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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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Cloud security and Jurisdiction: Need of the Hour 5th

Cloud Security and Jurisdiction: Need of the Hour

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5th International conference on Frontiers in Intelligent Computing - theory and applications (FICTA)

作者： Jena, Tamanna Mohanty, J. R. KIIT Univ Sch Comp Engn Bhubaneswar Orissa India KIIT Univ Sch Comp Applicat Bhubaneswar Orissa India

ISBN: (纸本)9789811031533;9789811031526

Features of cloud services that users' data is remotely in obscure machine is neither owned nor controlled by user. For adoption of services, from users' point of view, cloud security and arbitration are significant. security gap among different tiers causes privacy issues, customer concern about losing sensitive data available in a cloud computing infrastructure. Disagreement among different components of cloud can be mitigated by Online Dispute Resolution (ODR) to great extent. In this paper, we are focusing mainly on three factors, first trying to identify the customer threats, concerns and cross-border conflicts while using cloud computing. Second on ODR (Online Dispute Resolution) and its mechanisms. Finally on required regulatory framework between consumer, industry, and geographic boundaries. An accepted regulatory framework across participants/consumers/providers is currently at a premature stage but as imperative adoption to cloud computing increases across industry there will be paradigm shift in effort sooner than later to build the same.

关键词： Consumer protection security threat Cloud computing Cross-border conflict Online dispute resolution Jurisdiction

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5th Annual privacy Forum, APF 2017

5th Annual Privacy Forum, APF 2017

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5th Annual privacy Forum, APF 2017

ISBN: (纸本)9783319672793

the proceedings contain 12 papers. the special focus in this conference is on Annual privacy Forum. the topics include: Preface;the GDPR and big data: Leading the way for big genetic data?;privacyScore: Improving privacy and security via crowd-sourced benchmarks of websites;privacy data management and awareness for public administrations: A case study from the healthcare domain;better data Protection by Design through Multicriteria Decision Making: On False Tradeoffs Between privacy and Utility;towards a privacy-preserving reliable European identity ecosystem;forget me, forget me not - Redefining the boundaries of the right to be forgotten to address current problems and areas of criticism;a refinement approach for the reuse of privacy risk analysis results;a gamified approach to explore techniques of neutralization of threat actors in cybercrime;privacy by design data exchange between CSIRTs;mr X vs;Mr Y: the emergence of externalities in differential privacy;diffix: High-utility database anonymization;towards a principled approach for engineering privacy by design.

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Semi-supervised knowledge transfer for deep learning from private training data 5

Semi-supervised knowledge transfer for deep learning from pr...

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5th International conference on Learning Representations, ICLR 2017

作者： Papernot, Nicolas Goodfellow, Ian Abadi, Martín Talwar, Kunal Erlingsson, Úlfar Pennsylvania State University United States Google Brain United States Google United States

Some machine learning applications involve training data that is sensitive, such as the medical histories of patients in a clinical trial. A model may inadvertently and implicitly store some of its training data;careful analysis of the model may therefore reveal sensitive information. To address this problem, we demonstrate a generally applicable approach to providing strong privacy guarantees for training data: Private Aggregation of Teacher Ensembles (PATE). the approach combines, in a black-box fashion, multiple models trained with disjoint datasets, such as records from different subsets of users. Because they rely directly on sensitive data, these models are not published, but instead used as "teachers" for a "student" model. the student learns to predict an output chosen by noisy voting among all of the teachers, and cannot directly access an individual teacher or the underlying data or parameters. the student's privacy properties can be understood both intuitively (since no single teacher and thus no single dataset dictates the student's training) and formally, in terms of differential privacy. these properties hold even if an adversary can not only query the student but also inspect its internal workings. Compared with previous work, the approach imposes only weak assumptions on how teachers are trained: it applies to any model, including non-convex models like DNNs. We achieve state-of-the-art privacy/utility trade-offs on MNIST and SVHN thanks to an improved privacy analysis and semi-supervised learning. © ICLR 2019 - conference Track proceedings. All rights reserved.

关键词： Students

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Anonymity Services Tor, I2P, JonDonym: Classifying in the Dark 29

Anonymity Services Tor, I2P, JonDonym: Classifying in the Da...

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29th Int Teletraffic Congress (ITC) / 1st International conference on Networking Science and Practice / 1st International Workshop on Softwarized Infrastructures for 5G and Fog Computing (Soft5) / PhD Workshop on Modelling Communication Networks

作者： Montieri, Antonio Ciuonzo, Domenico Aceto, Giuseppe Pescape, Antonio Univ Napoli Federico II Naples Italy NM2 Srl Naples Italy

ISBN: (纸本)9780988304536

Traffic classification, i.e. associating network traffic to the application that generated it, is an important tool for several tasks, spanning on different fields (security, management, traffic engineering, R&D). this process is challenged by applications that preserve Internet users' privacy by encrypting the communication content, and even more by anonymity tools, additionally hiding the source, the destination, and the nature of the communication. In this paper, leveraging a public dataset released in 2017, we provide (repeatable) classification results with the aim of investigating to what degree the specific anonymity tool (and the traffic it hides) can be identified, when compared to the traffic of the other considered anonymity tools, using machine learning approaches based on the sole statistical features. To this end, four classifiers are trained and tested on the dataset: (i) Naive Bayes, (ii) Bayesian Network, (iii) C4.5, and (iv) Random Forest. Results show that the three considered anonymity networks (Tor, I2P, JonDonym) can be easily distinguished (with an accuracy of 99.99%), telling even the specific application generating the traffic (with an accuracy of 98.00%).

关键词： dark web Tor I2P JonDonym traffic classification anonymity privacy security

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SECURESTREAMS: A reactive middleware framework for secure data stream processing 17

SECURESTREAMS: A reactive middleware framework for secure da...

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11th acm International conference on Distributed Event-Based Systems, DEBS 2017

作者： Havet, Aurélien Pires, Rafael Felber, Pascal Pasin, Marcelo Rouvoy, Romain Schiavoni, Valerio University of Neuchâtel Neuchâtel Switzerland Univ. Lille INRIA IUF Lille France

ISBN: (纸本)9781450350655

the growing adoption of distributed data processing frameworks in a wide diversity of application domains challenges end-to-end integration of properties like security, in particular when considering deployments in the context of large-scale clusters or multi-tenant Cloud infrastructures. this paper therefore introduces SECURESTREAMS, a reactive middleware framework to deploy and process secure streams at scale. Its design combines the high-level reactive dataflow programming paradigm with Intel®'s low-level software guard extensions (SGX) in order to guarantee privacy and integrity of the processed data. the experimental results of SECURESTREAMS are promising: while offering a fluent scripting language based on LUA, our middleware delivers high processing throughput, thus enabling developers to implement secure processing pipelines in just few lines of code. © 2017 acm.

关键词： Middleware

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SQLI Attacks: Current State and Mitigation in SDLC 5th

SQLI Attacks: Current State and Mitigation in SDLC

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5th International conference on Frontiers in Intelligent Computing - theory and applications (FICTA)

作者： Kaur, Daljit Kaur, Parminder Lyallpur Khalsa Coll Jalandhar India Guru Nanak Dev Univ Amritsar Punjab India

ISBN: (纸本)9789811031533;9789811031526

the SQL injection is a predominant type of attack and threat to web applications. this attack attempts to subvert the relationship between a webpage and its supporting database. Due to widespread availability of valuable data and automated tools on web, attackers are motivated to launch high profile attacks on targeted websites. this paper is an effort to know the current state of SQL injection attacks. Different Researchers have proposed various solutions to address SQL injection problems. In this research work, those countermeasures are identified and applied to a vulnerable application and database system, then result are illustrated.

关键词： Attack security Sql injection Secure development Web applications

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proceedings - 2017 IEEE 5th International conference on Future Internet of things and Cloud, FiCloud 2017

Proceedings - 2017 IEEE 5th International Conference on Futu...

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5th IEEE International conference on Future Internet of things and Cloud, FiCloud 2017

ISBN: (纸本)9781538620748

the proceedings contain 51 papers. the topics discussed include: a run time technique for handling error in user-estimated execution times on systems processing MapReduce jobs with deadlines;the effect of workload computational demand variability on the performance of a SaaS cloud with a multi-tier SLA;a Markov-based prediction model for host load detection in live VM migration;service assignment in federated cloud environments based on multi-objective optimization of security;a JSON token-based authentication and access management schema for cloud SaaS applications;ensuring information security for Internet of things;proposal of adaptive data rate algorithm for LoRaWAN-based infrastructure;improve IoT/M2M data organization based on stream patterns;GreenCloudTax: a flexible IaaS tax approach as stimulus for green cloud computing;energy-aware mobile edge computing for low-latency visual data processing;security in lightweight network function virtualisation for federated cloud and IoT;concept for increasing security of national information technology infrastructure and private clouds;an approach to failure prediction in a cloud based environment;performance modelling and analysis of an OpenStack IaaS cloud computing platform;iDoRemind: a location-based reminder application for Android;an integrated platform for dynamic adaptation of multi-tenant single instance SaaS applications;a Raspberry Pi based scalable software defined network infrastructure for disaster relief communication;and converging mobile edge computing, fog computing, and IoT quality requirements.

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International conference on Computer Safety, Reliability, and security, SAFECOMP 2017 and 5th International Workshop on Assurance Cases for Software-Intensive Systems, ASSURE 2017, 12th Workshop on Dependable Embedded and Cyber-physical Systems and Systems-of Systems, DECSoS 2017, 6th International Workshop on Next Generation of System Assurance Approaches for Safety Critical Systems, SASSUR 2017, 3rd International Workshop on Technical and Legal Aspects of data privacy and security, TELERISE 2017 and 2nd International Workshop on the Timing Performance in Safety Engineering, TIPS 2017

International Conference on Computer Safety, Reliability, an...

引用

International conference on Computer Safety, Reliability, and security, SAFECOMP 2017 and 5th International Workshop on Assurance Cases for Software-Intensive Systems, ASSURE 2017, 12th Workshop on Dependable Embedded and Cyber-physical Systems and Systems-of Systems, DECSoS 2017, 6th International Workshop on Next Generation of System Assurance Approaches for Safety Critical Systems, SASSUR 2017, 3rd International Workshop on Technical and Legal Aspects of data privacy and security, TELERISE 2017 and 2nd International Workshop on the Timing Performance in Safety Engineering, TIPS 2017

ISBN: (纸本)9783319662831

the proceedings contain 39 papers. the special focus in this conference is on Computer Safety, Reliability, and security. the topics include: Making the case for safety of machine learning in highly automated driving;a thought experiment on evolution of assurance cases —from a logical aspect;a thought experiment on evolution of assurance cases from a logical aspect;uniform model interface for assurance case integration with system models;integrated model-based development of system and safety cases;a web based GSN editor for multiple stakeholders;towards combined safety and security constraints analysis;reconciling systems-theoretic and component-centric methods for safety and security co-analysis;reconciling systems-theoretic and component-centric methods for safety and security co-analysis;increasing dependability in safety critical CPSs using reflective statecharts;a survey of hardware technologies for mixed-critical integration explored in the project EMC2;a model-based design approach;GSN support of mixed-criticality systems certification;concepts for reliable communication in a software-defined network architecture and combining safety and security analysis for industrial collaborative automation systems.

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Modeling rover communication using hierarchical state machines with scala

Modeling rover communication using hierarchical state machin...

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作者： Havelund, Klaus Joshi, Rajeev Jet Propulsion Laboratory California Institute of Technology Pasadena United States

We demonstrate the application of a new domain-specific language (DSL) for modeling Hierarchical State Machines (HSMs) to the software that manages communications for the Curiosity Mars rover. © Springer Internat... 详细信息

ISBN: (纸本)9783319662831

关键词： application programs

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Research on big data information platform for smart grid 5

Research on big data information platform for smart grid

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5th International Symposium on Project Management, ISPM 2017

作者： Lv, Haiquan Lu, Pengfei Zhang, Jinfan Wuhan University of Technology Wuhan China

ISBN: (纸本)9781921712555

With the continuous development of various technologies, the future power grid is moving in a highly automated and intelligent development. Such a huge system will constantly produce massive data in the power generation, transmission, transformation, distribution, consumption, dispatch or other links, which need a powerful information platform as a support. Big data add into new vitality for the development of smart grid, cloud computing technology has the advantage of high security and large data processing capacity. Based on the analysis of big data, cloud computing and smart grid, this paper gives the general framework of power data platform and summarizes the application of cloud computing in the big data of smart grid, and then puts forward an information platform based on the cloud computing, constructs a data cloud model based on smart grid. Finally the paper puts forward several unsolved problems based on the whole text.

关键词： Smart power grids

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