What is Hash based Message Authentication Code (HMAC) in Network Security
Technology & Science / February 21, 2018

Today the Internet has virtually become the way of doing business as it offers a powerful ubiquitous medium of commerce and enables greater connectivity of disparate groups throughout the world. However this medium has its inherent risks. Loss of privacy, loss of data integrity, identify spoofing and denial of service are some of the major threats in the Internet. Two parties communicating across an insecure channel need a method by which any attempt to modify the information sent by one to the other, or fake its origin, is detected. Most commonly such a mechanism is based on a shared key between the parties, and in this setting is usually called a MAC, or Message Authentication Code. Overview of Hash based Message Authentication Code Providing a way to check the integrity of information transmitted over or stored in an unreliable medium is a prime necessity in the world of open computing and communications. Mechanisms that provide such integrity checks based on a secret key are usually called message authentication codes (MACs). Typically, message authentication codes are used between two parties that share a secret key in order to authenticate information transmitted between these parties. This standard defines a MAC that uses…

What is Recurrent Neural Network (RNN)
/ February 20, 2018

Neural networks are powerful learning models that achieve state-of-the-art results in a wide range of supervised and unsupervised machine learning tasks. They are suited especially well for machine perception tasks, where the raw underlying features are not individually interpretable. The use of recurrent neural networks are often related to deep learning and the use of sequences to evolve models that simulate the neural activity in the human brain. Overview of Recurrent Neural Network (RNN) The fundamental feature of a Recurrent Neural Network (RNN) is that the network contains at least one feed-back connection, so the activations can flow round in a loop. That enables the networks to do temporal processing and learn sequences, e.g., perform sequence recognition/reproduction or temporal association/prediction. Recurrent Neural Networks (RNNs) are connectionist models with the ability to selectively pass information across sequence steps, while processing sequential data one element at a time. Thus they can model input and/or output consisting of sequences of elements that are not independent. Further, recurrent neural networks can simultaneously model sequential and time dependencies on multiple scales. Figure 1: Recurrent Neural Network In other words, the RNN will be a function with inputs​$$x_t$$​  (input vector) and previous state ​$$h_(t-1)… What is Texture Analysis in Image Processing / February 18, 2018 In many machine vision and image processing algorithms, simplifying assumptions are made about the uniformity of intensities in local image regions. However, images of real objects often do not exhibit regions of uniform intensities. Extraction of effective features of objects is an important area of research in the intelligent processing of image data. Texture analysis is one of the fundamental aspects of human vision by which we discriminate between surfaces and objects. In a similar manner, computer vision can take advantage of the cues provided by surface texture to distinguish and recognize objects. In computer vision, texture analysis may be used alone or in combination with other sensed features (e.g. color, shape, or motion) to perform the task of recognition. Overview of Texture Analysis Texture analysis refers to the characterization of regions in an image by their texture content. Texture analysis attempts to quantify intuitive qualities described by terms such as rough, smooth, silky, or bumpy as a function of the spatial variation in pixel intensities. In this sense, the roughness or bumpiness refers to variations in the intensity values, or gray levels. Texture analysis is used in various applications, including remote sensing, automated inspection, and medical image processing. Texture analysis… What is Bit Plane Slicing in Image processing Image Processing / February 17, 2018 Bit plane slicing is well known technique used in Image processing. In image compression Bit plane slicing is used. Bit plane slicing is the conversion of image into multilevel binary image. These binary images are then compressed using different algorithm. With this technique, the valid bits from gray scale images can be separated, and it will be useful for processing these data in very less time complexity. Digitally, an image is represented in terms of pixels. These pixels can be expressed further in terms of bits. Separating a digital image into its bit-planes is useful for analyzing the relative importance played by each bit of image, a process aids in determining the adequacy of the no. of bits used to quantize each pixel. This type of decomposition is useful for image compression. This term of bit-plane extraction for an 8 bit image, it is not difficult to show that the (binary) image for bit-plane 7 can be obtained by processing input image with a thresholding gray-level transformation function. Overview of Bit Plane Slicing Instead of highlighting gray level images, highlighting the contribution made to total image appearance by specific bits might be desired. Suppose that each pixel in an image is… What is Plagiarism Detection / February 15, 2018 Plagiarism is the reuse of someone else’s prior ideas, processes, results, or words without explicitly acknowledging the original author and source. In modern years, plagiarism has raised great concern over knowledgeable property protection. Plagiarists violate knowledgeable property rights either by copying source/binary code or by stealing and covertly implementing protected algorithms. The first case is also known as software plagiarism. Plagiarism involves reproducing the existing information in modified format or sometimes the original document as it is. This is quiet common among students, researchers and academicians. This has made some strong influence on research community and awareness among academic peoples to prevent such a kind of misuse. in this presented article Plagiarism Detection is explained. Overview of Plagiarism Detection A word may have several possible meanings and senses due to the richness of natural languages, which make detecting plagiarism a hard task especially when dealing with semantic meaning, not just searching for patterns of text that are illegally copied from others (copy and paste texts from digital resources without acknowledging the original resource), Plagiarism occurs in various forms: submitting another’s work exactly same without proper citation, paraphrasing text, reordering the sentences, using synonyms, or changing grammar, code plagiarism etc. Plagiarism is… What is Automatic Number Plate Recognition (ANPR) Technology & Science / February 13, 2018 With growing urban population and its supporting transport services, there is an urgent need to improve traffic management and secure the transport systems. Automation in transport has been used successfully in signaling systems and has helped in managing urban traffic to a great extent. Automatic recognition of vehicle license plate number became a very important in our daily life because of the unlimited increase of cars and transportation systems which make it impossible to be fully managed and monitored by humans, examples are so many like traffic monitoring, tracking stolen vehicle, managing parking toll, red-light violation enforcement, border and customs checkpoints. Automatic Number Plate Recognition: Overview Automatic Number Plate Recognition (ANPR) system is an important technique, used in Intelligent Transportation System. ANPR is an advanced machine vision technology used to identify vehicles by their number plates without direct human intervention. The development of Intelligent Transportation System provides the data of vehicle numbers which can be used in follow up, analyses and monitoring. ANPR is important in the area of traffic problems, highway toll collection, borders and custom security, premises where high security is needed. The complexity of automatic number plate recognition work varies throughout the world. For the standard number… What is Cognitive Computing Technology & Science / February 11, 2018 Much of the excitement about cognitive computing is spurred by its enormous potential in learning, only a small fraction of which has so far been realized. The overarching goal here is to devise computational frameworks to help us learn better by exploiting data about our learning processes and activities. There are two important aspects of it—the mechanisms or insights about how we actually learn and the external manifestations of our learning activities. Cognitive computing is an emerging approach that builds upon a wealth of research and development work in Artificial Intelligence (AI). What is Cognitive Computing? Cognitive computing is the simulation of human thought processes in a computerized model. Cognitive computing involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works. The goal of cognitive computing is to create automated IT systems that are capable of solving problems without requiring human assistance. The origins of cognitive systems work lie in cognitive science — a discipline that brings together researchers from the fields of psychology, linguistics, philosophy, computer science, and more recently, neuro-computing. We perceive “cognitive computing” as an approach that has emerged from, and attempts to subsume, the work… What is Image Compression in Image Processing / February 10, 2018 A marked progress has been made in the field of image compression and its application in various branches of engineering. Image compression is associated with removing redundant information of image data. It is a solution which associated with storage and data transmission problem of huge amounts of data for digital image. Compressing an image is significantly different than compressing raw binary data. Of course, general purpose compression programs can be used to compress images, but the result is less than optimal. This is because images have certain statistical properties which can be exploited by encoders specifically designed for them. Also, some of the finer details in the image can be sacrificed for the sake of saving a little more bandwidth or storage space. Overview of Image Compression Image compression is an application of data compression that encodes the original image with few bits. The objective of image compression is to reduce the redundancy of the image and to store or transmit data in an efficient form. Image compression is a type of an application for data/image compression in which the basic image gets encoded with the limited bits. To lower the irrelevance and the redundancy of image data is the… What is Visual Analytics / February 9, 2018 We are living in a world which faces a rapidly increasing amount of data to be dealt with on a daily basis. In the last decade, the steady improvement of data storage devices and means to create and collect data along the way influenced our way of dealing with information: Most of the time, data is stored without filtering and refinement for later use. Virtually every branch of industry or business, and any political or personal activity nowadays generate vast amounts of data. Making matters worse, the possibilities to collect and store data increase at a faster rate than our ability to use it for making decisions. However, in most applications, raw data has no value in itself; instead we want to extract the information contained in it. Overview Generally, large scale organizations have large amount of data and information to process. They need some strong procedures and techniques to collect, analyze, process and visualize the data in order to get required results as well as to take the right decision in order to get their long term goals and objectives. Several software and tools relating to big data analytics, visual analytics are being used by companies in order to… What is Content Delivery Network (CDN) / February 8, 2018 With the proliferation of the Internet, popular Web services often suffer congestion and bottlenecks due to large demands made on their services. Such a scenario may cause unmanageable levels of traffic flow, resulting in many requests being lost. Replicating the same content or services over several mirrored Web servers strategically placed at various locations is a method commonly used by service providers to improve performance and scalability. The user is redirected to the nearest server and this approach helps to reduce network impact on the response time of the user requests. What is it? Content Delivery Networks (CDNs) provide services that improve network performance by maximizing bandwidth, improving accessibility and maintaining correctness through content replication. They offer fast and reliable applications and services by distributing content to cache or edge servers located close to users. CDNs have evolved to overcome the inherent limitations of the Internet in terms of user perceived Quality of Service (QoS) when accessing Web content. They provide services that improve network performance by maximizing bandwidth, improving accessibility, and maintaining correctness through content replication. The typical functionalities of a CDN include: Request redirection and content delivery services, to direct a request to the closest suitable CDN cache… Insert math as Additional settings Formula color Type math using LaTeX Preview \({}$$
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