Practical performance of Bloom filters and parallel free-text searching
Communications of the ACM
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Analysis of arithmetic coding for data compression
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Summary cache: a scalable wide-area Web cache sharing protocol
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OceanStore: an architecture for global-scale persistent storage
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
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The Bloomier filter: an efficient data structure for static support lookup tables
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
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An optimal Bloom filter replacement
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CAPTRA: coordinated packet traceback
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Approximately detecting duplicates for streaming data using stable bloom filters
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Beyond bloom filters: from approximate membership checks to approximate state machines
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Information Processing Letters
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Information Processing and Management: an International Journal
TAPER: tiered approach for eliminating redundancy in replica synchronization
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CoNEXT '06 Proceedings of the 2006 ACM CoNEXT conference
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Data & Knowledge Engineering
On the false-positive rate of Bloom filters
Information Processing Letters
Broadcast Authentication in Sensor Networks Using Compressed Bloom Filters
DCOSS '08 Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems
Bloomier Filters: A Second Look
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
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OPODIS '08 Proceedings of the 12th International Conference on Principles of Distributed Systems
Optimizing Distributed Joins with Bloom Filters
ICDCIT '08 Proceedings of the 5th International Conference on Distributed Computing and Internet Technology
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IEICE - Transactions on Information and Systems
Efficient access enforcement in distributed role-based access control (RBAC) deployments
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CSR '09 Proceedings of the Fourth International Computer Science Symposium in Russia on Computer Science - Theory and Applications
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Traceback-based Bloomfilter IPS in defending SYN flooding attack
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Trustworthy vacuuming and litigation holds in long-term high-integrity records retention
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INFOCOM'10 Proceedings of the 29th conference on Information communications
Denial of service attack-resistant flooding authentication in wireless sensor networks
Computer Communications
Real-time memory efficient data redundancy removal algorithm
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
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Cardinality estimation and dynamic length adaptation for Bloom filters
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A Generalized Bloom Filter to Secure Distributed Network Applications
Computer Networks: The International Journal of Computer and Telecommunications Networking
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OTM'05 Proceedings of the 2005 Confederated international conference on On the Move to Meaningful Internet Systems - Volume >Part I
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Computer Networks: The International Journal of Computer and Telecommunications Networking
IQN routing: integrating quality and novelty in P2P querying and ranking
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
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UIC'06 Proceedings of the Third international conference on Ubiquitous Intelligence and Computing
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A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Although Bloom filters allow false positives, for many applications the space savings outweigh this drawback when the probability of an error is sufficiently low. We introduce compressed Bloom filters, which improve performance when the Bloom filter is passed as a message, and its transmission size is a limiting factor. For example, Bloom filters have been suggested as a means for sharing Web cache information. In this setting, proxies do not share the exact contents of their caches, but instead periodically broadcast Bloom filters representing their caches. By using compressed Bloom filters, proxies can reduce the number of bits broadcast, the false positive probability, and/or the amount of computation per lookup. The cost is the processing time for compression and decompression, which can use simple arithmetic coding, and more memory use at the proxies, which utilize the larger uncompressed form of the Bloom filter.