Signature-based methods for data streams

被引：42

作者：

Cortes, C ^{[1
]}

Pregibon, D ^{[1
]}

机构：

[1] AT&T Labs Res, Shannon Lab, Florham Park, NJ 07932 USA

来源：

DATA MINING AND KNOWLEDGE DISCOVERY | 2001年 / 5卷 / 03期

关键词：

transactional data streams; signatures; large scale data mining;

D O I：

10.1023/A:1011464915332

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We have been developing signature-based methods in the telecommunications industry for the past 5 years. In this paper, we describe our work as it evolved due to improvements in technology and our aggressive attitude toward scale. We discuss the types of features that our signatures contain, nuances of how these are updated through time, our treatment of outliers, and the trade-off between time-driven and event-driven processing. We provide a number of examples, all drawn from the application of signatures to toll fraud detection.

引用

页码：167 / 182

页数：16

共 8 条

[1] BURGE P, 1997, P AI APPR FRAUD DET, P9
[2] Cortes C., 2000, Proceedings. KDD-2000. Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, P9, DOI 10.1145/347090.347094
[3] CORTES C, 1999, P KDD99
[4] AN INTRUSION-DETECTION MODEL
DENNING, DE
[J]. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 1987, 13 (02) : 222 - 232
[5] DuMouchel W, 1999, AM STAT, V53, P177, DOI 10.2307/2686093
[6] Adaptive fraud detection
Fawcett, T
Provost, F
[J]. DATA MINING AND KNOWLEDGE DISCOVERY, 1997, 1 (03) : 291 - 316
[7] Flake G. W., 2000, Proceedings. KDD-2000. Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, P150, DOI 10.1145/347090.347121
[8] Survey of intrusion detection techniques
Lunt, Teresa F.
[J]. Computers and Security, 1993, 12 (04) : 405 - 418

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