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检索条件"任意字段=Proceedings of the Twelfth 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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Decoding the Mystery of the Internet of Things 16

Decoding the Mystery of the Internet of Things

引用

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

作者： Voas, Jeffrey NIST 100 Bur DrMS 8930 Gaithersburg MD 20899 USA

ISBN: (纸本)9781450339353

System primitives allow formalisms, reasoning, simulations, and reliability and security risk-tradeoffs to be formulated and argued. In this work, six core primitives belonging to most distributed systems are presented. These primitives apply well to systems with large amounts of data, scalability concerns, heterogeneity concerns, temporal concerns, and elements of unknown pedigree with possible nefarious intent. These primitives form the basic building blocks for a Network of 'Things' (NoT), including the Internet of Things (IoT). This keynote offers an underlying and foundational science to IoT. To my knowledge, the ideas and the manner in which the science underlying IoT is presented here is unique. Further, this talk reflects my personal viewpoints and not those of NIST.

关键词： Distributed system Internet of Things (IoT) Network of Things (NoT) Trustworthiness Reliability security Composability

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Efficient Network Path Verification for Policy-routed Queries 16

Efficient Network Path Verification for Policy-routed Querie...

引用

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

作者： Karumanchi, Sushama Li, Jingwei Squicciarini, Anna Penn State Univ Coll Informat Sci & Technol University Pk PA 16802 USA Nankai Univ Coll Comp & Control Engn Tianjin Peoples R China

ISBN: (纸本)9781450339353

Resource discovery in unstructured peer-to-peer networks causes a search query to be flooded throughout the network via random nodes, leading to security and privacy issues. The owner of the search query does not have control over the transmission of its query through the network. Although algorithms have been proposed for policy-compliant query or data routing in a network, these algorithms mainly deal with authentic route computation and do not provide mechanisms to actually verify the network paths taken by the query. In this work, we propose an approach to deal with the problem of verifying network paths taken by a search query during resource discovery, and detection of malicious forwarding of search query. Our approach aims at being secure and yet very scalable, even in the presence of huge number of nodes in the network.

关键词： resource discovery security privacy network routing path verification malicious node detection query routing peer-to-peer security P2P security

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TTPP method for validation of k-anonymity on wi-fi association log data: poster 17

TTPP method for validation of k-anonymity on wi-fi associati...

引用

proceedings of the 10th acm conference on security and privacy in Wireless and Mobile Networks

作者： Akinobu Fukuzaki Noriaki Koide Noboru Sonehara National Institute of Informatics Tokyo Japan Tsuda University Tokyo Japan

ISBN: (纸本)9781450350846

Using data about individuals without revealing sensitive information about them is important. In recently years, a new privacy protection concept is called k-anonymity has been introduced. On the other hand, application of person trip data analysis is demanded for public policy making such as tourism and *** this research, TTPP and Kn-Query method is introduced to solved a conflict between privacy protection and utilization of person trip data. TTPP method is proposed as a data structure which describes person trip using the paired entries of fixed point observed personal location with track ID, time window and place. Kn-Query is a query summarizing the number of samples under given conditions satisfying *** an ordinal method, validation of k-anonymity and person trip analysis have been considered separately. The proposed method solved a conflict between privacy and utilization of personal data.

关键词： wi-fi sensing social data privacy

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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...

引用

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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