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Open AccessJournal ArticleDOI

A Backpropagation Neural Network for Computer Network Security

Khalil Shihab
- 30 Sep 2006 - 
- Vol. 2, Iss: 9, pp 710-715
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TLDR
This paper along with test results show 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.
Abstract
In this paper, an efficient and scalable technique for computer network security is presented. On one hand, the decryption scheme and the public key creation used in this work are based on a multi-layer neural network that is trained by backpropagation learning algorithm. On the other hand, the encryption scheme and the private key creation process are based on Boolean algebra. This 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. This paper along with test results show 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. The presented results are obtained through the use of MATLAB 6.5.1 software.

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Citations
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Retrieval of spinach crop parameters by microwave remote sensing with back propagation artificial neural networks: A comparison of different transfer functions

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Comparative analyses on medium optimization using one-factor-at-a-time, response surface methodology, and artificial neural network for lysine–methionine biosynthesis by Pediococcus pentosaceus RF-1

TL;DR: In this paper, an optimization strategy that encompassed one factor at a time (OFAT), response surface methodology (RSM), and artificial neural network method was implemented during medium formulation with specific

Automated Epileptic Seizure Detection in EEG Signals Using FastICA and Neural Network

TL;DR: A novel and efficient approach for automatically detecting the presence of epileptic seizures in EEG signals by using Fast Independent Component Analysis (FastICA), a Statistical Signal Processing Technique, and the BackPropagation Neural Network is proposed.
References
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Book

Artificial Intelligence: A Modern Approach

TL;DR: In this article, the authors present a comprehensive introduction to the theory and practice of artificial intelligence for modern applications, including game playing, planning and acting, and reinforcement learning with neural networks.
Book

Handbook of Applied Cryptography

TL;DR: A valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography, this book provides easy and rapid access of information and includes more than 200 algorithms and protocols.
Book

Self-Organizing Maps

TL;DR: The Self-Organising Map (SOM) algorithm was introduced by the author in 1981 as mentioned in this paper, and many applications form one of the major approaches to the contemporary artificial neural networks field, and new technologies have already been based on it.
Book ChapterDOI

Anomalous Payload-Based Network Intrusion Detection

TL;DR: A payload-based anomaly detector, called PAYL, for intrusion detection that demonstrates the surprising effectiveness of the method on the 1999 DARPA IDS dataset and a live dataset the authors collected on the Columbia CS department network.

Intrusion detection with unlabeled data using clustering

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