In this paper, a method for hiding cipher text in an image file is introduced . The
proposed method is to hide the cipher text message in the frequency domain of the image.
This method contained two phases: the first is embedding phase and the second is extraction
phase. In the embedding phase the image is transformed from time domain to frequency
domain using discrete wavelet decomposition technique (Haar). The text message encrypted
using RSA algorithm; then Least Significant Bit (LSB) algorithm used to hide secret message
in high frequency. The proposed method is tested in different images and showed success in
hiding information according to the Peak Signal to Noise Ratio (PSNR) measure of the the
original image .
This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s
In recent years, with the growing size and the importance of computer networks, it is very necessary to provide adequate protection for users data from snooping through the use of one of the protection techniques: encryption, firewall and intrusion detection systems etc. Intrusion detection systems is considered one of the most important components in the computer networks that deal with Network security problems. In this research, we suggested the intrusion detection and classification system through merging Fuzzy logic and Artificial Bee Colony Algorithm. Fuzzy logic has been used to build a classifier which has the ability to distinguish between the behavior of the normal user and behavior of the intruder. The artificial bee colony al
... Show MoreUntil recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15
... Show MoreSemantic segmentation is effective in numerous object classification tasks such as autonomous vehicles and scene understanding. With the advent in the deep learning domain, lots of efforts are seen in applying deep learning algorithms for semantic segmentation. Most of the algorithms gain the required accuracy while compromising on their storage and computational requirements. The work showcases the implementation of Convolutional Neural Network (CNN) using Discrete Cosine Transform (DCT), where DCT exhibit exceptional energy compaction properties. The proposed Adaptive Weight Wiener Filter (AWWF) rearranges the DCT coefficients by truncating the high frequency coefficients. AWWF-DCT model reinstate the convolutional l
... Show MoreMinimizing the power consumption of electronic systems is one of the most critical concerns in the design of integrated circuits for very large-scale integration (VLSI). Despite the reality that VLSI design is known for its compact size, low power, low price, excellent dependability, and high functionality, the design stage remains difficult to improve in terms of time and power. Several optimization algorithms have been designed to tackle the present issues in VLSI design. This study discusses a bi-objective optimization technique for circuit partitioning based on a genetic algorithm. The motivation for the proposed research is derived from the basic concept that, if some portions of a circuit's system are deactivated during th
... Show MoreRecently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results
... Show MoreA new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever
... Show MoreFaces blurring is one of the important complex processes that is considered one of the advanced computer vision fields. The face blurring processes generally have two main steps to be done. The first step has detected the faces that appear in the frames while the second step is tracking the detected faces which based on the information extracted during the detection step. In the proposed method, an image is captured by the camera in real time, then the Viola Jones algorithm used for the purpose of detecting multiple faces in the captured image and for the purpose of reducing the time consumed to handle the entire captured image, the image background is removed and only the motion areas are processe
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