The Internet of Things (IoT) is widely known as a computer network of interconnected electronic devices with intelligent processing and optimized controlling. Recently, the ubiquitous mobile devices have witnessed an evolution of participatory sensing in the IoT. Crowd-sensing, known as a new sensing paradigm, relies on both static sensors and dynamic mobile devices to jointly collect diverse data from surroundings. In some application-specific scenarios, such as traffic monitoring and smart city, a large volume of sensing data is outsourced to data servers for storage and processing. During the entire process, the IoT and data servers are separately tasked with distinct functionalities. In particular, the IoT can be regarded as sensing devices that collect crowd-sensing data as the front-end; while the cloud computer servers are responsible for data storage and efficient processing, acting as the back-end.

However, security and privacy issues have been two critical concerns, especially in the IoT with crowd-sensing. These issues include trustworthy data sensing and transmission at the front-end, as well as data confidentiality, integrity, and privacy preservation of mobile users at the back-end. More importantly, security and privacy solutions should be systematically studied in a cross-domain strategy that can protect data from the electronical device of information sensing the centralized data processing save in the back-end cloud computer system. Meanwhile, the complexity and diversity of crowd-sensing data also pose a new challenge for secure data collection, fusion, transmission, and processing.

Therefore, it is time to revisit the security and privacy issues from a comprehensive perspective in IoT; this special issue will focus on novel security and privacy protection methods for the IoT system with crowd-sensing. The guest editors cordially invite the state-of-the-art research contributions from the academia and the industry that address the timely security challenges of integrating IoT with crowd-sensing.

Potential topics include but are not limited to the following:

• Security threats for Internet of Things with crowd-sensing
• Secure IoT architectures with diverse crowd-sensing
• Privacy protection and data trustworthiness in sensing big data from IoT
• Schemes, model, and tools for security and privacy protection in crowd-sensing IOT
• Detection and defenses of attacks in IOT with crowd-sensing
• Secure IoT applications with crowd-sensing data
• Schemes, model, and tools for secure data fusion in IOT
• Security of IoT sensing data in cloud systems
• Privacy preserving data processing in IoT with crowd-sensing
• Novel searchable encryption schemes for outsourced crowd-sensing data
• Security and privacy concerned applications in IoT with crowd-sensing
• Security analysis techniques for IOT and its data sensing process