A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling
Computers and Operations Research
Effects of Symbiotic Evolution in Genetic Algorithms for Job-Shop Scheduling
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 3 - Volume 3
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Evolutionary Algorithm and Its Application in Artificial Immune System
IITA '08 Proceedings of the 2008 Second International Symposium on Intelligent Information Technology Application - Volume 03
A novel quantum swarm evolutionary algorithm for solving 0-1 knapsack problem
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Iterative CDMA Multiuser Receiver With Soft Decision-Directed Channel Estimation
IEEE Transactions on Signal Processing
Generalized Parallel Interference Cancellation With Near-Optimal Detection Performance
IEEE Transactions on Signal Processing
Efficient statistical parallel interference cancellation for DS-CDMA in Rayleigh fading channels
IEEE Transactions on Wireless Communications
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Genetically modified multiuser detection for code division multiple access systems
IEEE Journal on Selected Areas in Communications
Key management scheme with bionic optimization
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Proxy signature scheme based on bionic evolution
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Bionic evolution based electronic cash scheme
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
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Bionic evolution mimicks the unique properties of biological evolution and proves to be an effective way to solve optimizing problem. As comparison and connection with natural evolution and biological inheritance, we analyzed the principles of bionic evolution and its superiorities for application in IDS (intrusion detection system). To solve the security problems and system flaws in intrusion detection system, we put forward an optimizing algorithm based on bionic evolution algorithm for parameter selection in IDS. With the bionic evolution based parameter optimizing algorithm, we put forward an intrusion analyzing scheme for IDS; the scheme is composed of anomaly-based detection and misuse-based detection. By applying bionic evolution algorithm, the scheme improves the accuracy and efficiency in selecting detection parameters and reinforces the adaptability, stability and robustness in intrusion analyzing and reacting. Therefore the scheme achieves considerable improvement on system security and efficiency regarding software and hardware environment.