The field of edge computing and IoT is moving towards developing innovative solutions for secure data protection and authentication. Researchers are exploring new frameworks and algorithms to ensure the security and privacy of user data, particularly in decentralized edge computing ecosystems. The focus is on designing secure, anonymous, and auditable offloading frameworks that protect sensitive user service information and prevent unfair offloading and malicious attacks. Additionally, there is a growing interest in developing robust image encryption schemes that can efficiently protect large-volume image data in resource-constrained IoT devices. Noteworthy papers include:

• SA2FE, a novel framework for edge access control, offloading, and accounting that ensures fair offloading decisions and protects sensitive user service information.
• A Novel Feature-Aware Chaotic Image Encryption Scheme, which integrates feature-aware pixel segmentation with chaotic chain permutation and confusion mechanisms to enhance security while maintaining efficiency.
• Active Light Modulation to Counter Manipulation of Speech Visual Content, which proposes a system for protecting live speech videos from visual falsification of speaker identity and lip and facial motion.