ensemble L...

引用

6th acm conference on data and application security and privacy (CODASPY)

作者： Tomuro, Noriko Lytinen, Steven Hornsburg, Kurt Depaul Univ Coll Comp & Digital Media CDM Chicago IL 60604 USA MobileEvolution Vienna Austria

ISBN: (纸本)9781450339353

When customers purchase a product or sign up for service from a company, they often are required to agree to a privacy Policy or Terms of Service agreement. Many of these policies are lengthy, and a typical customer agrees to them without reading them carefully if at all. To address this problem, we have developed a prototype automatic text summarization system which is specifically designed for privacy policies. Our system generates a summary of a policy statement by identifying important sentences from the statement, categorizing these sentences by which of 5 "statement categories" the sentence addresses, and displaying to a user a list of the sentences which match each category. Our system incorporates keywords identified by a human domain expert and rules that were obtained by machine learning, and they are combined in an ensemble architecture. We have tested our system on a sample corpus of privacy statements, and preliminary results are promising.

关键词： privacy Policy Natural Language Processing Machine Learning

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Safely Measuring Tor 16

Safely Measuring Tor

引用

23rd acm conference on Computer and Communications security (CCS)

作者： Jansen, Rob Johnson, Aaron US Navy Res Lab Washington DC 20375 USA

ISBN: (纸本)9781450341394

Tor is a popular network for anonymous communication. The usage and operation of Tor is not well-understood, however, because its privacy goals make common measurement approaches ineffective or risky. We present PrivCount, a system for measuring the Tor network designed with user privacy as a primary goal. PrivCount securely aggregates measurements across Tor relays and over time to produce differentially private outputs. PrivCount improves on prior approaches by enabling flexible exploration of many diverse kinds of Tor measurements while maintaining accuracy and privacy for each. We use PrivCount to perform a measurement study of Tor of sufficient breadth and depth to inform accurate models of Tor users and traffic. Our results indicate that Tor has 710,000 users connected but only 550,000 active at a given time, that Web traffic now constitutes 91% of data bytes on Tor, and that the strictness of relays' connection policies significantly affects the type of application data they forward.

关键词： Tor anonymity differential privacy anonymous communication network measurement secure aggregation

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DIVERSITY 16

DIVERSITY

引用

6th acm conference on data and application security and privacy (CODASPY)

作者： Knight, John Univ Virginia Charlottesville VA 22903 USA

No abstract available.

ISBN: (纸本)9781450339353

No abstract available.

关键词： Design diversity data diversity artificial diversity secretless security software security

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security Constraints in Temporal Role-Based Access-Controlled Workflows 16

Security Constraints in Temporal Role-Based Access-Controlle...

引用

6th acm conference on data and application security and privacy (CODASPY)

作者： Combi, Carlo Vigano, Luca Zavatteri, Matteo Univ Verona Dipartimento Informat I-37100 Verona Italy Kings Coll London Dept Informat London WC2R 2LS England

ISBN: (纸本)9781450339353

Workflows and role-based access control models need to be suitably merged, in order to allow users to perform processes in a correct way, according to the given data access policies and the temporal constraints. Given a mapping between workflow models and simple temporal networks with uncertainty, we discuss a mapping between role temporalities and simple temporal networks, and how to connect the two resulting networks to make explicit who can do what, when. If the connected network is still executable, we show how to compute the set of authorized users for each task. Finally, we define security constraints (to prevent users from doing unauthorized actions) and security constraint propagation rules (to propagate security constraints at runtime). We also provide an algorithm to check whether a set of propagation rules is safe, and we extend an existing execution algorithm to take into account these new security aspects.

关键词： Access-controlled workflow TRBAC temporal separation of duties security constraint propagation rules STNU

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privacy-Preserving Mining of Sequential Association Rules from Provenance Workflows 16

Privacy-Preserving Mining of Sequential Association Rules fr...

引用

6th acm conference on data and application security and privacy (CODASPY)

作者： Maruseac, Mihai Ghinita, Gabriel UMass Boston Boston MA 02125 USA

ISBN: (纸本)9781450339353

Provenance workflows capture movement and transformation of data in complex environments, such as document management in large organizations, content generation and sharing in in social media, scientific computations, etc. Sharing and processing of provenance workflows brings numerous benefits, e.g., improving productivity in an organization, understanding social media interaction patterns, etc. However, directly sharing provenance may also disclose sensitive information such as confidential business practices, or private details about participants in a social network. We propose an algorithm that privately extracts sequential association rules from provenance workflow datasets. Finding such rules has numerous practical applications, such as capacity planning or identifying hot-spots in provenance graphs. Our approach provides good accuracy and strong privacy, by leveraging on the exponential mechanism of differential privacy. We propose an heuristic that identifies promising candidate rules and makes judicious use of the privacy budget. Experimental results show that the our approach is fast and accurate, and clearly outperforms the state-of-the-art. We also identify influential factors in improving accuracy, which helps in choosing promising directions for future improvement.

关键词： differential privacy provenance

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PANDDE: Provenance-based ANomaly Detection of data Exfiltration 16

PANDDE: Provenance-based ANomaly Detection of Data Exfiltrat...

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6th acm conference on data and application security and privacy (CODASPY)

作者： Fadolalkarim, Daren Sallam, Asmaa Bertino, Elisa Purdue Univ Dept Comp Sci W Lafayette IN 47906 USA Purdue Univ Cyber Ctr W Lafayette IN 47906 USA

ISBN: (纸本)9781450339353

Preventing data exfiltration by insiders is a challenging process since insiders are users that have access permissions to the data. Existing mechanisms focus on tracking users' activities while they are connected to the database, and are unable to detect anomalous actions that the users perform on the data once they gain access to it. Being able to detect anomalous actions on the data is critical as these actions are often sign of attempts to misuse data. In this paper, we propose an approach to detect anomalous actions executed on data returned to the users from a database. The approach has been implemented as part of the Provenance based ANomaly Detection of data Exfiltration (PANDDE) tool. PANDDE leverages data provenance information captured at the operating system level. Such information is then used to create profiles of users' actions on the data once retrieved from the database. The profiles indicate actions that are consistent with the tasks of the users. Actions recorded in the profiles include data printing, emailing, and storage. Profiles are then used at run-time to detect anomalous actions.

关键词： Operating System security and Reliability Insider Attacks Anomaly Detection Provenance Collection

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On Energy security of Smartphones 16

On Energy Security of Smartphones

引用

6th acm conference on data and application security and privacy (CODASPY)

作者： Gao, Xing Liu, Dachuan Liu, Daiping Wang, Haining Univ Delaware Newark DE 19716 USA Coll William & Mary Williamsburg VA USA

ISBN: (纸本)9781450339353

The availability of smartphones is still severely restricted by the limited battery lifetime. To help users understand the energy consumption, major mobile platforms support fine-grained energy profiling for each app. In this paper, we present a new threat, called energy collateral attacks, which can abuse and mislead all existing energy modeling approaches. In particular, energy collateral attacks are able to divulge battery stealthily through interprocess communication, wakelock, and screen. To defend against those attacks, we propose E-Android to accurately profile the energy consumption in a comprehensive manner. E-Android monitors energy collateral related events and maintains energy consumption for relevant apps. We utilize E-Android to measure the energy consumption under the attack of six energy malware and two normal scenarios. While Android fails to disclose all these energy-malware-based attacks, E Android can accurately profile energy consumption and reveal the existence of energy malware.

关键词： smartphone malware security energy attack

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JSLINQ: Building Secure applications across Tiers 16

JSLINQ: Building Secure Applications across Tiers

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6th acm conference on data and application security and privacy (CODASPY)

作者： Balliu, Musard Liebe, Benjamin Schoepe, Daniel Sabelfeld, Andrei Chalmers Gothenburg Sweden

ISBN: (纸本)9781450339353

Modern web and mobile applications are complex entities amalgamating different languages, components, and platforms. The rich features span the application tiers and components, some from third parties, and require substantial efforts to ensure that the insecurity of a single component does not render the entire system insecure. As of today, the majority of the known approaches fall short of ensuring security across tiers. This paper proposes a framework for end-to-end security, by tracking information flow through the client, server, and underlying database. The framework utilizes homogeneous meta-programming to provide a uniform language for programming different components. We leverage. NET meta-programming capabilities from the F# language, thus enabling language-integrated queries on databases and interoperable heterogeneous execution on the client and the server. We develop a core of our security enforcement in the form of a security type system for a functional language with mutable store and prove it sound. Based on the core, we develop JSLINQ, an extension of the WebSharper library to track information flow. We demonstrate the capabilities of JSLINQ on the case studies of a password meter, two location-based services, a movie rental database, an online Battleship game, and a friend finder app. Our experiments indicate that JSLINQ is practical for implementing high-assurance web and mobile applications.

关键词： declassification information-flow control security type system noninterference formal security model web application security

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CODASPY 2015 - proceedings of the 5th acm conference on data and application security and privacy

CODASPY 2015 - Proceedings of the 5th ACM Conference on Data...

引用

5th acm conference on data and application security and privacy, CODASPY 2015

ISBN: (纸本)9781450331913

The proceedings contain 40 papers. The topics discussed include: DBMask: fine-grained access control on encrypted relational databases;differentially-private mining of moderately-frequent high-confidence association rules;StaDynA: addressing the problem of dynamic code updates in the security analysis of android applications;CoinParty: secure multi-party mixing of bitcoins;how your phone camera can be used to stealthily spy on you: transplantation attacks against android camera service;Pleco and Plectron two provably secure password hashing algorithms;one thing leads to another: credential based privilege escalation;epidemic behavior of negative users in online social sites;rapid screening of transformed data leaks with efficient algorithms and parallel computing;ABSS: an attribute-based sanitizable signature for integrity of outsourced database with public cloud;and privacy-preserving scanning of big content for sensitive data exposure with MapReduce.

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Differentially Private K-Means Clustering 16

Differentially Private K-Means Clustering

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6th acm conference on data and application security and privacy (CODASPY)

作者： Su, Dong Cao, Jianneng Li, Ninghui Bertino, Elisa Jin, Hongxia Purdue Univ W Lafayette IN 47907 USA Inst Infocomm Res Singapore Singapore Samsung Res Amer Mountain View CA USA

ISBN: (纸本)9781450339353

There are two broad approaches for differentially private data analysis. The interactive approach aims at developing customized differentially private algorithms for various data mining tasks. The non-interactive approach aims at developing differentially private algorithms that can output a synopsis of the input dataset, which can then be used to support various data mining tasks. In this paper we study the effectiveness of the two approaches on differentially private k-means clustering. We develop techniques to analyze the empirical error behaviors of the existing interactive and non-interactive approaches. Based on the analysis, we propose an improvement of DPLloyd which is a differentially private version of the Lloyd algorithm. We also propose a non-interactive approach EUGkM which publishes a differentially private synopsis for k-means clustering. Results from extensive and systematic experiments support our analysis and demonstrate the effectiveness of our improvement on DPLloyd and the proposed EUGkM algorithm.

关键词： Differential privacy k-means clustering Private data publishing

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