Visual IoT Security: Data Hiding in AMBTC Images Using Block-Wise Embedding Strategy

Area of Science:

• Computer Science
• Information Security
• Image Processing

Background:

• Visual Internet of Things (IoT) is crucial for smart cities, necessitating secure data transmission.
• Image compression is vital for efficient data transfer but poses security challenges.
• Data hiding in digital images is essential for authentication, forgery prevention, and intellectual property protection.

Purpose of the Study:

• To develop a novel data hiding scheme for compressed images using Absolute Moment Block Truncation Coding (AMBTC).
• To improve the visual quality of data-embedded compressed images by leveraging human vision system properties.
• To enhance security and transmission efficiency for visual data in the Internet of Things (IoT) context.

Main Methods:

• A two-phase data hiding strategy is proposed for AMBTC compressed images.
• An intra-block embedding phase manipulates AMBTC parameters using a novel hidden function.
• An inter-block embedding phase reversibly embeds data by exploiting adjacent block value relevance.
• A direct binary search halftoning scheme is integrated to enhance image quality without altering fixed parameters.
• Data extraction is performed using the modulo operator.

Main Results:

• The proposed method effectively embeds secret data within AMBTC compressed images.
• Experimental results demonstrate superior visual quality compared to existing methods.
• The scheme enhances network transmission efficiency by hiding data in compressed images.
• The method proves effective for increasing IoT security.

Conclusions:

• The developed data hiding scheme offers an effective solution for securing compressed images.
• The integration of human vision properties and AMBTC improves visual quality and security.
• This research contributes to more efficient and secure data handling in visual IoT applications.