Abstract: The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.
Abstract: Context-aware technologies provide system
applications with the awareness of environmental conditions,
customer behaviours, object movements, etc. Further, with such
capability system applications can be smart to intelligently adapt their
responses to the changing conditions. In regard to business
operations, this promises businesses that their business processes can
run more intelligently, adaptively and flexibly, and thereby either
improve customer experience, enhance reliability of service delivery,
or lower operational cost, to make the business more competitive and
sustainable. Aiming at realising such context-aware business process
management, this paper firstly explores its potential benefit, and then
identifies some gaps between the current business process
management support and the expected. In addition, some preliminary
solutions are also discussed in regard to context definition, rule-based
process execution, run-time process evolution, etc. A framework is
also presented to give a conceptual architecture of context-aware
business process management system to guide system
implementation.
Abstract: Context awareness is a capability whereby mobile
computing devices can sense their physical environment and adapt
their behavior accordingly. The term context-awareness, in
ubiquitous computing, was introduced by Schilit in 1994 and has
become one of the most exciting concepts in early 21st-century
computing, fueled by recent developments in pervasive computing
(i.e. mobile and ubiquitous computing). These include computing
devices worn by users, embedded devices, smart appliances, sensors
surrounding users and a variety of wireless networking technologies.
Context-aware applications use context information to adapt
interfaces, tailor the set of application-relevant data, increase the
precision of information retrieval, discover services, make the user
interaction implicit, or build smart environments. For example: A
context aware mobile phone will know that the user is currently in a
meeting room, and reject any unimportant calls. One of the major
challenges in providing users with context-aware services lies in
continuously monitoring their contexts based on numerous sensors
connected to the context aware system through wireless
communication. A number of context aware frameworks based on
sensors have been proposed, but many of them have neglected the
fact that monitoring with sensors imposes heavy workloads on
ubiquitous devices with limited computing power and battery. In this
paper, we present CALEEF, a lightweight and energy efficient
context aware framework for resource limited ubiquitous devices.