This research introduces a proposed hybrid Spam Filtering System (SFS) which consists of Ant Colony System (ACS), information gain (IG) and Naïve Bayesian (NB). The aim of the proposed hybrid spam filtering is to classify the e-mails with high accuracy. The hybrid spam filtering consists of three consequence stages. In the first stage, the information gain (IG) for each attributes (i.e. weight for each feature) is computed. Then, the Ant Colony System algorithm selects the best features that the most intrinsic correlated attributes in classification. Finally, the third stage is dedicated to classify the e-mail using Naïve Bayesian (NB) algorithm. The experiment is conducted on spambase dataset. The result shows that the accuracy of NB with IG-ACS is better than NB with IG only.
Classification of network traffic is an important topic for network management, traffic routing, safe traffic discrimination, and better service delivery. Traffic examination is the entire process of examining traffic data, from intercepting traffic data to discovering patterns, relationships, misconfigurations, and anomalies in a network. Between them, traffic classification is a sub-domain of this field, the purpose of which is to classify network traffic into predefined classes such as usual or abnormal traffic and application type. Most Internet applications encrypt data during traffic, and classifying encrypted data during traffic is not possible with traditional methods. Statistical and intelligence methods can find and model traff
... Show MoreThe past years have seen a rapid development in the area of image compression techniques, mainly due to the need of fast and efficient techniques for storage and transmission of data among individuals. Compression is the process of representing the data in a compact form rather than in its original or incompact form. In this paper, integer implementation of Arithmetic Coding (AC) and Discreet Cosine Transform (DCT) were applied to colored images. The DCT was applied using the YCbCr color model. The transformed image was then quantized with the standard quantization tables for luminance and chrominance. The quantized coefficients were scanned by zigzag scan and the output was encoded using AC. The results showed a decent compression ratio
... Show MoreDetermining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
... Show MoreSkull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor
... Show MoreIntrusion-detection systems (IDSs) aim at detecting attacks against computer systems and networks or, in general, against information systems. Most of the diseases in human body are discovered through Deoxyribonucleic Acid (DNA) investigations. In this paper, the DNA sequence is utilized for intrusion detection by proposing an approach to detect attacks in network. The proposed approach is a misuse intrusion detection that consists of three stages. First, a DNA sequence for a network traffic taken from Knowledge Discovery and Data mining (KDD Cup 99) is generated. Then, Teiresias algorithm, which is used to detect sequences in human DNA and assist researchers in decoding the human genome, is used to discover the Shortest Tandem Repeat (S
... Show MoreIn the last decade, 3D models gained interest in many applications, such as games, the medical field, and manufacture. It is necessary to protect these models from unauthorized copying, distribution, and editing. Digital watermarking is the best way to solve this problem. This paper introduces a robust watermarking method by embedding the watermark in the low-frequency domain, then selecting the coarsest level for embedding the watermark based on the strength factor. The invisibility of the watermark for the proposed algorithm is tested by using different measurements, such as HD and PSNR. The robustness was tested by using different types of attacks; the correlation coefficient was applied for the evaluati
... Show MoreThe investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o
... Show MoreThe lossy-FDNR based aclive fil ter has an important property among many design realizations. 'This includes a significant reduction in component count particularly in the number of OP-AMP which consumes power. However the· problem of this type is the large component spreads which affect the fdter performance.
In this paper Genetic Algorithm is applied to minimize the component spread (capacitance and resistance p,read). The minimization of these spreads allow the fil
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