TY - GEN
T1 - An immune-based model for computer virus detection
AU - Li, Tao
AU - Liu, Xiaojie
AU - Li, Hongbin
PY - 2005
Y1 - 2005
N2 - Inspired by biological immune systems, a new immune-based model for computer virus detection is proposed in this paper. Quantitative description of the model is given. A dynamic evolution model for self/nonself description is presented, which reduces the size of self set. Furthermore, an evolutive gene library is introduced to improve the generating efficiency of mature detectors, reducing the system time spending, false-negative and false-positive rates. Experiments show that this model has better time efficiency and detecting ability than the classical model ARTIS.
AB - Inspired by biological immune systems, a new immune-based model for computer virus detection is proposed in this paper. Quantitative description of the model is given. A dynamic evolution model for self/nonself description is presented, which reduces the size of self set. Furthermore, an evolutive gene library is introduced to improve the generating efficiency of mature detectors, reducing the system time spending, false-negative and false-positive rates. Experiments show that this model has better time efficiency and detecting ability than the classical model ARTIS.
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U2 - 10.1007/11599371_6
DO - 10.1007/11599371_6
M3 - Conference contribution
AN - SCOPUS:33744818877
SN - 3540308490
SN - 9783540308492
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 59
EP - 71
BT - Cryptology and Network Security - 4th International Conference, CANS 2005, Proceedings
T2 - 4th International Conference on Cryptology and Network Security, CANS 2005
Y2 - 14 December 2005 through 16 December 2005
ER -