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Dive into the research topics where Ravi Ramamurthy is active.

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Featured researches published by Ravi Ramamurthy.


international conference on data engineering | 2015

Transaction processing on confidential data using cipherbase

Arvind Arasu; Ken Eguro; Manas Joglekar; Raghav Kaushik; Donald Kossmann; Ravi Ramamurthy

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.


field-programmable logic and applications | 2013

A secure coprocessor for database applications

Arvind Arasu; Ken Eguro; Raghav Kaushik; Donald Kossmann; Ravi Ramamurthy; Ramarathnam Venkatesan

The scalability and availability of cloud computing makes it an ideal platform for many database applications. However, it is challenging to secure sensitive client information in a practical and rigorous manner against both external attackers and curious cloud administrators. In this paper, we describe a novel secure FPGA-based query coprocessor and discuss how it can be tightly integrated with a commercial database system such as SQL Server. This combination, called Cipherbase, leverages efficient division of labor - using a conventional untrusted cloud server to handle mundane database operations while sensitive data is segregated and processed in trusted hardware to ensure confidentiality. We examine the architectural design issues that affect the achievable performance of the system and report initial results demonstrating the effectiveness for real-world cloud database applications.


international conference on data engineering | 2013

Querying encrypted data

Arvind Arasu; Ken Eguro; Raghav Kaushik; Ravi Ramamurthy

Data security is a serious concern when we migrate data to a cloud DBMS. Database encryption, where sensitive columns are encrypted before they are stored in the cloud, has been proposed as a mechanism to address such data security concerns. The intuitive expectation is that an adversary cannot “learn” anything about the encrypted columns, since she does not have access to the encryption key. However, query processing becomes a challenge since it needs to “look inside” the data. This tutorial explores the space of designs studied in prior work on processing queries over encrypted data. We cover approaches based on both classic client-server and involving the use of a trusted hardware module where data can be securely decrypted. We discuss the privacy challenges that arise in both approaches and how they may be addressed. Briefly, supporting the full complexity of a modern DBMS including complex queries, transactions and stored procedures leads to significant challenges that we survey.


international conference on management of data | 2017

Concerto: A High Concurrency Key-Value Store with Integrity

Arvind Arasu; Ken Eguro; Raghav Kaushik; Donald Kossmann; Pingfan Meng; Vineet Pandey; Ravi Ramamurthy

Verifying the integrity of outsourced data is a classic, well-studied problem. However current techniques have fundamental performance and concurrency limitations for update-heavy workloads. In this paper, we investigate the potential advantages of deferred and batched verification rather than the per-operation verification used in prior work. We present Concerto, a comprehensive key-value store designed around this idea. Using Concerto, we argue that deferred verification preserves the utility of online verification and improves concurrency resulting in orders-of-magnitude performance improvement. On standard benchmarks, the performance of Concerto is within a factor of two when compared to state-of-the-art key-value stores without integrity.


symposium on cloud computing | 2017

Towards verifiable metering for database as a service providers

Min Du; Ravi Ramamurthy

Metering is an important component of cloud database services. We discuss potential problems in verifiability for existing DBaaS metering and initiate a discussion of how we can address this problem.


very large data bases | 2007

Stop-and-restart style execution for long running decision support queries

Surajit Chaudhuri; Raghav Kaushik; Abhijit Pol; Ravi Ramamurthy


Archive | 2010

Transformation rule profiling for a query optimizer

Surajit Chaudhuri; Leo Giakoumakis; Vivek R. Narasayya; Ravi Ramamurthy


Archive | 2011

Optimizing fine grained access control using authorization indexes

Ravi Ramamurthy; Raghav Kaushik; Abhijeet Mohapatra


Archive | 2013

Querying Encrypted Data (Tutorial)

Arvind Arasu; Ken Eguro; Raghav Kaushik; Ravi Ramamurthy


Archive | 2013

Auditing of sql queries using select triggers

Ravi Ramamurthy; Shriraghav Kaushik; Daniel Fabbri

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