An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

This paper proposes a novel hidden Markov model (HMM)-based gesture recognition method and applies it to an HCI to control a computer game. The novelty of the proposed method is two-fold: 1) the proposed method uses a continuous streaming of human motion as the input to the HMM instead of isolated data sequences or pre-segmented sequences of data and 2) the gesture segmentation and recognition are performed simultaneously. The proposed method consists of a single HMM composed of thirteen gesture-specific HMMs that independently recognize certain gestures. It takes a continuous stream of pose symbols as an input, where a pose is composed of coordinates that indicate the face, left hand, and right hand. Whenever a new input Pose arrives, the HMM continuously updates its state probabilities, then recognizes a gesture if the probability of a distinctive state exceeds a predefined threshold. To assess the validity of the proposed method, it was applied to a real game, Quake II, and the results demonstrated that the proposed HMM could provide very useful information to enhance the discrimination between different classes and reduce the computational cost.

Hidden Markov Model for Gesture Recognition

Understanding acceptance of eHealthcare by IoT natives and IoT immigrants: An integrated model of UTAUT, perceived risk, and financial cost

There is no suspicion that IoT has added a new dimension to the living being by the link between smart objects. Thus making the link among any media and anything at any place and anytime was appreciable. Under the umbrella of the Internet of Things (IoT) the number of interconnected devices is expected to grow exponentially toward more than 34 billion devices until 2021. IoT will propose the unique identification of the objects and their virtual representation as the basis for autonomously development of applications and services. These will be characterized by enormous and self-governing data capture, incident transfer, network connectivity and interoperability. This technology has a lot of applications in heterogeneous fields. The IoT technology and applications are likely to be major drivers of investment and innovation in the communications sector, over the forthcoming years, delivering the valued advantage to citizens, client and industrial end-users. These will lead to the introduction of many new and modern services. It will permit data to be transmitted between many various types of devices, enhance the safety of transportation, and decrease the consumption of energy and enhance our health. In this paper, we are briefly discussing about the Internet of Things and applications in several fields. The IoT applications are using at the edge of the network sensors accumulate data on a computing and communicating device and actuators to perform distinguished tasks controlled by these devices.

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The Internet of Things (IoT) and its Application Domains

Internet-of-Things (IoT) technology is increasingly prominent in the current stage of social development. All walks of life have begun to implement the IoT integration technology, so as to strive to promote industrial modernization, intelligence, and digitalization. In this case, how to link high-risk network activities with entities has become the primary issue for promoting industrial development. However, at this stage, the security issues in the development of the IoT technology have contradictions that are difficult to resolve. According to this situation, how to make system defense intelligent and replace manual monitoring has become the future of the development of security architecture. This article combines existing security research to explore the possibility of deep learning (DL) in upgrading the IoT security architecture, discusses how the IoT can identify and respond to cyber attacks, and how to encrypt edge data transmission. Moreover, this article discusses security research in application fields, such as Industrial IoT, Internet of Vehicles, smart grid, smart home, and smart medical. Then, we summarized the areas that can be improved in future technological development, including sharing computing power through the edge network processing unit (NPU) central device and closely combining the environmental simulation model with the actual environment, as well as malicious code detection, intrusion detection, production safety, vulnerability detection, fault diagnosis, and blockchain technology. 

Deep Learning in Security of Internet of Things

The Internet as a whole does not use secure links, thus information in transit may be vulnerable to interruption as well. The important of reducing a chance of the information being detected during the transmission is being an issue in the real world now days. The Digital watermarking method provides for the quick and inexpensive distribution of digital information over the Internet. This method provides new ways of ensuring the sufficient protection of copyright holders in the intellectual property dispersion process. The property of digital watermarking images allows insertion of additional data in the image without altering the value of the image.In this paper investigate the following relevant concepts and terminology, history of watermarks and the properties of a watermarking system and applications. We are proposing edge detection using Gabor Filters. In this paper we are proposed least significant bit (LSB) substitution method to encrypt the message in the watermark image file. The benefits of the LSB are its simplicity to embed the bits of the message directly into the LSB plane of cover-image and many techniques using these methods. The LSB does not result in a human perceptible difference because the amplitude of the change is little therefore the human eye the resulting stego image will look identical to the cover image and this allows high perceptual transparency of the LSB. The spatial domain technique LSB substitution it would be able to use a pseudo-random number generator to determine the pixels to be used for embedding based on a given key. We are using DCT transform watermark algorithms based on robustness. The watermarking robustness have been calculated by the Peak Signal to Noise Ratio (PSNR) and Normalized cross correlation (NC) is used to quantify by the similarity between the real watermark and after extracting watermark.

An Adaptive Watermarking Technique for the copyright of digital images and Digital Image Protection

Recent years have seen the swift development and deployment of Internet-of-Things (IoT) applications in a variety of application domains. In this scenario, people worldwide are now ready to delight the benefits of the Internet of Things (IoT). The IoT is emerging as the third wave in the evolution of the Internet. The 1990s’ Internet wave connected 1.2 billion subscribers while the 2000s’ mobile wave connected another 2.4 billion. Actually, IoT is expected to consist of more than 84 billion connected devices generating 186 zettabyte of data by 2025, in the opinion of IDC. It includes major types of networks, such as distributed, ubiquitous, grid, and vehicular, these have conquered the world of information technology over a decade. IoT is growing fast across several industry verticals along with increases in the number of interconnected devices and diversify of IoT applications. In spite of the fact that, IoT technologies are not reaching maturity yet and there are many challenges to overcome. The Internet of Things combines actual and virtual anywhere and anytime, fascinate the attention of both constructor and hacker. Necessarily, leaving the devices without human interference for a long period could lead to theft and IoT incorporates many such things. In this paper, we are briefly discussing technological perspective of Internet of Things security. Because, the protection was a major concern when just two devices were coupled. In this context, security is the most significant of them. Today scenario, there are millions of connected devices and billions of sensors and their numbers are growing. All of them are expected secure and reliable connectivity. Consequently, companies and organizations adopting IoT technologies require well-designed security IoT architectures.

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The Internet-of-Things (IoT) Security : A Technological Perspective and Review

The Internet as a whole does not use secure links, thus information in transit may be vulnerable to interruption as well. The important of reducing a chance of the information being detected during the transmission is being an issue in the real world now days. The Digital watermarking method provides for the quick and inexpensive distribution of digital information over the Internet. This method provides new ways of ensuring the sufficient protection of copyright holders in the intellectual property dispersion process. The property of digital watermarking images allows insertion of additional data in the image without altering the value of the image. This message is hidden in unused visual space in the image and stays below the human visible threshold for the image. Both seek to embed information inside a cover message with little or no degradation of the cover-object. In this paper investigate the following relevant concepts and terminology, history of watermarks and the properties of a watermarking system as well as a type of watermarking and applications. We are proposing edge detection using Gabor Filters. In this paper we are proposed least significant bit (LSB) substitution method to encrypt the message in the watermark image file. The benefits of the LSB are its simplicity to embed the bits of the message directly into the LSB plane of cover-image and many techniques using these methods. The LSB does not result in a human perceptible difference because the amplitude of the change is little therefore the human eye the resulting stego image will look identical to the cover image and this allows high perceptual transparency of the LSB. The spatial domain technique LSB substitution it would be able to use a pseudo-random number generator to determine the pixels to be used for embedding based on a given key. We are using DCT transform watermark algorithms based on robustness. The watermarking robustness have been calculated by the Peak Signal to Noise Ratio (PSNR) and Normalized cross correlation (NC) is used to quantify by the similarity between the real watermark and after extracting watermark.

Big Data make conversant with novel technology, skills and processes to your information architecture and the people that operate, design, and utilization them. The big data delineate a holistic information management contrivance that comprise and integrates numerous new types of data and data management together conventional data. The Hadoop is an unlocked source software framework licensed under the Apache Software Foundation, render for supporting data profound applications running on huge grids and clusters, to proffer scalable, credible, and distributed computing. This is invented to scale up from single servers to thousands of machines, every proposition local computation and storage. In this paper, we have endeavored to converse about on the taxonomy for big data and Hadoop technology. Eventually, the big data technologies are necessary in providing more actual analysis, which may leadership to more concrete decision-making consequence in greater operational capacity, cost deficiency, and detect risks for the business. In this paper, we are converse about the taxonomy of the big data and components of Hadoop.

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Firoj Parwej

Papers

The Internet of Things (IoT) and its Application Domains

An Adaptive Watermarking Technique for the copyright of digital images and Digital Image Protection

The Internet-of-Things (IoT) Security : A Technological Perspective and Review

An Adaptive Watermarking Technique for the copyright of digital images and Digital Image Protection

A Perusal of Big Data Classification and Hadoop Technology