Development of Committee Neural Network for Computer Access Security System
A computer access security system, a reliable way of preventing unauthorized people for accessing, changing or deleting, and stealing the information, needed to be developed and implemented. In the present study, a neural network based system is proposed for computer access security for the issues of preventive security and detection of violation. Two types of data, time intervals between successive keystrokes during password entry through keyboard and voice patterns spoken via a microphone, are considered to deal with a situation of multiple users where each user has a certain password with different length. For each type of data, several multi-layered neural networks are designed and evaluated in terms of recognition accuracy. A committee neural network is formed consisting of six multi-layered neural networks. The committee decision was based on majority voting of the member networks. The committee neural network performance was better than the neural networks trained separately.
KeywordsRecognition Accuracy Speaker Verification Multilayered Neural Network Authorized Person Security Code
Unable to display preview. Download preview PDF.
- 1.Anagun, A.S.: An Artificial Neural Network Approach for a Computer Access Security System Based on the Characteristics of the Users. Endüstri Mühendisliği 10, 3–11 (1999)Google Scholar
- 5.Obaidat, M.S., Macchairolo, D.T., Bleha, S.A.: An Intelligent Neural Network System for Identifying Computer Users. In: Dagli, et al. (eds.) ASME Intelligent Engineering Systems through Artificial Neural Networks, vol. 1, pp. 953–959 (1991)Google Scholar
- 8.Anagun, A.S., Cin, I.: An Alternative Way for Computer Access Security: Password Entry Patterns. In: Proceedings of the 18th National Conference on Operations Research and Industrial Engineering, Istanbul, Turkey, pp. 17–20 (1996)Google Scholar
- 11.Markel, J.D., Gray Jr., A.H.: Linear Prediction of Speech. Springer, New York (1982)Google Scholar
- 12.Deller Jr., J.R., Proakis, J.G., Hansen, J.H.L.: Discrete-Time Processing of Speech Signals. Macmillian Publishing Co., New York (1993)Google Scholar
- 13.Rabiner, L.R., Schafer, R.W.: Digital Processing of Speech Signals. Prentice-Hall, Englewood Cliffs (1978)Google Scholar
- 15.Huang, W., Lippmann, R.: Comparisons between Neural Networks and Conventional Classifiers. In: Proceedings of the 1st International Conference on Neural Networks, pp. 485–494 (1987)Google Scholar
- 18.Soucek, B.: Neural and Concurrent Real-Time Systems - The Sixth Generation. John Wiley-Sons, New York (1989)Google Scholar
- 19.Anagun, A.S.: A Multilayered Neural Network Based Computer Access Security System: Effects of Training Algorithms. Lecture Series on Computer and Computational Sciences 4B, 1604–1607 (2005)Google Scholar
- 20.Klimasauskas, C.C.: Applying Neural Networks, Part III: Training a Neural Network. PC AI, 20–24 (1991)Google Scholar