Communication system information resource security breach model

Introduction: Models and methods for diagnosing computer incidents recorded in information and communication systems are the most important components in mathematical support of information security systems. The main requirement for the diagnostics is prompt identification of security violation characteristics. This problem is complicated due to the amount and variability of the initial data on information security violation. Purpose: Development of a model for diagnosing a computer incident, along with a method which would allow you to quickly determine the characteristics of a security violation. Results: Security breach characteristics important for making a decision about responding to an identified computer incident can be determined via deep artificial neural networks. A structural feature of the proposed deep artificial neural network is combining the coding part of the autoencoder and a multilayer perceptron. In addition, the method implements a parallel mode of processing information events which have occurred in the information and communication system before the incident was detected, by using a separate proposed artificial neural network for each secondary characteristic of the security breach. The method of determining the values of these secondary characteristics allows you to greatly improve the diagnostics efficiency, having acceptable values of precision and recall for the security violation characteristics to determine. The dependence has been studied of the completeness and classification accuracy on the number of neurons in the hidden layer. A sufficient number of neurons in the hidden layer for achieving the required training efficiency is experimentally determined. Practical relevance: The developed model and method can be implemented using standard software and hardware (servers) of an information and communication system. Their combined use with the existing models and methods of monitoring and diagnostics can significantly improve the efficiency of an information security system.

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AAC Decision-Making and Mobile Technology: Points to Ponder

Perspectives on Augmentative and Alternative Communication ◽

10.1044/aac23.2.104 ◽

2014 ◽

Vol 23 (2) ◽

pp. 104-111 ◽

Cited By ~ 6

Author(s):

Mary Ann Abbott ◽

Debby McBride

Keyword(s):

Decision Making ◽

Mobile Technology ◽

Communication System ◽

Augmentative And Alternative Communication ◽

Evaluation Process ◽

Decision Making Process ◽

Alternative Communication ◽

Ipod Touch ◽

Feature Match

The purpose of this article is to outline a decision-making process and highlight which portions of the augmentative and alternative communication (AAC) evaluation process deserve special attention when deciding which features are required for a communication system in order to provide optimal benefit for the user. The clinician then will be able to use a feature-match approach as part of the decision-making process to determine whether mobile technology or a dedicated device is the best choice for communication. The term mobile technology will be used to describe off-the-shelf, commercially available, tablet-style devices like an iPhone®, iPod Touch®, iPad®, and Android® or Windows® tablet.

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A Community Based High Risk Register for Hearing Loss

Journal of Speech and Hearing Disorders ◽

10.1044/jshd.4704.373 ◽

1982 ◽

Vol 47 (4) ◽

pp. 373-375 ◽

Cited By ~ 2

Author(s):

James L. Fitch ◽

Thomas F. Williams ◽

Josephine E. Etienne

Keyword(s):

Hearing Loss ◽

System Identification ◽

High Risk ◽

Language Learning ◽

Education Program ◽

Communication System ◽

Auditory Signal ◽

Early Age ◽

Community Based ◽

Children With Hearing Loss

The critical need to identify children with hearing loss and provide treatment at the earliest possible age has become increasingly apparent in recent years (Northern & Downs, 1978). Reduction of the auditory signal during the critical language-learning period can severely limit the child's potential for developing a complete, effective communication system. Identification and treatment of children having handicapping conditions at an early age has gained impetus through the Handicapped Children's Early Education Program (HCEEP) projects funded by the Bureau of Education for the Handicapped (BEH).

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