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Simultaneous scalability and security for data-intensive web applications

Published:27 June 2006Publication History

ABSTRACT

For Web applications in which the database component is the bottleneck, scalability can be provided by a third-party Database Scalability Service Provider (DSSP) that caches application data and supplies query answers on behalf of the application. Cost-effective DSSPs will need to cache data from many applications, inevitably raising concerns about security. However, if all data passing through a DSSP is encrypted to enhance security, then data updates trigger invalidation of large regions of cache. Consequently, achieving good scalability becomes virtually impossible. There is a tradeoff between security and scalability, which requires careful consideration.In this paper we study the security-scalability tradeoff, both formally and empirically. We begin by providing a method for statically identifying segments of the database that can be encrypted without impacting scalability. Experiments over a prototype DSSP system show the effectiveness of our static analysis method--for all three realistic bench-mark applications that we study, our method enables a significant fraction of the database to be encrypted without impacting scalability. Moreover, most of the data that can be encrypted without impacting scalability is of the type that application designers will want to encrypt, all other things being equal. Based on our static analysis method, we propose a new scalability-conscious security design methodology that features: (a) compulsory encryption of highly sensitive data like credit card information, and (b) encryption of data for which encryption does not impair scalability. As a result, the security-scalability tradeoff needs to be considered only over data for which encryption impacts scalability, thus greatly simplifying the task of managing the tradeoff.

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      cover image ACM Conferences
      SIGMOD '06: Proceedings of the 2006 ACM SIGMOD international conference on Management of data
      June 2006
      830 pages
      ISBN:1595934340
      DOI:10.1145/1142473

      Copyright © 2006 ACM

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      Publication History

      • Published: 27 June 2006

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