An Adaptive Lightweight Security Framework Suited for IoT
Standard security systems are widely implemented in the industry. These systems consume considerable computational resources. Devices in the Internet of Things [IoT] are very limited with processing capacity, memory and storage. Therefore, existing security systems are not applicable for IoT. To cope with it, we propose downsizing of existing security processes. In this chapter, we describe three areas, where we reduce the required storage space and processing power. The first is the classification process required for ongoing anomaly detection, whereby values accepted or generated by a sensor are classified as valid or abnormal. We collect historic data and analyze it using machine learning techniques to draw a contour, where all streaming values are expected to fall within the contour space. Hence, the detailed collected data from the sensors are no longer required for real-time anomaly detection. The second area involves the implementation of the Random Forest algorithm to apply distributed and parallel processing for anomaly discovery. The third area is downsizing cryptography calculations, to fit IoT limitations without compromising security. For each area, we present experimental results supporting our approach and implementation.
Part of the book: Internet of Things
Smart Home Systems Based on Internet of Things
Smart home systems achieved great popularity in the last decades as they increase the comfort and quality of life. Most smart home systems are controlled by smartphones and microcontrollers. A smartphone application is used to control and monitor home functions using wireless communication techniques. We explore the concept of smart home with the integration of IoT services and cloud computing to it, by embedding intelligence into sensors and actuators, networking of smart things using the corresponding technology, facilitating interactions with smart things using cloud computing for easy access in different locations, increasing computation power, storage space and improving data exchange efficiency. In this chapter we present a composition of three components to build a robust approach of an advanced smart home concept and implementation.
Part of the book: Internet of Things (IoT) for Automated and Smart Applications
Wearable Devices and their Implementation in Various Domains
Wearable technologies are networked devices that collect data, track activities and customize experiences to users? needs and desires. They are equipped, with microchips sensors and wireless communications. All are mounted into consumer electronics, accessories and clothes. They use sensors to measure temperature, humidity, motion, heartbeat and more. Wearables are embedded in various domains, such as healthcare, sports, agriculture and navigation systems. Each wearable device is equipped with sensors, network ports, data processor, camera and more. To allow monitoring and synchronizing multiple parameters, typical wearables have multi-sensor capabilities and are configurable for the application purpose. For the wearer?s convenience, wearables are lightweight, modest shape and multifunctional. Wearables perform the following tasks: sense, analyze, store, transmit and apply. The processing may occur on the wearer or at a remote location. For example, if dangerous gases are detected, the data are processed, and an alert is issued. It may be transmitted to a remote location for testing and the results can be communicated in real-time to the user. Each scenario requires personalized mobile information processing, which transforms the sensory data to information and then to knowledge that will be of value to the individual responding to the situation.
Part of the book: Wearable Devices
Expanding Navigation Systems by Integrating It with Advanced Technologies
Navigation systems provide the optimized route from one location to another. It is mainly assisted by external technologies such as Global Positioning System (GPS) and satellite-based radio navigation systems. GPS has many advantages such as high accuracy, available anywhere, reliable, and self-calibrated. However, GPS is limited to outdoor operations. The practice of combining different sources of data to improve the overall outcome is commonly used in various domains. GIS is already integrated with GPS to provide the visualization and realization aspects of a given location. Internet of things (IoT) is a growing domain, where embedded sensors are connected to the Internet and so IoT improves existing navigation systems and expands its capabilities. This chapter proposes a framework based on the integration of GPS, GIS, IoT, and mobile communications to provide a comprehensive and accurate navigation solution. In the next section, we outline the limitations of GPS, and then we describe the integration of GIS, smartphones, and GPS to enable its use in mobile applications. For the rest of this chapter, we introduce various navigation implementations using alternate technologies integrated with GPS or operated as standalone devices.
Part of the book: Geographic Information Systems in Geospatial Intelligence
Advancements in Optical Data Transmission and Security SystemsView all chapters
Optical Communication (OC) for data transmission was introduced more than 30 years ago. It employs two main technologies, fiber optics using a physical wire and Free Space Optical (FSO) wireless transmission. Fiber optics has been well developed over the years in terms of distance, bandwidth, speed, reliability, and other enhancements that contribute to its use. Recent developments in FSO transmission has made it the mainstream and a better alternative compared to RF wireless transmission, concerning all parameters. In this chapter, we focus on advancements in OC that represent innovative ideas of how to enable new methods of secured optical data transmission in different ways and not simply as an extension to current methods and technologies.
Part of the book: Cryptography