Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system. A new features selection method is proposed based on DNA encoding and on DNA keys positions. The current system has three phases, the first phase, is called pre-processing phase, which is used to extract the keys and their positions, the second phase is training phase; the main goal of this phase is to select features based on the key positions that gained from pre-processing phase, and the third phase is the testing phase, which classified the network traffic records as either normal or attack by using specific features. The performance is calculated based on the detection rate, false alarm rate, accuracy, and also on the time that include both encoding time and matching time. All these results are based on using two or three keys, and it is evaluated by using two datasets, namely, KDD Cup 99, and NSL-KDD. The achieved detection rate, false alarm rate, accuracy, encoding time, and matching time for all corrected KDD Cup records (311,029 records) by using two and three keys are equal to 96.97, 33.67, 91%, 325, 13 s, and 92.74, 7.41, 92.71%, 325 and 20 s, respectively. The results for detection rate, false alarm rate, accuracy, encoding time, and matching time for all NSL-KDD records (22,544 records) by using two and three keys are equal to 89.34, 28.94, 81.46%, 20, 1 s and 82.93, 11.40, 85.37%, 20 and 1 s, respectively. The proposed system is evaluated and compared with previous systems and these comparisons are done based on encoding time and matching time. The outcomes showed that the detection results of the present system are faster than the previous ones.
In this paper, we introduce three robust fuzzy estimators of a location parameter based on Buckley’s approach, in the presence of outliers. These estimates were compared using the variance of fuzzy numbers criterion, all these estimates were best of Buckley’s estimate. of these, the fuzzy median was the best in the case of small and medium sample size, and in large sample size, the fuzzy trimmed mean was the best.
Doses for most drugs are determined from population-level information, resulting in a standard ?one-size-fits-all’ dose range for all individuals. This review explores how doses can be personalised through the use of the individuals’ pharmacokinetic (PK)-pharmacodynamic (PD) profile, its particular application in children, and therapy areas where such approaches have made inroads.
The Bayesian forecasting approach, based on population PK/PD models that account for variability in exposure and response, is a potent method for personalising drug therapy. Its potential utility is eve
in this paper the notion of threshold relations by using resemblance relation are introduced to get a similarity relation from a resemnblance relation R
In this paper, certain types of regularity of topological spaces have been highlighted, which fall within the study of generalizations of separation axioms. One of the important axioms of separation is what is called regularity, and the spaces that have this property are not few, and the most important of these spaces are Euclidean spaces. Therefore, limiting this important concept to topology is within a narrow framework, which necessitates the use of generalized open sets to obtain more good characteristics and preserve the properties achieved in general topology. Perhaps the reader will realize through the research that our generalization preserved most of the characteristics, the most important of which is the hereditary property. Two t
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In this paper we introduce the basic of definitions of groups for geometric figures; we describe some of geometric figures by using the properties of groups. The classification of some geometric figures by using the properties of some algebraic structures.
The concept of epiform modules is a dual of the notion of monoform modules. In this work we give some properties of this class of modules. Also, we give conditions under which every hollow (copolyform) module is epiform.