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Handbook of Applied Cryptography
Handbook of Applied Cryptography
Computer Networks and Internets with CD (Audio)
Computer Networks and Internets with CD (Audio)
Learning Fingerprints for a Database Intrusion Detection System
ESORICS '02 Proceedings of the 7th European Symposium on Research in Computer Security
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Cryptanalysis of a chaotic neural network based multimedia encryption scheme
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part III
Training a neural-network based intrusion detector to recognize novel attacks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Control and management in next-generation networks: challenges and opportunities
IEEE Communications Magazine
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We present a neural-network approach for computer network security. The approach uses a neural network to learn the decryption and public key creation. It is a new potential source for public key cryptographic schemes which are not based on number theoretic functions, and have small time and memory complexities. The proposed method follows the asymmetric model. While the encryption process and private key creation are based on Boolean algebra, the decryption process is based on a neural network technique. The application of this method shows that the possibility of guessing keys is extremely weaker than using the Data Encryption Standard method (DES), which is a widely-used method of data encryption.