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INCDM
2010
Springer
159views Data Mining» more  INCDM 2010»
15 years 6 months ago
Semi-supervised Learning for False Alarm Reduction
Abstract. Intrusion Detection Systems (IDSs) which have been deployed in computer networks to detect a wide variety of attacks are suffering how to manage of a large number of tri...
Chien-Yi Chiu, Yuh-Jye Lee, Chien-Chung Chang, Wen...
RAID
1999
Springer
15 years 5 months ago
Towards trapping wily intruders in the large
The rapid increase in network bandwidth from mega bits per second to giga bits per second and potentially to tera bits per second, is making it increasingly difficult to carry out...
Glenn Mansfield
ACSAC
2007
IEEE
15 years 7 months ago
Database Isolation and Filtering against Data Corruption Attacks
Various attacks (e.g., SQL injections) may corrupt data items in the database systems, which decreases the integrity level of the database. Intrusion detections systems are becomi...
Meng Yu, Wanyu Zang, Peng Liu
INFOCOM
2012
IEEE
13 years 3 months ago
Stochastic analysis of horizontal IP scanning
—Intrusion Detection Systems (IDS) have become ubiquitous in the defense against virus outbreaks, malicious exploits of OS vulnerabilities, and botnet proliferation. As attackers...
Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri...
ISWC
2003
IEEE
15 years 6 months ago
Unsupervised, Dynamic Identification of Physiological and Activity Context in Wearable Computing
Context-aware computing describes the situation where a wearable / mobile computer is aware of its user’s state and surroundings and modifies its behavior based on this informat...
Andreas Krause, Daniel P. Siewiorek, Asim Smailagi...