The emergence of video streams as a primary medium for communication and the demand for high-quality video sharing over the internet have given rise to several security and privacy issues, such as unauthorized access and data breaches. To address these limitations, various Selective Video Encryption (SVE) schemes have been proposed, which encrypt specific portions of a video while leaving others unencrypted. The SVE approach balances security and usability, granting unauthorized users access to certain parts while encrypting sensitive content. However, existing SVE schemes adopt an all-or-nothing coarse-grain encryption approach, where a user with a decryption key can access all the contents of a given video stream. This paper proposes and designs a fine-grained access control-based selective video encryption scheme, ABSVE, and a use-case protocol called Blind Brother. Our scheme encrypts different identified Regions of Interest (ROI) with a unique symmetric key and applies a Ciphertext Policy Attribute Based Encryption (CP-ABE) scheme to tie these keys to specific access policies. This method provides multiple access levels for a single encrypted video stream. Crucially, we provide a formal syntax and security definitions for ABSVE, allowing for rigorous security analysis of this and similar schemes - which is absent in prior works. Finally, we provide an implementation and evaluation of our protocol in the Kvazaar HEVC encoder. Overall, our constructions enhance security and privacy while allowing controlled access to video content and achieve comparable efficiency to compression without encryption.

Functional Encryption (FE) is a cutting-edge cryptographic technique that enables a user with a specific functional decryption key to determine a certain function of encrypted data without gaining access to the underlying data. Given its potential and the fact that FE is still a relatively new field, we set out to investigate how it could be applied to resource-constrained environments. This work presents what we believe to be the first lightweight FE scheme explicitly designed for resource-constrained devices. We also propose a use case protocol that demonstrates how our scheme can secure an Internet of Things (IoT) architecture where relevant devices collect data and securely deliver them to a storage server, where an analyst can request access to the encrypted data. Finally, we conduct thorough experiments on two commercially available resource-constrained devices to provide compelling evidence of our approach’s practicality and efficiency. Although the results of our evaluations show that there is room for improvement in the proposed scheme, this work represents one of the first attempts to apply FE to the IoT setting that can directly impact people’s daily lives and the everyday operations of organizations.

Functional Encryption (FE) allows users to extract specific function-related information from encrypted data while preserving the privacy of the underlying plaintext. Though significant research has been devoted to developing secure and efficient Multi-Input Functional Encryption schemes supporting diverse functions, there remains a noticeable research gap in the development of verifiable FE schemes. Functionality and performance have received considerable attention, however, the crucial aspect of verifiability in FE has been relatively understudied. Another important aspect that prior research in FE with outsourced decryption has not adequately addressed is the fairness of the data-for-money exchange between a curator and an analyst. This paper focuses on addressing these gaps by proposing a verifiable FE scheme for inner product computation. The scheme not only supports the multi-client setting but also extends its functionality to accommodate multiple users -- an essential feature in modern privacy-respecting services. Additionally, it demonstrates how this FE scheme can be effectively utilized to ensure fairness and atomicity in a payment protocol, further enhancing the trustworthiness of data exchanges.