An Image Authentication Scheme Using Merkle Tree Mechanism

Abstract

[[abstract]]數位影像處理的研究在近年來變得相當頻繁而且進展快速，學者們提出各種不同的影像驗證機制，另一方面，區塊鏈技術在近期也非常熱門，由於區塊鏈機制中的Merkle tree 樹根為記憶圖像特徵提供了可靠的環境，IPFS（Inter-Planetary File System）協議提供了分散的存儲系統，本篇提出一個新的影像驗證機制，基於區塊鏈中的Merkle tree技術來進行驗證。在影像驗證上每個影像的驗證可以藉由Merkle tree的機制取得路徑上分支點的Hash值即可驗證影像的正確性，並且結合分散式儲存系統IPFS提高取得影像的可用性。本影像驗證之方法為分散式的架構，驗證的過程於區塊鏈網路節點中，是不需仰賴第三方，對於資安上層面，比起集中式的驗證管理系統更佳可靠。本篇論文方法除了可以驗證影像之完整性，也能在影像被竄改之情況下進行復原，由於驗證機制使用Hash值來比對，因此能辨別出影像上的些微更動，相對的對於影像遭旋轉、平移的篡改，本研究方法效果較不明顯。 Research in the digital image processing field has received significant attention and has advanced rapidly in recent years. Image tampering and misattribution have become real concerns in the open environment of the worldwide web, and scholars have proposed various image verification mechanisms to detect and mitigate image tampering. Likewise, blockchain technology has become very popular in recent years. This study proposes a novel image verification mechanism based on the Merkle tree, a fundamental component of blockchains that underpin their functionality. The Merkle tree root in the blockchain mechanism provides a reliable environment for storage of image features. The verification of images to detect tampering can be performed by the Merkle tree mechanism to obtain the hash values of the Merkle tree nodes. In addition, the proposed method combined with the Inter-Planetary File System (IPFS) to improve the availability of images. The primary purpose of this study is to achieve the goal of image integrity verification. The proposed method can not only verify the integrity of an image, but can also repair the tampered area if the image has been altered. Because the proposed method employs the blockchain mechanism, third party is not needed for image verification. The verification method is performed by each node in the blockchain network. The experimental results demonstrate that the proposed method successfully achieves the goal of image authentication and tampered area restoration. Since the verification mechanism uses the hash values for change detection, it can recognize the slightest alterations in the image. However, the tampering of the rotation and translation is less obvious