National Institute of Standards and Technology における超伝導研究及び生活

Today’s cloud computing infrastructure requires substantial trust. Cloud users rely on both the provider’s staff and its globally distributed software/hardware platform not to expose any of their private data.We introduce the notion of shielded execution, which protects the confidentiality and integrity of a program and its data from the platform on which it runs (i.e., the cloud operator’s OS, VM, and firmware). Our prototype, Haven, is the first system to achieve shielded execution of unmodified legacy applications, including SQL Server and Apache, on a commodity OS (Windows) and commodity hardware. Haven leverages the hardware protection of Intel SGX to defend against privileged code and physical attacks such as memory probes, and also addresses the dual challenges of executing unmodified legacy binaries and protecting them from a malicious host. This work motivated recent changes in the SGX specification.

Shielding Applications from an Untrusted Cloud with Haven

We present VC3, the first system that allows users to run distributed MapReduce computations in the cloud while keeping their code and data secret, and ensuring the correctness and completeness of their results. VC3 runs on unmodified Hadoop, but crucially keeps Hadoop, the operating system and the hyper visor out of the TCB, thus, confidentiality and integrity are preserved even if these large components are compromised. VC3 relies on SGX processors to isolate memory regions on individual computers, and to deploy new protocols that secure distributed MapReduce computations. VC3 optionally enforces region self-integrity invariants for all MapReduce code running within isolated regions, to prevent attacks due to unsafe memory reads and writes. Experimental results on common benchmarks show that VC3 performs well compared with unprotected Hadoop: VC3's average runtime overhead is negligible for its base security guarantees, 4.5% with write integrity and 8% with read/write integrity.

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VC3: Trustworthy Data Analytics in the Cloud Using SGX

This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.

Decision Forests for Computer Vision and Medical Image Analysis

Privacy-preserving multi-party machine learning allows multiple organizations to perform collaborative data analytics while guaranteeing the privacy of their individual datasets. Using trusted SGX-processors for this task yields high performance, but requires a careful selection, adaptation, and implementation of machine-learning algorithms to provably prevent the exploitation of any side channels induced by data-dependent access patterns.

We propose data-oblivious machine learning algorithms for support vector machines, matrix factorization, neural networks, decision trees, and k-means clustering. We show that our efficient implementation based on Intel Skylake processors scales up to large, realistic datasets, with overheads several orders of magnitude lower than with previous approaches based on advanced cryptographic multi-party computation schemes.

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Oblivious multi-party machine learning on trusted processors

This paper describes the design of the Cipherbase system. Cipherbase is a full-fledged SQL database system that achieves high performance and high data confidentiality by storing and processing strongly encrypted data. The Cipherbase system incorporates customized trusted hardware, extending Microsoft’s SQL Server for efficient execution of queries using both secure hardware and commodity servers. This paper presents the design of the Cipherbase secure hardware and its implementation using FPGAs. Furthermore, this paper shows how we addressed hardware / software co-design in the Cipherbase system.

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Orthogonal Security With Cipherbase

FPGA manufacturers have offered devices with bitstream protection for a number of years. This feature is currently primarily used to prevent IP piracy through cloning. However, in this paper we describe how protected bitstreams can also be used to create a root of trust for the clients of cloud computing services. Unlike related software-based solutions, this hardware-based approach solves a fundamental problem that currently impedes the greater adoption of cloud computing: how to secure client data and computation from both potential external attackers and an untrusted system administrator. We examine how this approach can be applied to the specific application of handling sensitive health data. This system maintains the advantages of the cloud with minimal additional hardware. We also describe how this system can be extended to provide a more generic secure cloud architecture.

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FPGAs for trusted cloud computing

Cipherbase is a comprehensive database system that provides strong end-to-end data confidentiality through encryption. Cipherbase is based on a novel architecture that combines an industrial strength database engine (SQL Server) with lightweight processing over encrypted data that is performed in secure hardware. The overall architecture provides significant benefits over the state-of-the-art in terms of security, performance, and functionality. This paper presents a prototype of Cipherbase that uses FPGAs to provide secure processing and describes the system engineering details implemented to achieve competitive performance for transactional workloads. This includes hardware-software co-design issues (e.g. how to best offer parallelism), optimizations to hide the latency between the secure hardware and the main system, and techniques to cope with space inefficiencies. All these optimizations were carefully designed not to affect end-to-end data confidentiality. Our experiments with the TPC-C benchmark show that in the worst case when all data are strongly encrypted, Cipherbase achieves 40% of the throughput of plaintext SQL Server. In more realistic cases, if only critical data such as customer names are encrypted, the Cipherbase throughput is more than 90% of plaintext SQL Server.

https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/cipherbase.pdf

Transaction processing on confidential data using cipherbase

Field-Programmable Gate Arrays (FPGAs) are integrated circuits that implement reconfigurable hardware. They are used in modern systems, creating specialized, highly-optimized integrated circuits without the need to design and manufacture dedicated chips. As the capacity of FPGAs grows, it is increasingly common for designers to incorporate implementations of algorithms and protocols from a range of third-party sources. The monolithic nature of FPGAs means that all on-chip circuits, including third party black-box designs, must share common on-chip infrastructure, such as routing resources. In this paper, we observe that a "long" routing wire carrying a logical 1 reduces the propagation delay of other adjacent but unconnected long wires in the FPGA interconnect, thereby leaking information about its state. We exploit this effect and propose a communication channel that can be used for both covert transmissions between circuits, and for exfiltration of secrets from the chip. We show that the effect is measurable for both static and dynamic signals, and that it can be detected using very small on-board circuits. In our prototype, we are able to correctly infer the logical state of an adjacent long wire over 99% of the time, even without error correction, and for signals that are maintained for as little as 82us. Using a Manchester encoding scheme, our channel bandwidth is as high as 6kbps. We characterize the channel in detail and show that it is measurable even when multiple competing circuits are present and can be replicated on different generations and families of Xilinx devices (Virtex 5, Virtex 6, and Artix 7). Finally, we propose countermeasures that can be deployed by systems and tools designers to reduce the impact of this information leakage.

Leaky Wires: Information Leakage and Covert Communication Between FPGA Long Wires

Data confidentiality is one of the main concerns for users of public cloud services. The key problem is protecting sensitive data from being accessed by cloud administrators who have root privileges and can remotely inspect the memory and disk contents of the cloud servers. While encryption is the basic mechanism that can leveraged to provide data confidentiality, providing an efficient database-as-a-service that can run on encrypted data raises several interesting challenges. In this demonstration we outline the functionality of Cipherbase --- a full fledged SQL database system that supports the full generality of a database system while providing high data confidentiality. Cipherbase has a novel architecture that tightly integrates custom-designed trusted hardware for performing operations on encrypted data securely such that an administrator cannot get access to any plaintext corresponding to sensitive data.

Ken Eguro

Papers

Orthogonal Security With Cipherbase

FPGAs for trusted cloud computing

Transaction processing on confidential data using cipherbase

Leaky Wires: Information Leakage and Covert Communication Between FPGA Long Wires

Secure database-as-a-service with Cipherbase