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.
Abstract:
Typological analysis about the negation marker in different languages is one of the fields of research that has attracted much attention. In Persian language, this constituent has been analysed from different aspects. This study aimed to analyse different aspects of negation marker in the adjectives, the noun phrases and the verb phrases based on typological analysis. Many studies have been revealed that the negation in adjectives has shown lexically and morphologically. In the noun phrases, /hich/ has used as a negative marker necessarily marking the verb phrase as negative too. In the verb phrases, negation occurs morphologically by the addition of the prefix /n
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Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time. In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D
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: Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision maker to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick–Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and Fourier mod
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Image Fusion Using A Convolutional Neural Network
Peer-Reviewed Journal
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Recently, a new secure steganography algorithm has been proposed, namely, the secure Block Permutation Image Steganography (BPIS) algorithm. The new algorithm consists of five main steps, these are: convert the secret message to a binary sequence, divide the binary sequence into blocks, permute each block using a key-based randomly generated permutation, concatenate the permuted blocks forming a permuted binary sequence, and then utilize a plane-based Least-Significant-Bit (LSB) approach to embed the permuted binary sequence into BMP image file format. The performance of algorithm was given a preliminary evaluation through estimating the PSNR (Peak Signal-to-Noise Ratio) of the stego image for limited number of experiments comprised hiding
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Wireless networks and communications have witnessed tremendous development and growth in recent periods and up until now, as there is a group of diverse networks such as the well-known wireless communication networks and others that are not linked to an infrastructure such as telephone networks, sensors and wireless networks, especially in important applications that work to send and receive important data and information in relatively unsafe environments, cybersecurity technologies pose an important challenge in protecting unsafe networks in terms of their impact on reducing crime. Detecting hacking in electronic networks and penetration testing. Therefore, these environments must be monitored and protected from hacking and malicio
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