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» Detecting anomalous access patterns in relational databases
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KDD
2007
ACM
168views Data Mining» more  KDD 2007»
14 years 8 months ago
Finding tribes: identifying close-knit individuals from employment patterns
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
Lisa Friedland, David Jensen
VLDB
2002
ACM
116views Database» more  VLDB 2002»
13 years 7 months ago
Watermarking Relational Databases
We enunciate the need for watermarking database relations to deter their piracy, identify the unique characteristics of relational data which pose new challenges for watermarking,...
Rakesh Agrawal, Jerry Kiernan
WWW
2010
ACM
14 years 2 months ago
HTTP database connector (HDBC): RESTful access to relational databases
Relational databases hold a vast quantity of information and making them accessible to the web is an big challenge. There is a need to make these databases accessible with as litt...
Alexandros Marinos, Erik Wilde, Jiannan Lu
VLDB
2003
ACM
156views Database» more  VLDB 2003»
14 years 7 months ago
Watermarking relational data: framework, algorithms and analysis
We enunciate the need for watermarking database relations to deter data piracy, identify the characteristics of relational data that pose unique challenges for watermarking, and de...
Rakesh Agrawal, Peter J. Haas, Jerry Kiernan
ANCS
2007
ACM
13 years 11 months ago
High-speed detection of unsolicited bulk emails
We propose a Progressive Email Classifier (PEC) for highspeed classification of message patterns that are commonly associated with unsolicited bulk email (UNBE). PEC is designed t...
Sheng-Ya Lin, Cheng-Chung Tan, Jyh-Charn Liu, Mich...