Anonymity in traceable cloud data broadcast system with simultaneous individual messaging

• Published in: International journal of information security 2021-06, Vol.20 (3), p.405-430
• Main Author: Mandal, Mriganka
• Format: Article
• Language: English
• Subjects: Cloud computing; Coding and Information Theory; Communications Engineering; Computer Communication Networks; Computer Science; Computing costs; Consumers; Cost analysis; Cryptology; Customization; Encryption; Internet of Things; Management of Computing and Information Systems; Messages; Networks; Operating Systems; Privacy; Regular Contribution
• ISSN: 1615-5262; 1615-5270
• DOI: 10.1007/s10207-020-00512-9

Internet of Things (IoT) and cloud computing are separate emerging paradigms, which are both an indispensable part of numerous ubiquitous devices that are connected to our life via the Internet. Their enactment and effectiveness are presumed to be more and more pervasive, making them essential ingredients of the Future Internet. Cloud data broadcast system is a novel framework where the advancement of both cloud and IoT is merged and becomes an enabler of a vast number of application scenarios. A data broadcast system with simultaneous individual messaging, aka broadcast encryption with personalized messages (BEPM), outsources not only a common encrypted message to a group of consumers but also encrypted personalized messages to individual consumers of the cloud server. Currently available BEPM are not secure against social engineering attacks, which means information of subscribed consumers is available to enemies. In this article, we present a new cloud data broadcast paradigm, called anonymous cloud data broadcast system with simultaneous individual messaging, in which anonymity of subscribed consumers is a primary concern. Furthermore, we extend our study of anonymization to develop the first traceable cloud data broadcast system with simultaneous individual messaging that concatenates two mutually orthogonal functionalities, namely consumer’s anonymity and traitor consumers traceability, in a unified manner. In particular, security and performance analysis explicates that both the designs are very cost-effective as consumer’s secret-key size is constant that fulfills the goals of achieving low overhead and computational cost for resource-constrained IoT devices.