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» Detecting worm variants using machine learning
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112
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DSMML
2004
Springer
15 years 8 months ago
SVM Based Learning System for Information Extraction
Abstract. We present an SVM-based learning algorithm for information extraction, including experiments on the influence of different algorithm settings. Our approach needs fewer ...
Yaoyong Li, Kalina Bontcheva, Hamish Cunningham
121
Voted
ICASSP
2009
IEEE
15 years 9 months ago
A semi-supervised learning approach to online audio background detection
We present a framework for audio background modeling of complex and unstructured audio environments. The determination of background audio is important for understanding and predi...
Selina Chu, Shrikanth S. Narayanan, C.-C. Jay Kuo
129
Voted
ICIP
2004
IEEE
16 years 4 months ago
Steganalysis of quantization index modulation data hiding
Quantization index modulation (QIM) techniques have been gaining popularity in the data hiding community because of their robustness and information-theoretic optimality against a...
Kenneth Sullivan, Zhiqiang Bi, Upamanyu Madhow, Sh...
145
Voted
EMSOFT
2006
Springer
15 years 6 months ago
Defining a strategy to introduce a software product line using existing embedded systems
Engine Control Systems (ECS) for automobiles have numerous variants for many manufactures and different markets. To improve development efficiency, exploiting ECS commonalities an...
Kentaro Yoshimura, Dharmalingam Ganesan, Dirk Muth...
116
Voted
NDSS
2006
IEEE
15 years 8 months ago
Protocol-Independent Adaptive Replay of Application Dialog
For many applications—including recognizing malware variants, determining the range of system versions vulnerable to a given attack, testing defense mechanisms, and filtering m...
Weidong Cui, Vern Paxson, Nicholas Weaver, Randy H...