Due to advancements in technology, the real world requires improvements in state-of-art services that can aid tremendous increases in computational power for the purpose of providing ground-breaking service delivery. This kind of increased computational power for smart devices could be provided by the Internet of Things (IoT). When these kinds of devices are used, there is a huge transfer of information resulting in usage of services and methodologies that could enable instant access with high quality, high security and reduced complexity.
To achieve such a speedy experience, methods related to big data, cloud, etc. can be used to make these services work seamlessly. Recent services provided by IoT are requests related to logistics, financial services, healthcare services, educational services, online purchasing, smart cities, etc., which help in getting the services carried out with limited time and effort. Furthermore, analysing such huge data can also help in knowing the choices of the population, along with their ratings and feedback regarding the services provided.
The usage of smartphones and wearable devices has encouraged a great shift from big data to crowd sourcing applications in IoT. The data collected through these mobile devices could be further used for analysis and then processed to aid intelligent decisions and services.
With the increased usage of these intelligent and interconnected devices in our daily lives, high trust, security and privacy are required. Hence data trust, privacy of data provider, attack identification and so on are research issues contributing to the achievement of high quality of service when data is collected, transmitted, selected, processed, analysed, mined and utilised. Though various novel solutions are offered, there are still unresolved challenges in the area of services provided by IoT and the trust, security and privacy of crowd sourcing applications in IoT.
This special issue aims to bring researchers, academicians and practitioners together to discuss the applications, state-of-art methodologies and real-time solutions for overcoming the challenges in IoT-based services in relation to aspects of trust, security and privacy in crowd sourcing, and to explore key technologies and innovative new solutions for overcoming the major challenges in this research filed.
Suitable topics include, but are not limited, to the following:
- Smart cities and smart homes
- Power grid, energy efficiency systems, applications and services
- Health monitoring and smart health applications
- Weather data analysis, visualisation and real case studies
- Spark/Advanced MapReduced; Large-scale NoSQL services; integrations between Spark/MapReduced and NoSQL
- Large-scale traffic control systems, algorithms and services
- Financial and business intelligence services and applications
- Supply chain computation, applications and services
- Innovative big data processing for IoT
- Security, privacy and trust
- Mobile applications, services and integrations
- Complex information systems: case studies and real deliveries
- Real-use cases and research contributions to industry
- Trust evaluation and management
- Truth discovery in huge volumes of unconnected data
- Big data trust and reputation enhancement mechanisms
- Security threat detection theories and technologies
- Crowdsourcing applications with privacy and security protection
Manuscripts due by: 31 July, 2017
Notification to authors: 30 October, 2017
Final versions due by: 30 December, 2017