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This paper presents the threat modeling approach for pervasive environment's security. In pervasive computing, a user might be part of various security domains at any particular instant of time having various authentication mechanisms and different privileges in different security domains. A number of threat modeling approaches and methods have been defined in literature and are in use. However, because of the nature of the pervasive computing and ubiquitous networks, these approaches do not handle the inherent security problems and perspective of pervasive computing. The paper examines in detail the threat modeling and analysis approaches being developed at Microsoft and other methods used for threat modeling. The paper present a novel approach for addressing the threat modeling in pervasive computing and presents the model for threat modeling and risk analysis in pervasive environment.

Context Awareness is the task of inferring contextual data acquired through sensors present in the environment. ‘Context’ encompasses all knowledge bounded by a scope and includes attributes of machines and users. A general context aware system is composed of context gathering and context inference modules. This paper proposes a Context Inference Engine (CiE) that classifies the current context as one of several recorded context activities. The engine follows a distance measure based classification approach with standard deviation based ranks to identify likely activities. The paper presents the algorithm and some results of the context classification process.

Context awareness enables smart service discovery and adaptation for mobile and wireless hosts. The contextual data is acquired from sensors present in the smart space, which may be absent. The inherent noisy nature of wireless environments does not guarantee the gathering of correct data. A history module is thus required in conjunction with existing context-aware systems that overcomes these limitations by predicting the data. We present a modular approach that when coupled with existing context managers will be able to provide user preference on the basis of usage history.

Context aware systems strive to facilitate better usability through advanced devices, interfaces and systems in day to day activities. These systems offer smart service discovery, delivery and adaptation all based on the current context. A context aware system must gather the context prior to context inference. This gathered context is then stored in a tagged, platform independent format using Extensible Markup Language (XML) or Web Ontology Language (OWL). The hierarchy is enforced for fast lookup and contextual data organization. Researchers have proposed and implemented different contextual data organizations a large number of which has been reviewed in this chapter. The chapter also identifies the tactics of contextual data organizations as evident in the literature. A qualitative comparison of these structures is also carried out to provide reference to future research.

With the advent of smart, inexpensive devices and a highly connected world, a need for smart service discovery, delivery, and adaptation has appeared. This interconnection is composed of sensors within devices or placed externally in the surrounding environment. Our research addresses this need through a context aware system, which adapts to the users’ context. Given that the devices are mobile and battery operated, the main challenge in a context awareness approach is power conservation. The devices are composed of small sensors that consume power in the order of a few mW. However, their consumptions increase manifold during data processing. There is a need to conserve power while delivering the requisite functionality of the context aware system. Therefore, this feature is termed as ‘power awareness.’ In this paper, we describe different power awareness techniques and compare them in terms of their conservation effectiveness. In addition, based on the investigations and comparison of the results, a power aware framework is proposed for a context aware system.

Context Awareness is the mechanism through which systems can adapt to the needs of a user by monitoring the context. Context includes environment, spatial, temporal, etc information that is used to infer the current activity. UML is used to design a context aware system. The context aware system is viewed as an Object Oriented software product. The UML model is generated through ArgoUML, a free UML modelling tool. The Use Case Diagram, the Sequence Diagrams and the Class Diagram are modelled using this tool. The Class Diagram is subjected to CK metrics to identify the strengths and weaknesses of the design. The measurements show that the proposed model is within the recommended range.

Widespread use of numerous hand-held smart devices has opened new avenues in computing. Internet of things (IoT) is the next big thing resulting in the 4th industrial revolution. Coupling IoT with data collection, storage, and processing leads to Internet of everything (IoE). This work outlines the concept of smart device and presents an IoE ecosystem. Characteristics of IoE ecosystem with a review of contemporary research is also presented. A comparison table contains the research finding. To realize IoE, an object-oriented context aware model is presented. This model is based on Unified Modelling Language (UML). A case study of a museum guide system is outlined that discusses how IoE can be implemented. The contribution of this chapter includes review of contemporary IoE systems, a detailed comparison, a context aware IoE model, and a case study to review the concepts.