Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the disadvantages of these two methods. In this paper, a new hybrid IDS is proposed based on the RNA encoding idea and applying the K-means clustering algorithm. Firstly, choosing random records for both training and testing. Secondly, propose RNA encoding by calculating all possible record values within dataset and generating RNA characters for each value, then dividing it into blocks. The third step is done by searching and extracting normal keys based on the most repeated blocks, and the same procedure is applied to extract the attack keys. Finally, the Kmeans clustering method is used to classify the testing records based on extracted keys. The proposed method is evaluated by calculating the detection rate (DR), false alarm rate (FAR), and accuracy, where the achieved DR, FAR, and accuracy are equal to 91.13%, 0.46%, and 92.02% respectively. Based on the achieved results, it can be said that the proposed hybrid IDS has high DR and accuracy results, can detect new attacks, and can solve the problem of anomaly IDS by getting a low false alarm rate result.
This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta
... Show More
(2)
(1)
The aim of advancements in technologies is to increase scientific development and get the overall human satisfaction and comfortability. One of the active research area in recent years that addresses the above mentioned issues, is the integration of radio frequency identification (RFID) technology into network-based systems. Even though, RFID is considered as a promising technology, it has some bleeding points. This paper identifies seven intertwined deficiencies, namely: remote setting, scalability, power saving, remote and concurrent tracking, reusability, automation, and continuity in work. This paper proposes the construction of a general purpose infrastructure for RFID-based applications (IRFID) to tackle these deficiencies. Finally
... Show More
(1)
This paper explores a fuzzy-logic based speed controller of an interior permanent magnet synchronous motor (IPMSM) drive based on vector control. PI controllers were mostly used in a speed control loop based field oriented control of an IPMSM. The fundamentals of fuzzy logic algorithms as related to drive control applications are illustrated. A complete comparison between two tuning algorithms of the classical PI controller and the fuzzy PI controller is explained. A simplified fuzzy logic controller (FLC) for the IPMSM drive has been found to maintain high performance standards with a much simpler and less computation implementation. The Matlab simulink results have been given for different mechanical operating conditions. The simulated
... Show More
(22)
(16)
Recently, wireless charging based RF harvesting has interfered our lives [1] significantly through the different applications including biomedical, military, IoT, RF energy harvesting, IT-care, and RFID technologies. Wirelessly powered low energy devices become significantly essential for a wide spectrum of sensing applications [1]. Such devices require for low energy resources from sunlight, mechanical vibration, thermal gradients, convection flows or other forms of harvestable energy [2]. One of the emerging power extraction resources based on passive devices is harvesting radio frequency (RF) signals powers [3]–[5]. Such applications need devices that can be organized in very large numbers, so, making separate node battery impractical.
... Show More
(14)
(9)
The problem of frequency estimation of a single sinusoid observed in colored noise is addressed. Our estimator is based on the operation of the sinusoidal digital phase-locked loop (SDPLL) which carries the frequency information in its phase error after the noisy sinusoid has been acquired by the SDPLL. We show by computer simulations that this frequency estimator beats the Cramer-Rao bound (CRB) on the frequency error variance for moderate and high SNRs when the colored noise has a general low-pass filtered (LPF) characteristic, thereby outperforming, in terms of frequency error variance, several existing techniques some of which are, in addition, computationally demanding. Moreover, the present approach generalizes on existing work tha
... Show More
The research aims to know the impact of science, technology, engineering, and mathematics education on both creative thinking and mathematical achievement. To achieve it, the two researchers followed the quasi-experimental approach with an experimental design for two groups, one experimental and the other a control. The research sample consisted of (32) female students from the fourth scientific grade in Al-Intisar Preparatory School for Girls/ AlRasafa, First Directorate. The sample was chosen intentionally and was divided into two groups: a control group studying by the traditional method, their number (16), and an experimental group that applied the STEM approach, their number also (16). There was parity between the two research groups i
... Show More
(66)
(22)