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CVPR
2010
IEEE
15 years 11 months ago
An Online Approach: Learning-Semantic-Scene-by-Tracking and Tracking-by-Learning-Semantic-Scene
Learning the knowledge of scene structure and tracking a large number of targets are both active topics of computer vision in recent years, which plays a crucial role in surveilla...
Xuan Song, Xiaowei Shao, Huijing Zhao, Jinshi Cui,...
USS
2008
15 years 9 months ago
In Defense of Pseudorandom Sample Selection
Generation of random numbers is a critical component of existing post-election auditing techniques. Recent work has largely discouraged the use of all pseudorandom number generato...
Joseph A. Calandrino, J. Alex Halderman, Edward W....
IMC
2009
ACM
16 years 1 months ago
ANTIDOTE: understanding and defending against poisoning of anomaly detectors
Statistical machine learning techniques have recently garnered increased popularity as a means to improve network design and security. For intrusion detection, such methods build ...
Benjamin I. P. Rubinstein, Blaine Nelson, Ling Hua...
CCS
1999
ACM
15 years 11 months ago
A High-Performance Network Intrusion Detection System
In this paper we present a new approach for network intrusion detection based on concise specifications that characterize normal and abnormal network packet sequences. Our speciļ...
R. Sekar, Y. Guang, S. Verma, T. Shanbhag
DIMVA
2008
15 years 8 months ago
Embedded Malware Detection Using Markov n-Grams
Embedded malware is a recently discovered security threat that allows malcode to be hidden inside a benign file. It has been shown that embedded malware is not detected by commerci...
M. Zubair Shafiq, Syed Ali Khayam, Muddassar Faroo...