A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results show that the proposed system has obtained good results and these results are equal to 86.36%, 49.69%, and 77.65% for detection rate, false alarm rate and accuracy respectively. These results are considered as a better result when it is compared with the other previous basic algorithms. It is possible to conclude that DNA sequence has potential for NIDS solution and it has potential improvement using a better encoding method.
This research aims to present a proposed model for disclosure and documentation when performing the audit according to the joint audit method by using the questions and principles of the collective intelligence system, which leads to improving and enhancing the efficiency of the joint audit, and thus enhancing the confidence of the parties concerned in the outputs of the audit process. As the research problem can be formulated through the following question: “Does the proposed model for disclosure of the role of the collective intelligence system contribute to improving joint auditing?”
The proposed model is designed for the disclosure of joint auditing and the role
... Show MoreCommunity detection is useful for better understanding the structure of complex networks. It aids in the extraction of the required information from such networks and has a vital role in different fields that range from healthcare to regional geography, economics, human interactions, and mobility. The method for detecting the structure of communities involves the partitioning of complex networks into groups of nodes, with extensive connections within community and sparse connections with other communities. In the literature, two main measures, namely the Modularity (Q) and Normalized Mutual Information (NMI) have been used for evaluating the validation and quality of the detected community structures. Although many optimization algo
... Show MoreIn data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.
Continuous turbidimetric analysis (CTA) for a distinctive analytical application by employing a homemade analyser (NAG Dual & Solo 0-180°) which contained two consecutive detection zones (measuring cells 1 & 2) is described. The analyser works based on light-emitting diodes as a light source and a set of solar cells as a light detector for turbidity measurements without needing further fibres or lenses. Formation of a turbid precipitated product with yellow colour due to the reaction between the warfarin and the precipitation reagent (Potassium dichromate) is what the developed method is based on. The CTA method was applied to determine the warfarin in pure form and pharmaceu
In this paper we study the effect of the number of training samples for Artificial neural networks ( ANN ) which is necessary for training process of feed forward neural network .Also we design 5 Ann's and train 41 Ann's which illustrate how good the training samples that represent the actual function for Ann's.
DNA, as the basis of every living cell, is one of the most important and influential scientific discoveries. This research aims to identify and compare the organizational DNA to the leadership practices of school principals in the Sultanate of Oman and to reveal the similarity between principals’ leadership practices and the structure of DNA. In addition, it intends to identify any statistically significant differences between the responses of the participants due to the study variables: gender, job title and experience. A questionnaire was designed and data were collected from a randomly selected sample composed of (100) teachers in the Sultanate of Oman. The study found limitless diversity in the characteristics of DNA of leadership
... Show MoreThe article aims to consider the concept of language metaphor in Russian and Arabic languages and the problem of metaphor functioning in language, since it is one of the most important figurative components of the structural organization of the text and an important means of reflecting the national culture of each people. and often in revealing the image of a metaphor one can feel the full flexibility of the language and its beauty.
Obesity is an escalating health problem in developing countries. One to ten children worldwide are overweight in a report showed by the International Obesity Task Force. Ghrelin, orexigenic peptide, has 28 amino acids, it is considered the greatest remarkable promotion in the last two decades for understanding the physiological changes of action regulating food intake and hunger. Obestatin is a 23-amino acid peptide nearly connected to ghrelin that secures from substitutio
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