Paper Type

Complete

Abstract

The legitimacy and integrity of live-streaming content remain a concern. According to studies, conventional watermarking solutions still need to manage the dynamic nature of streaming content. In this paper, we assess the restrictions of existing techniques and offer an adaptive quantitative index modulation (QIM) watermarking solution. Historical approaches struggled with dynamic frame rates, resolution changes, and real-time processing, resulting in insufficient tampering detection. The artifact uses adaptive Quantization Index Modulation (QIM) to distinguish itself in real-time streaming. The artifact detects manipulation via temporal discrepancies, content updates, and latency limits. This design research seeks a new watermarking solution. A comprehensive solution for ensuring authenticity, unaltered state, and reliable delivery of real-time streaming content is proposed. It stands out due to its adaptability to streaming media dynamics.

Paper Number

1740

Author Connect URL

https://authorconnect.aisnet.org/conferences/AMCIS2024/papers/1740

Comments

SIGSEC

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Aug 16th, 12:00 AM

Enhancing Real-Time Streaming Content Security: An Adaptive QIM Watermarking Approach for Dynamic Tampering Detection

The legitimacy and integrity of live-streaming content remain a concern. According to studies, conventional watermarking solutions still need to manage the dynamic nature of streaming content. In this paper, we assess the restrictions of existing techniques and offer an adaptive quantitative index modulation (QIM) watermarking solution. Historical approaches struggled with dynamic frame rates, resolution changes, and real-time processing, resulting in insufficient tampering detection. The artifact uses adaptive Quantization Index Modulation (QIM) to distinguish itself in real-time streaming. The artifact detects manipulation via temporal discrepancies, content updates, and latency limits. This design research seeks a new watermarking solution. A comprehensive solution for ensuring authenticity, unaltered state, and reliable delivery of real-time streaming content is proposed. It stands out due to its adaptability to streaming media dynamics.

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