MailLeak:使用迁移学习的模糊鲁棒特征提取

Wei Wang, Emily Sallenback, Zeyu Ning, Hugues Nelson Iradukunda, Wenxing Lu, Qingquan Zhang, Ting Zhu
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引用次数: 2

摘要

信封上的模糊图像被认为是安全的,已被广泛用于保护邮件中的信息。在本文中,我们提出了一种新的算法,可以从混淆图像中进行字符识别。具体来说,通过使用迁移学习方法,我们证明了攻击者可以在不打开信封的情况下有效地识别信件。我们认为,所提出的方法揭示了对当前邮政服务的潜在威胁。为了防御提议的攻击,我们引入了一个与上下文相关的着色器来防止此类威胁的发生。
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MailLeak: Obfuscation-Robust Character Extraction Using Transfer Learning
The obfuscated images on envelopes are believed to be secure and have been widely used to protect the information contained in a mail. In this paper, we present a new algorithm that can conduct character recognition from obfuscated images. Specifically, by using a transfer learning method, we prove that an attacker can effectively recognize the letter without unfolding the envelope. We believe that the presented method reveals the potential threat to current postal services. To defend against the proposed attack, we introduce a context-related shader to prevent such threats from occurring.
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