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TJS
2010
182views more  TJS 2010»
13 years 4 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
ICDCS
2010
IEEE
13 years 9 months ago
Sifting through Network Data to Cull Activity Patterns with HEAPs
—Today’s large campus and enterprise networks are characterized by their complexity, i.e. containing thousands of hosts, and diversity, i.e. with various applications and usage...
Esam Sharafuddin, Yu Jin, Nan Jiang, Zhi-Li Zhang
AINA
2007
IEEE
14 years 1 hour ago
Intrusion Detection for Encrypted Web Accesses
As various services are provided as web applications, attacks against web applications constitute a serious problem. Intrusion Detection Systems (IDSes) are one solution, however,...
Akira Yamada, Yutaka Miyake, Keisuke Takemori, Ahr...
ANCS
2007
ACM
13 years 9 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...
PKDD
2009
Springer
134views Data Mining» more  PKDD 2009»
14 years 5 days ago
Mining Graph Evolution Rules
In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequenc...
Michele Berlingerio, Francesco Bonchi, Björn ...