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An Urban Sensing Architecture as Essential Infrastructure for Future Cities 14

An Urban Sensing Architecture as Essential Infrastructure fo...

引用

IEEE/acm 14th International conference on Utility and Cloud Computing

作者： Kumar, Vijay Oikonomou, George Tryfonas, Theo Univ Bristol Bristol Avon England

ISBN: (纸本)9781450391634

Climate change and migration have become one of the most challenging problems for our civilization. In this context, city councils work hard to manage essential services for citizens such as waste collection, street lamp lighting, and water supply. Increasingly, digitalization and the Internet of Things (IoT) help cities improve services, increase productivity and reduce costs. However, to understand how this may happen, we explore the urban sensing capabilities from citizen- to city-scale, how sensing at different levels is interlinked, and the challenges of managing innovations based on IoT data and devices. Local authorities collaborate with researchers and deploy testbeds as a part of demonstration and research projects to perform the above data collection, improve city services, and support innovation. The data gathered is about indoor and outdoor environmental conditions, energy usage, built environment, structural health monitoring. Such monitoring requires IT infrastructure at three different tiers: at the endpoint, edge, and cloud. Managing infrastructure at all tiers with provisioning, connectivity, security updates of devices, user data privacy controls, visualization of data, multi-tenancy of applications, and network resilience, is challenging. So, in turn, we focus on performing a systematic study of the technical and non-technical challenges faced during the implementation, management, and deployment of devices into citizens' homes and public spaces. Our third piece of work explores IoT edge applications' resiliency and reliability requirements that vary from non-critical (best delivery efforts) to safety-critical with time-bounded guarantees. We investigate how to meet IoT application mixed-criticality QoS requirements in multi-communication networks. Finally, to demonstrate the principles of our framework in the real world, we implement an open-source air quality platform Open City Air Quality Platform (OpenCAQP), that merges a wide range of data so

关键词： Urban Sensing data monitoring infrastructure IoT

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Fast database Joins and PSI for Secret Shared data 20

Fast Database Joins and PSI for Secret Shared Data

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acm SIGSAC conference on Computer and Communications security (acm CCS)

作者： Mohassel, Payman Rindal, Peter Rosulek, Mike Facebook Cambridge MA 02142 USA Visa Res Palo Alto CA USA Oregon State Univ Corvallis OR 97331 USA

ISBN: (纸本)9781450370899

We present a scalable protocol for database joins on secret shared data in the honest-majority three-party setting. The key features of our protocol are a rich set of SQL-like join/select queries and the ability to compose join operations together due to the inputs and outputs being generically secret shared between the parties. Provided that all joins operate on unique primary keys, no information is revealed to any party during the protocol. In particular, not even the sizes of intermediate joins are revealed. All of our protocols are constant-round and achieve O (n) communication and computation overhead for joining two tables of n rows. These properties make our protocol ideal for outsourced secure computation. In this setting several non-colluding servers are setup and the input data is shared among them. These servers then perform the relevant secret shared computation and output the result. This model has recently been gaining traction in industry, e.g. Facebook's Crypten, Cape privacy's TFEncrypted, Mozilla Telemetry. We additionally implement two applications on top of our framework. The first application detects voter registration errors within and between agencies of 50 US states, in a privacy-preserving manner. The second application allows several organizations to compare network security logs to more accurately identify common security threats, e.g. the IP addresses of a bot net. In both cases, the practicality of these applications depends on efficiently performing joins on millions of secret shared records. For example, our three party protocol can perform a join on two sets of 1 million records in 4.9 seconds or, alternatively, compute the cardinality of this join in just 3.1 seconds.

关键词： Network security

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Vallum-Med: Protecting Medical data in Cloud Environments 20

Vallum-Med: Protecting Medical Data in Cloud Environments

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29th acm International conference on Information and Knowledge Management (CIKM)

作者： Peterson, Ronny da Silva, Altigran Carvalho, Andre Fetzer, Christof Martin, Andre Blanquer, Ignacio Univ Fed Amazonas Manaus Amazonas Brazil Tech Univ Dresden Dresden Germany Univ Politecn Valencia Valencia Spain

ISBN: (纸本)9781450368599

Despite the many advantages of cloud computing, keeping information in such an environment increases the risk of cyber attacks, as well as the possibility of unauthorized access by cloud provider employees. Another critical concern is privacy protection, since depending on data access control, confidential information may be exposed even through authorized access. To solve these issues we have previously proposed Vallum, a platform that leverages Intel SGX protection to ensure the security, confidentiality, and integrity of data at rest and during processing. It also provides tools for privacy protection, following policies set by the data owner. In this demo we present Vallum-Med, an application of Vallum for the protection of medical patient personal data, including imaging results of their cardiac examinations. We will demonstrate that this system fully supports cloud protection of such sensitive data as well as the definition of privacy policies and ensuring that all results of queries are compliant to these policies. All processing, data storage and network traffic are protected using SCONE, a docker container-based technology for seamlessly incorporating SGX protection for applications, which provides a fully encrypted memory environment.

关键词： privacy security Cloud Computing Medical data

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Session details: Session 6 Hardware and Device security/privacy 21

Session details: Session 6 Hardware and Device Security/Priv...

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proceedings of the Eleventh acm conference on data and application security and privacy

作者： Ziming Zhao University at Buffalo

No abstract available.

ISBN: (纸本)9781450381437

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GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models 20

GAN-Leaks: A Taxonomy of Membership Inference Attacks agains...

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acm SIGSAC conference on Computer and Communications security (acm CCS)

作者： Chen, Dingfan Yu, Ning Zhang, Yang Fritz, Mario CISPA Helmholtz Ctr Informat Secur Saarbrucken Germany Univ Maryland College Pk MD 20742 USA Max Planck Inst Informat Saarbrucken Germany

ISBN: (纸本)9781450370899

Deep learning has achieved overwhelming success, spanning from discriminative models to generative models. In particular, deep generative models have facilitated a new level of performance in a myriad of areas, ranging from media manipulation to sanitized dataset generation. Despite the great success, the potential risks of privacy breach caused by generative models have not been analyzed systematically. In this paper, we focus on membership inference attack against deep generative models that reveals information about the training data used for victim models. Specifically, we present the first taxonomy of membership inference attacks, encompassing not only existing attacks but also our novel ones. In addition, we propose the first generic attack model that can be instantiated in a large range of settings and is applicable to various kinds of deep generative models. Moreover, we provide a theoretically grounded attack calibration technique, which consistently boosts the attack performance in all cases, across different attack settings, data modalities, and training configurations. We complement the systematic analysis of attack performance by a comprehensive experimental study, that investigates the effectiveness of various attacks w.r.t. model type and training configurations, over three diverse application scenarios (i.e., images, medical data, and location data).

关键词： Membership inference attacks deep learning generative models privacy-preserving machine learning

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Explore the Transformation Space for Adversarial Images 20

Explore the Transformation Space for Adversarial Images

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10th acm conference on data and application security and privacy (CODASPY)

作者： Chen, Jiyu Wang, David Chen, Hao Univ Calif Davis Davis CA 95616 USA Vestavia Hills High Sch Vestavia Hills AL USA

ISBN: (纸本)9781450371070

Deep learning models are vulnerable to adversarial examples. Most of current adversarial attacks add pixel-wise perturbations restricted to some L-p -norm, and defense models are evaluated also on adversarial examples restricted inside L-p-norm balls. However, we wish to explore adversarial examples exist beyond L-p-norm balls and their implications for attacks and defenses. In this paper, we focus on adversarial images generated by transformations. We start with color transformation and propose two gradient-based attacks. Since L-p-norm is inappropriate for measuring image quality in the transformation space, we use the similarity between transformations and the Structural Similarity Index. Next, we explore a larger transformation space consisting of combinations of color and affine transformations. We evaluate our transformation attacks on three data sets - CIFAR10, SVHN, and ImageNet - and their corresponding models. Finally, we perform retraining defenses to evaluate the strength of our attacks. The results show that transformation attacks are powerful. They find high-quality adversarial images that have higher transferability and misclassification rates than C&W's L-p attacks, especially at high confidence levels. They are also significantly harder to defend against by retraining than C&W's L-p attacks. More importantly, exploring different attack spaces makes it more challenging to train a universally robust model.

关键词： Adversarial attacks Image transformation Deep learning security

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Session details: Session 3: privacy 21

Session details: Session 3: Privacy

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proceedings of the Eleventh acm conference on data and application security and privacy

作者： Maribel Fernandez King's College London

No abstract available.

ISBN: (纸本)9781450381437

No abstract available.

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Post-Quantum TLS Without Handshake Signatures 20

Post-Quantum TLS Without Handshake Signatures

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acm SIGSAC conference on Computer and Communications security (acm CCS)

作者： Schwabe, Peter Stebila, Douglas Wiggers, Thom Max Planck Inst Secur & Privacy Bochum Germany Radboud Univ Nijmegen Nijmegen Netherlands Univ Waterloo Waterloo ON Canada

ISBN: (纸本)9781450370899

We present KEMTLS, an alternative to the TLS 1.3 handshake that uses key-encapsulation mechanisms (KEMs) instead of signatures for server authentication. Among existing post-quantum candidates, signature schemes generally have larger public key/signature sizes compared to the public key/ciphertext sizes of KEMs: by using an IND-CCA-secure KEM for server authentication in post-quantum TLS, we obtain multiple benefits. A size-optimized post-quantum instantiation of KEMTLS requires less than half the bandwidth of a size-optimized post-quantum instantiation of TLS 1.3. In a speed-optimized instantiation, KEMTLS reduces the amount of server CPU cycles by almost 90% compared to TLS 1.3, while at the same time reducing communication size, reducing the time until the client can start sending encrypted application data, and eliminating code for signatures from the server's trusted code base.

关键词： Post-quantum cryptography key-encapsulation mechanisms Transport Layer security NIST PQC

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Session details: Session 7 Software security and Malware 21

Session details: Session 7 Software Security and Malware

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proceedings of the Eleventh acm conference on data and application security and privacy

作者： Yonghwi Kwon University of Virginia

No abstract available.

ISBN: (纸本)9781450381437

No abstract available.

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OAuth 2.0-based authentication solution for FPGA-enabled cloud computing 21

OAuth 2.0-based authentication solution for FPGA-enabled clo...

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proceedings of the 14th IEEE/acm International conference on Utility and Cloud Computing Companion

作者： Semih Ince David Espes Guy Gogniat Julien Lallet Renaud Santoro Nokia Bell Labs Univ. Bretagne Occidentale Univ. Bretagne Sud

ISBN: (纸本)9781450391634

FPGA-enabled cloud computing is getting more and more common as cloud providers offer hardware accelerated solutions. In this context, clients need confidential remote computing. However Intellectual Properties and data are being used and communicated. So current security models require the client to trust the cloud provider blindly by disclosing sensitive information. In addition, the lack of strong authentication and access control mechanisms, for both the client and the provided FPGA in current solutions, is a major security drawback. To enhance security measures and privacy between the client, the cloud provider and the FPGA, an additional entity needs to be introduced: the trusted authority. Its role is to authenticate the client-FPGA pair and isolate them from the cloud provider. With our novel OAuth 2.0-based access delegation solution for FPGA-accelerated clouds, a remote confidential FPGA environment with a token-based access can be created for the client. Our solution allows to manage and securely allocate heterogeneous resource pools with enhanced privacy & confidentiality for the client. Our formal analysis shows that our protocol adds a very small latency which is suitable for real-time application.

关键词： cloud OAuth security authentication FPGA

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