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检索条件"任意字段=Proceedings of the 5th ACM Conference on Data and Application Security and Privacy"

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Solving a Hard Instance of Suspicious Behaviour Detection with Sparse Binary Vectors Clustering 5th

Solving a Hard Instance of Suspicious Behaviour Detection wi...

引用

5th International conference on Information Systems security and privacy (ICISSP)

作者： Filiol, Eric Hota, Abhilash ESIEA Lab Virol & Cryptol Operat Laval France

ISBN: (纸本)9789897583599

In this article we present a study dealing with the problem of detecting a very small subset of suspicious and malicious behaviours represented by sparse binary vectors in a population of individuals significantly larger. the main problem lies in the fact that malicious behaviours, in the case of sparse vectors, are difficult to distinguish from normal behaviours. Despite the fact that vectors are apparently strongly unbalanced, this property cannot be exploited since the objects to classify (behaviours) do not exhibit strongly enough frequencies discrepancy. It is not possible to work on detection directly and it is therefore necessary to go through a preliminary phase of vector partitioning (representing normal or malicious behaviour) to select a reduced subset concentrating with a high probability most of the vectors corresponding to malicious behaviours. We have been working on a set of anonymized real data from terrorism-related cases.

关键词： Machine Learning Clustering Sparse Binary Vector Malicious Behaviour Infrastructure security

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Deep Neural Networks Classification over Encrypted data 19

Deep Neural Networks Classification over Encrypted Data

引用

9th acm conference on data and application security and privacy (CODASPY)

作者： Hesamifard, Ehsan Takabi, Hassan Ghasemi, Mehdi Univ North Texas Denton TX 76203 USA Univ Saskatchewan Saskatoon SK Canada

ISBN: (纸本)9781450360999

Deep Neural Networks (DNNs) have overtaken classic machine learning algorithms due to their superior performance in big data analysis in a broad range of applications. On the other hand, in recent years Machine Learning as a Service (MLaaS) has become more widespread in which a client uses cloud services for analyzing its data. However, the client's data may be sensitive which raises privacy concerns. In this paper, we address the issue of privacy preserving classification in a Machine Learning as a Service (MLaaS) settings and focus on convolutional neural networks (CNN). To achieve this goal, we develop new techniques to run CNNs over encrypted data. First, we design methods to approximate commonly used activation functions in CNNs (i.e. ReLU, Sigmoid, and Tanh) with low degree polynomials which is essential for a practical and efficient solution. then, we train CNNs with approximation polynomials instead of original activation functions and implement CNNs classification over encrypted data. We evaluate the performance of our modified models at each step. the results of our experiments using several CNNs with a varying number of layers and structures are promising. When applied to the MNIST optical character recognition tasks, our approach achieved 99.25% accuracy which significantly outperforms state-of-the-art solutions and is close to the accuracy of the best non-private version. Furthermore, it can make up to 164000 predictions per hour. these results show that our approach provides accurate, efficient, and scalable privacy-preserving predictions in CNNs.

关键词： privacy deep learning convolutional neural network homomorphic encryption classification

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A Novel Features Set for Internet Traffic Classification using Burstiness 5th

A Novel Features Set for Internet Traffic Classification usi...

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5th International conference on Information Systems security and privacy (ICISSP)

作者： Oudah, Hussein Ghita, Bogdan Bakhshi, Taimur Plymouth Univ Ctr Secur Commun & Network Res Plymouth Devon England

ISBN: (纸本)9789897583599

Traffic classification is an essential tool for network management and security. Traditional techniques such as port-based and payload analysis are ineffective as major Internet applications use dynamic port numbers and encryption. Recent studies have used statistical properties of flows to classify traffic with high accuracy, minimising the overhead limitations associated with other schemes such as deep packet inspection (DPI). Classification accuracy of statistical flow-based approaches, however, depends on the discrimination ability of the traffic features used. To this effect, the present paper customised the popular tcptrace utility to generate classification features based on traffic burstiness and periods of inactivity (idle time) for everyday Internet usage. An attempt was made to train a C5.0 decision tree classifier using the proposed features for eleven different Internet applications, generated by ten users. Overall, the newly proposed features reported a significant level of accuracy (similar to 98%) in classifying the respective applications.

关键词： Traffic Classification Tcptrace application Detection C5.0 Algorithm

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SPROOF: A Platform for Issuing and Verifying Documents in a Public Blockchain 5th

SPROOF: A Platform for Issuing and Verifying Documents in a ...

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5th International conference on Information Systems security and privacy (ICISSP)

作者： Brunner, Clemens Knirsch, Fabian Engel, Dominik Salzburg Univ Appl Sci Ctr Secure Energy Informat Puch Bei Hallein Austria

ISBN: (纸本)9789897583599

Managing educational certificates or records of personal achievements often comes at the cost of handling documents, loss of data or malicious counterfeits. Especially in the case of printed certificates, both the origin and the integrity of certificates are hard to verify. Furthermore, such documents can be lost or destroyed due to unseen circumstances. Reissuing certificates can then be cost intensive, hard or impossible, e.g., if the issuing organization has been closed. While issuing and signing documents digitally solves some of these issues, this still requires centralized trusted infrastructures and still does not allow for easy verification or recovery of lost documents. In this paper, we present SPROOF, a platform for issuing, managing and verifying digital documents in a public blockchain. In the proposed approach, all data needed for verification of documents and issuers is stored decentralized, transparent, and integrity protected. the platform is permissionless and thus no access restrictions apply. Rather, following principles of the Web of Trust, issuers can confirm each other in a decentralized way. Additionally, scalability and privacy issues are taken into consideration.

关键词： Blockchain Certificate privacy-friendly Digital Document Pseudonym

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proceedings - 5th IEEE International conference on Big data security on Cloud, Bigdatasecurity 2019, 5th IEEE International conference on High Performance and Smart Computing, HPSC 2019 and 4th IEEE International conference on Intelligent data and security, IDS 2019

Proceedings - 5th IEEE International Conference on Big Data ...

引用

5th IEEE International conference on Big data security on Cloud, 5th IEEE International conference on High Performance and Smart Computing and 4th IEEE International conference on Intelligent data and security, Bigdatasecurity/HPSC/IDS 2019

ISBN: (纸本)9781728100067

the proceedings contain 55 papers. the topics discussed include: an analysis of differential privacy research in location data;speech emotion recognition based on multi-task learning;high performance data encryption with AES implementation on FPGA;blockchain " can it solve the security issues and fraud expenses for credit card commerce?;designing security system for iot;research on 3d interactive model selection and customization of ceramic products based on big data cloud service platform;raw cardinality information discovery for big datasets;and streaming machine learning for real-time gas concentration prediction.

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Are You Ready When It Counts? IT Consulting Firm's Information security Incident Management 5th

Are You Ready When It Counts? IT Consulting Firm's Informati...

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5th International conference on Information Systems security and privacy (ICISSP)

作者： Nyman, Maja Grosse, Christine Mid Sweden Univ Dept Informat Syst & Technol Holmgatan 10 Sundsvall Sweden

ISBN: (纸本)9789897583599

Information security incidents are increasing both in number and in scope. In consequence, the General data Protection Regulation and the Directive on security of network and information systems force organisations to report such incidents to a supervision authority. Due to the growing of both the importance of managing incidents and the tendency to outsourcing, this study focuses on IT-consulting firms and highlights their vulnerable position as subcontractors. this study thereby addresses the lack of empirical research on incident management and contributes valuable insights in IT-consulting firms' experiences with information security incident management. Evidence from interviews and a survey with experts at IT-consulting firms focuses on challenges in managing information security incidents. the analyses identify and clarify both new and known challenges, such as how the recent regulations affect the role of an IT-consulting firm and how the absence of major incidents influences stakeholder awareness. Improvements of IT-consulting firm's incident management process need to address internal and external communication, the information security awareness of employees and customers and the adequacy of the cost focus.

关键词： security Awareness Information security Incident Management IT Consulting GDPR NIS Directive

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Mobile Devices as Digital Sextants for Zero-Permission Geolocation 5th

Mobile Devices as Digital Sextants for Zero-Permission Geolo...

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5th International conference on Information Systems security and privacy (ICISSP)

作者： Schwittmann, Lorenz Wander, Matthaeus Weis, Torben Univ Duisburg Essen Distributed Syst Grp D-47048 Duisburg Germany

ISBN: (纸本)9789897583599

Sensors in mobile devices can be used to infer information about a user's context, most notably the location. Android apps and websites shown in Firefox for Android allow software to read the ambient light sensor, gyroscope and accelerometer without asking the user for permission. We show that these three sensors are sufficient to determine the rough geographical location of a user by turning the mobile device into a digital sextant. Despite low-quality sensor data, our approach is able to determine the position of the sun and thereby the geographical area where the user is located. Our approach works even if the user holding the device does not cooperate in being located or employs location-disguising techniques such as a VPN. We analyze in detail the different error sources and show in which settings and situations our approach works best. the location accuracy was at best 146 km with a medium accuracy better than 500 km. Truncating the positional sensor readings minimizes the privacy threat, while truncation of the ambient light sensor has almost no effect.

关键词： Geolocation Tracking privacy Ambient Light Sensor Mobile Web security

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privacy and security analysis of cryptocurrency mobile applications 5

Privacy and Security analysis of cryptocurrency mobile appli...

引用

5th International conference on Mobile and Secure Services (MobiSecServ)

作者： Sai, Ashish Rajendra Buckley, Jim Le Gear, Andrew Univ Limerick Lero Limerick Ireland Univ Limerick Nexus Ctr Horizon Globex Ireland DAC Limerick Ireland

ISBN: (纸本)9781538677001

Subsequent to the introduction of Bitcoin, the field of cryptocurrency has seen unprecedented growth. Mobile applications known as wallets often facilitate user interaction to these cryptocurrencies. With a perceived real world value these wallets are a target for attackers. Unlike mainstream financial services applications, cryptocurrency wallets are not subject to the same stringent security requirements of their regulated counterparts. In this paper, we examine the security profiles of commonly used Android cryptocurrency applications. We examine these applications for common vulnerabilities outlined by OWASP mobile top 10. We establish a baseline for our tests by evaluating commonly used banking and trading applications. We compare the results from our baseline test and establish the state of security provided by cryptocurrency wallet applications. the paper also examines the possible privacy implications of mobile applications. We report that the conventional financial services applications are only marginally better than cryptocurrency application in security provisions but they provide greater privacy.

关键词： cryptocurrency smartphone application security OWASP mobile

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A Study of data Store-based Home Automation 19

A Study of Data Store-based Home Automation

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9th acm conference on data and application security and privacy (CODASPY)

作者： Kafle, Kaushal Moran, Kevin Manandhar, Sunil Nadkarni, Adwait Poshyvanyk, Denys William & Mary Williamsburg VA 23185 USA

ISBN: (纸本)9781450360999

Home automation platforms provide a new level of convenience by enabling consumers to automate various aspects of physical objects in their homes. While the convenience is beneficial, security flaws in the platforms or integrated third-party products can have serious consequences for the integrity of a user's physical environment. In this paper we perform a systematic security evaluation of two popular smart home platforms, Google's Nest platform and Philips Hue, that implement home automation "routines" (i.e., trigger-action programs involving apps and devices) via manipulation of state variables in a centralized data store. Our semi-automated analysis examines, among other things, platform access control enforcement, the rigor of non-system enforcement procedures, and the potential for misuse of routines. this analysis results in ten key findings with serious security implications. For instance, we demonstrate the potential for the misuse of smart home routines in the Nest platform to perform a lateral privilege escalation, illustrate how Nest's product review system is ineffective at preventing multiple stages of this attack that it examines, and demonstrate how emerging platforms may fail to provide even bare-minimum security by allowing apps to arbitrarily add/remove other apps from the user's smart home. Our findings draw attention to the unique security challenges of platforms that execute routines via centralized data stores, and highlight the importance of enforcing security by design in emerging home automation platforms.

关键词： Smart Home Routines Lateral Privilege Escalation Overprivilege

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Representing cloud security and privacy policies and detecting potential problems 5

Representing cloud security and privacy policies and detecti...

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5th IEEE International conference on Big data Intelligence and Computing, dataCom 2019

作者： Opara, Anthony Song, Youngsang Cho, Seong-Je Chung, Lawrence University of Texas Dallas United States Dankook University Korea Republic of

ISBN: (纸本)9781728141176

Cloud computing involves multiple stakeholders, each with its own security, privacy and trust requirements, where policy enforcement is shared between the various stakeholders, in contrast to on-premise computing, where an organizations policies are enforced using internal resources. To effectively manage and integrate security requirements in the cloud, the provider and customer needs to negotiate and agree upon the applied security policies. However, there is no standard way of expressing cloud security policies in a vendor-agnostic manner. Cloud security and privacy policies are often stated in an informal and ad-hoc manner, which leads to policy conflicts, incompleteness, ambiguity and inconsistencies. In this paper, we present CERBERUS, a framework for representing cloud security and privacy policies and detecting potential problems in the policies. CERBERUS adopts an object-oriented approach and consists of an ontology and notation, policies, guidelines and rules, and a tool for capturing and detecting policy errors. Using CERBERUS, policies can be analyzed for potential problems, including policy conflicts, inconsistencies, ambiguities, and incompleteness. An application of CERBERUS shows that it indeed helps to discover policy errors, which otherwise would go undetected or in many cases would be detected a posteriori at runtime. © 2019 IEEE.

关键词： Cloud security

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