Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermore, various uses in the real world, Data distributions in intrusion detection systems, for example, are non-stationary, which produce concept drift over time or non-stationary learning. The word "concept drift" is used to describe the process of changing one's mind about something in an online-supervised learning scenario, the connection between the input data and the target variable changes over time. We define adaptive learning, classify existing concept drift strategies, evaluate the most typical, distinct, and widely used approaches and algorithms, describe adaptive algorithm assessment methodology, and show a collection of examples, all of this is based on the assumption that you have a basic understanding of supervised learning. The survey examines the various aspects of concept drift in a comprehensive manner in order to think about the current fragmented "state-of-the-art". As a result, which intends to give scholars, industry analysts, and practitioners a comprehensive introduction to idea drift adaptability.
An Auto Crop method is used for detection and extraction signature, logo and stamp from the document image. This method improves the performance of security system based on signature, logo and stamp images as well as it is extracted images from the original document image and keeping the content information of cropped images. An Auto Crop method reduces the time cost associated with document contents recognition. This method consists of preprocessing, feature extraction and classification. The HSL color space is used to extract color features from cropped image. The k-Nearest Neighbors (KNN) classifier is used for classification.
Facial identification is one of the biometrical approaches implemented for identifying any facial image with the use of the basic properties of that face. In this paper we proposes a new improved approach for face detection based on coding eyes by using Open CV's Viola-Jones algorithm which removes the falsely detected faces depending on coding eyes. The Haar training module in Open CV is an implementation of the Viola-Jones framework, the training algorithm takes as input a training group of positive and negative images, and generates strong features in the format of an XML file which is capable of subsequently being utilized for detecting the wanted face and eyes in images, the integral image is used to speed up Haar-like features calc
... Show MoreAs a result of the increase in wireless applications, this led to a spectrum problem, which was often a significant restriction. However, a wide bandwidth (more than two-thirds of the available) remains wasted due to inappropriate usage. As a consequence, the quality of the service of the system was impacted. This problem was resolved by using cognitive radio that provides opportunistic sharing or utilization of the spectrum. This paper analyzes the performance of the cognitive radio spectrum sensing algorithm for the energy detector, which implemented by using a MATLAB Mfile version (2018b). The signal to noise ratio SNR vs. Pd probability of detection for OFDM and SNR vs. BER with CP cyclic prefix with energy dete
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Computer vision is an emerging area with a huge number of applications. Identification of the fingertip is one of the major parts of those areas. Augmented reality and virtual reality are the most recent technological advancements that use fingertip identification. The interaction between computers and humans can be performed easily by this technique. Virtual reality, robotics, smart gaming are the main application domains of these fingertip detection techniques. Gesture recognition is one of the most fascinating fields of fingertip detection. Gestures are the easiest and productive methods of communication with regard to collaboration with the computer. This analysis examines the different studies done in the field of
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The Non-Photorealistic Rendering (NPR) demands are increased with the development of electronic devices. This paper presents a new model for a cartooning system, as an essential category of the NPR. It is used the concept of vector quantization and Logarithmic Image Processing (LIP). An enhancement of Kekre Median Codebook Generation (KMCG) algorithm has been proposed and used by the system. Several metrics utilized to evaluate the time and quality of the system. The results showed that the proposed system reduced the time of cartoon production. Additionally, it enhanced the quality of several aspects like smoothing, color reduction, and brightness.
Hiding secret information in the image is a challenging and painstaking task in computer security and steganography system. Certainly, the absolute intricacy of attacks to security system makes it more attractive.in this research on steganography system involving information hiding,Huffman codding used to compress the secret code before embedding which provide high capacity and some security. Fibonacci decomposition used to represent the pixels in the cover image, which increase the robustness of the system. One byte used for mapping all the pixels properties. This makes the PSNR of the system higher due to random distribution of embedded bits. Finally, three kinds of evaluation are applied such as PSNR, chi-square attack, a
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The rapid development of automation industries and technologies has shown incredible prospects for transforming our homes into a smart home automation system, which are more secure than a simple home. This paper proposes a home application based on voice and text called the Automated Control and Monitoring System (ASCM). This application can be utilized by both normal and vision-impaired people by using with a mobile phone.
The application allows users to send voice commands through Google Assistant installed on Android to control the appliances. They can also have complete monitoring by logging onto the ThingSpeak dashboard, which displays a device status indicator and sends alert messages in the event of dang
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