Ubiquitous mobile computing, allowing the transmission of data, voice, and video via mobile devices (such as smartphones, tablets, and laptops) without having to be connected to a fixed physical link, has profoundly changed every-day life. Statistics show that the number of mobile devices worldwide will reach 17.72 billion by 2024. The data collected from mobile terminals provides significant support for analysis in social computing, healthcare, and finance. Although the connected mobile devices have brought great convenience, they have also caused many security and privacy issues.

In ubiquitous mobile computing, the existing techniques suffer from many practical security limitations due to massive devices and data. For example, they cannot accurately collect critical data and effectively analyze security risks. As a result, many techniques are ineffective or inefficient enough, making them less user-centric. Thus, it is crucial to design innovative techniques (e.g., artificial intelligence and deep learning) to guarantee the data security. On the other hand, in ubiquitous mobile computing, a large amount of users' privacy has been exposed and suffered from more threats, such as gradient inversion attacks and attribute inference attacks. The attacker can analyze and restore the user's privacy through fragments of personal information from mobile devices, such as the user’s location, personal photos, and sensors’ data. Traditionally, one-dimensional protection mechanisms have been difficult to satisfy the complex privacy protection requirements. Therefore, it is urgent to combine various privacy protection schemes and accurately protect privacy in ubiquitous mobile computing.

This Special Issue will focus on state-of-the-art research paradigms on security and privacy aspects in ubiquitous mobile computing, particularly with advances in Internet of Things (IoTs), mobile social networking and smart cities. Moreover, in this issue, the security and privacy challenges in mobile cloud computing will be spotlighted. Original research papers and state of the art reviews will be accepted.

Potential topics include but are not limited to the following:

• Artificial intelligence and deep learning for mobile computing
• Social computing, financial analysis, and medical assistance in mobile computing
• Cross-domain authentication for mobile computing devices
• Cross-cloud access control and delegation in mobile cloud computing
• Access control mechanism for large-scale IoT scenarios
• Biometrics/bio-cryptography access control
• Secure data sharing and storage for mobile computing
• Abnormal behavior audit
• Intrusion detection and response
• Crowd sensing model, mechanism and systems
• Theory and language of Privacy computing for mobile computation
• Cryptography-based privacy-preserving methods for mobile computing
• Game theory for privacy and accuracy, utility, and reliability for mobile computing
• Blockchain-based privacy-preserving methods for mobile computing