Simple and secured access to networked home appliances via internet using SSL, BioHashing and single Authentication Server

This thesis describes a web-based application that will enable users to access their networked home appliances over the Internet in an easy, secured, accessible and cost effective manner, using the user's iris image only for authentication. As Internet is increasingly gaining significance and popularity in our daily lives, various home networking technologies also started gaining importance from consumers, which helped in facilitating interoperability, sharing of services and exchange of information between different electronic devices at home. As a result, the demand to be able to access home appliances or security cameras over the Internet gradually grew. In this research, we propose an efficient, secured, low-cost and user-friendly method to access networked home appliances over the Internet, providing strong, well integrated, three levels of security to the whole application and user data. According to our design, the user's iris data after hashing (using BioHashing) is sent through a secure communication channel utilizing Secure Sockets Layer v-3.0. The deterministic feature sequence from the iris image is extracted using 1D log-Gabor filters and while performing BioHashing, the orthonormalization of the pseudorandom number is implemented employing Gram-Schmidt orthonormalization algorithm. In addition to this protected data transfer mechanism, we propose the design of an Authentication Server that can be shared among multiple homes, allowing numerous users to access their home appliances in a trouble-free and secured manner. It can also bring down the cost of commercial realization of this endeavor and increase its accessibility without compromising on system security. We demonstrate that the recognition efficiency of this system is computationally effective with equal error rate (EER) of 0% and 6.75% (average) in two separate conditions on CASIA 1 and CASIA 2 iris image datasets

Agent Based Computing Environment for Accessing Previleged Servics

In this paper we propose an application for accessing privileged services on the web, which is deployed on JADE (Java Agent Development Framework) platform. There are many Organizations/ Institutes which have subscribed to certain services inside their network, and these will not be accessible to people who are a part of the Organization/Institute when they are outside their network (for example in his residence). Therefore we have developed two software agents; the person will request the Client Agent (which will be residing outside the privileged network) for accessing the privileged services. The Client Agent will interact with the Server Agent (which will be residing inside the network which is subscribed to privileged services), which will process the request, and send the desired result back to the Client Agent

An overview of machine learning and 5G for people with disabilities

Currently, over a billion people, including children (or about 15% of the world’s population), are estimated to be living with disability, and this figure is going to increase to beyond two billion by 2050. People with disabilities generally experience poorer levels of health, fewer achievements in education, fewer economic opportunities, and higher rates of poverty. Artificial intelligence and 5G can make major contributions towards the assistance of people with disabilities, so they can achieve a good quality of life. In this paper, an overview of machine learning and 5G for people with disabilities is provided. For this purpose, the proposed 5G network slicing architecture for disabled people is introduced. Different application scenarios and their main benefits are considered to illustrate the interaction of machine learning and 5G. Critical challenges have been identified and addressed.This work has been supported by the Agencia Estatal de Investigación of Ministerio de Ciencia e Innovación of Spain under project PID2019-108713RB-C51 MCIN/ AEI /10.13039/501100011033.Postprint (published version

Unobtrusive Health Monitoring in Private Spaces: The Smart Home

With the advances in sensor technology, big data, and artificial intelligence, unobtrusive in-home health monitoring has been a research focus for decades. Following up our research on smart vehicles, within the framework of unobtrusive health monitoring in private spaces, this work attempts to provide a guide to current sensor technology for unobtrusive in-home monitoring by a literature review of the state of the art and to answer, in particular, the questions: (1) What types of sensors can be used for unobtrusive in-home health data acquisition? (2) Where should the sensors be placed? (3) What data can be monitored in a smart home? (4) How can the obtained data support the monitoring functions? We conducted a retrospective literature review and summarized the state-of-the-art research on leveraging sensor technology for unobtrusive in-home health monitoring. For structured analysis, we developed a four-category terminology (location, unobtrusive sensor, data, and monitoring functions). We acquired 912 unique articles from four relevant databases (ACM Digital Lib, IEEE Xplore, PubMed, and Scopus) and screened them for relevance, resulting in n=55 papers analyzed in a structured manner using the terminology. The results delivered 25 types of sensors (motion sensor, contact sensor, pressure sensor, electrical current sensor, etc.) that can be deployed within rooms, static facilities, or electric appliances in an ambient way. While behavioral data (e.g., presence (n=38), time spent on activities (n=18)) can be acquired effortlessly, physiological parameters (e.g., heart rate, respiratory rate) are measurable on a limited scale (n=5). Behavioral data contribute to functional monitoring. Emergency monitoring can be built up on behavioral and environmental data. Acquired physiological parameters allow reasonable monitoring of physiological functions to a limited extent. Environmental data and behavioral data also detect safety and security abnormalities. Social interaction monitoring relies mainly on direct monitoring of tools of communication (smartphone; computer). In summary, convincing proof of a clear effect of these monitoring functions on clinical outcome with a large sample size and long-term monitoring is still lacking

A novel three stage network joining protocol for home automation

Modern advances in electronics and communication technology have given rise to the development of several home automation technologies and systems. Current home automation systems have several drawbacks including high cost, not being of a Do It Yourself (DIY) nature, and there is currently no safe way for a simple Internet of Things (IoT) device to join a Local Area Network (LAN) without the addition of extra user interface hardware. The simplest IoT devices, for example a mains power switch, could contain just a cheap Wi-Fi interface and very limited computing capability. Such devices are already available for under US $4 but are not usable in the IoT context as they lack the ability to join a Wi-Fi network in a secure DIY manner. The ability to securely join IoT Devices to Wi-Fi networks is an on-going area of research. This thesis describes a novel three-stage network joining protocol, which that allows IoT devices to securely join a Wi-Fi network even if they completely lack a user interface. This protocol can eliminate a central controller for a home automation system and allow users to purchase off the shelf devices from a range of manufactures and control them by a PC or mobile device in a very simple manner. This new method will significantly reduce costs as the system and does not require expert configuration or a central controller. This in turn may help revitalize the home automation industry, which has not seen great penetration into suburban homes. The protocol is implemented using a WPA2 based LAN, an Android phone and a Raspberry Pi which represents an IoT device lacking any form of keyboard and display. The method allows cost reductions for simple IoT devices and is suitable for immediate adoption by manufacturers of IoT devices

Data fusion strategies for energy efficiency in buildings: Overview, challenges and novel orientations

Recently, tremendous interest has been devoted to develop data fusion strategies for energy efficiency in buildings, where various kinds of information can be processed. However, applying the appropriate data fusion strategy to design an efficient energy efficiency system is not straightforward; it requires a priori knowledge of existing fusion strategies, their applications and their properties. To this regard, seeking to provide the energy research community with a better understanding of data fusion strategies in building energy saving systems, their principles, advantages, and potential applications, this paper proposes an extensive survey of existing data fusion mechanisms deployed to reduce excessive consumption and promote sustainability. We investigate their conceptualizations, advantages, challenges and drawbacks, as well as performing a taxonomy of existing data fusion strategies and other contributing factors. Following, a comprehensive comparison of the state-of-the-art data fusion based energy efficiency frameworks is conducted using various parameters, including data fusion level, data fusion techniques, behavioral change influencer, behavioral change incentive, recorded data, platform architecture, IoT technology and application scenario. Moreover, a novel method for electrical appliance identification is proposed based on the fusion of 2D local texture descriptors, where 1D power signals are transformed into 2D space and treated as images. The empirical evaluation, conducted on three real datasets, shows promising performance, in which up to 99.68% accuracy and 99.52% F1 score have been attained. In addition, various open research challenges and future orientations to improve data fusion based energy efficiency ecosystems are explored

The Direction of mobile evolution examined through the NTT DoCoMo strategy, Mobile Frontier

NTT DoCoMo is Japan\u27s biggest mobile service provider. They added extra value into cellular phone as telephone , and contributed to the explosive spread of the mobile phone in Japan. They have still led Japan as a country with the world\u27s largest mobile Internet. The mobile phone now changes our lifestyles or work styles, and has a great influence also on business. In 1997, NTT DoCoMo created the company vision towards the year 2010, Mobile Frontier . It consists of five concepts, named MAGIC , and indicates the mobile phone figure in the future as a whole. I regard it as a guideline of this paper, and examine the direction of mobile evolution by researching the following topics: the present situation, the issues needed to realize each concept, and the future. At first, I state the background of the mobile phone spread in Japan and the cultural aspects peculiar to Japan. After that, I examine the mobile evolution along with the five concepts. The objective of this paper is to refer to and understand the vision of a leading company in the telecommunication field, and consider mobile communications\u27 influence and applications in the future. The goal is to expand knowledge in the present situation of the mobile phone and the trend towards future mobile, and to examine the direction the Mobile Frontier aims

Securing voice communications using audio steganography

Although authentication of users of digital voice-based systems has been addressed by much research and many commercially available products, there are very few that perform well in terms of both usability and security in the audio domain. In addition, the use of voice biometrics has been shown to have limitations and relatively poor performance when compared to other authentication methods. We propose using audio steganography as a method of placing authentication key material into sound, such that an authentication factor can be achieved within an audio channel to supplement other methods, thus providing a multi factor authentication opportunity that retains the usability associated with voice channels. In this research we outline the challenges and threats to audio and voice-based systems in the form of an original threat model focusing on audio and voice-based systems, we outline a novel architectural model that utilises audio steganography to mitigate the threats in various authentication scenarios and finally, we conduct experimentation into hiding authentication materials into an audible sound. The experimentation focused on creating and testing a new steganographic technique which is robust to noise, resilient to steganalysis and has sufficient capacity to hold cryptographic material such as a 2048 bit RSA key in a short audio music clip of just a few seconds achieving a signal to noise ratio of over 70 dB in some scenarios. The method developed was seen to be very robust using digital transmission which has applications beyond this research. With acoustic transmission, despite the progress demonstrated in this research some challenges remain to ensure the approach achieves its full potential in noisy real-world applications and therefore the future research direction required is outlined and discussed