一个定制的哈希算法,用于在公共云中托管安全的灰度图像存储库
Veenasri Murugesan1, Nithya Chidambaram2, Rengarajan Amirtharajan1
1School of Electrical & Electronics Engineering, SASTRA Deemed University, Thanjavur, 613401, India.
Scientific reports
|December 13, 2025
概括
本研究介绍了一种基于区块的新哈希算法,用于安全的云图像存储,增强数据完整性和改检测. 该系统有效地识别了修改的图像区域,确保了云环境中可靠的数据安全.
科学领域:
- 计算机科学 计算机科学
- 信息安全 信息安全
- 云计算 云计算 云计算 云计算
背景情况:
- 在存储和传输过程中数据泄露在数字技术中带来了重大挑战.
- 传统的数据丢失预防 (DLP) 方法在处理大量数据时遇到困难.
- 云计算为数据安全和管理提供了可扩展和强大的解决方案.
研究的目的:
- 提出一种基于块的定制哈希算法,用于生成灰度图像的数字指纹.
- 为了增强数据完整性,实现改检测,并准确地识别存储在云中的图像中的改区域.
- 整合用户级认证,并开发一个用于实际应用的GUI.
主要方法:
- 开发了一种基于块的定制哈希算法,用于生成图像哈希值.
- 实施云环境,以安全存储和管理数字指纹.
- 集成用户级认证,并创建了一个图形用户界面 (GUI) 用于哈希生成和改验证.
主要成果:
- 拟议的算法成功生成数字指纹,以防改整个图像 (256x256).
- 完整性验证是通过将生成的消化剂与原始消化剂进行比较来实现的.
- 该算法在对完整性代码,碰撞特性和雪崩效应的定量和定性测试中表现良好.
结论:
- 基于自定义块的哈希算法有效地确保了图像数据的完整性和云存储中的改检测.
- 开发的框架,包括GUI和用户身份验证,为管理图像安全提供了安全和用户友好的解决方案.
- 拟议的方法提供了一个可扩展和可靠的方法来打击云环境中的数据泄露.
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