A Novel Algorithm for Digital Watermarking for Image Tamper Localization and Recovery

2013 ◽  
Vol 432 ◽  
pp. 538-542
Author(s):  
Chuan Mu Li
Keyword(s):  
Digital Watermarking ◽  
Image Authentication ◽  
Chaotic Sequence ◽  
Key Exchange ◽  
Tamper Localization ◽  
Exchange Method ◽  
Diffie Hellman ◽  
Diffie Hellman Key Exchange ◽  
Content Feature ◽  
Novel Algorithm

A content-based and block-wise image authentication algorithm with location and recovery is presented. In this algorithm, the watermark of each block is its content-feature which is encrypted by md5, and it is embedded in another block which selected by an ergodic matrix of a chaotic sequence. That all security parameters are user dependent and can be computed at both ends individually based on Diffie-Hellman key exchange method makes the scheme not only robust against collage attack but also truly oblivious. The experiments demonstrate that the proposed scheme can detect and localize any tampering of size 8x8 pixels and above and can recover a 40% damaged image to an intelligible one.

A Robust Algorithm for Digital Watermarking with Tamper Recovery

2013 ◽  
Vol 432 ◽  
pp. 533-537
Author(s):  
Chuan Mu Li
Keyword(s):  
Digital Watermarking ◽  
Image Authentication ◽  
Chaotic Sequence ◽  
Authentication Scheme ◽  
Exchange Method ◽  
Robust Algorithm ◽  
Diffie Hellman ◽  
Tamper Recovery ◽  
Diffie Hellman Key Exchange ◽  
Content Feature

A block-wise and content-based image authentication scheme with location and recovery is presented. In this scheme, the watermark of each block is an encrypted form of its content-feature, which is embedded in another block which selected by an ergodic matrix of a chaotic sequence. The randomicity of selected block can robust the VQ attack. The encryption further strengthens the security. That all security parameters are user dependent and can be computed at both ends individually based on Diffie-Hellman key exchange method makes the scheme not only robust against collage attack but also truly oblivious. The experiments demonstrate that the proposed scheme can detect and localize any tampering of size 8x8 pixels and above and can recover a 40% damaged image to an intelligible one.

Research on psychological stress intervention of college students based on Diffie-hellman key exchange algorithm

2021 ◽  
pp. 1-7
Author(s):  
Yibo Liu ◽  
Xuejing Hao ◽  
Yanjun Mao
Keyword(s):  
College Students ◽  
Psychological Stress ◽  
Original Data ◽  
Key Exchange ◽  
Psychological Burden ◽  
Exchange Algorithm ◽  
Diffie Hellman ◽  
Stress Intervention ◽  
Psychological Pressure ◽  
Diffie Hellman Key Exchange

At present, the mental health of college students has also become an important issue that urgently needs attention under the influence of the surrounding environment. It is coupled with the grim employment situation after graduation and the students’ psychological burden is becoming more and heavier. This paper based on Diffie-Hellman key exchange algorithm studied the effect of psychological stress intervention. First, the Diffie-Hellman key exchange algorithm was analyzed, and then the Diffie-Hellman prediction model was established according to the psychological pressure of college students. Secondly, the simulation test was conducted to compare the simulated results with the original data. The conclusion of the data fitting of the network model training set, verification set and test set were good and the error was very small. Finally, the detailed application of the algorithm and the model were described.

scholarly journals Secure Audio-Visual Data Exchange for Android In-Vehicle Ecosystems

2021 ◽  
Vol 11 (19) ◽  
pp. 9276
Author(s):  
Alfred Anistoroaei ◽  
Adriana Berdich ◽  
Patricia Iosif ◽  
Bogdan Groza
Keyword(s):  
Data Exchange ◽  
Key Exchange ◽  
Visual Data ◽  
Security Applications ◽  
Diffie Hellman ◽  
Audio Data ◽  
Diffie Hellman Key Exchange ◽  
Visual Domain ◽  
Audio Video ◽  
Acoustic Domain

Mobile device pairing inside vehicles is a ubiquitous task which requires easy to use and secure solutions. In this work we exploit the audio-video domain for pairing devices inside vehicles. In principle, we rely on the widely used elliptical curve version of the Diffie-Hellman key-exchange protocol and extract the session keys from the acoustic domain as well as from the visual domain by using the head unit display. The need for merging the audio-visual domains first stems from the fact that in-vehicle head units generally do not have a camera so they cannot use visual data from smartphones, however, they are equipped with microphones and can use them to collect audio data. Acoustic channels are less reliable as they are more prone to errors due to environmental noise. However, this noise can be also exploited in a positive way to extract secure seeds from the environment and audio channels are harder to intercept from the outside. On the other hand, visual channels are more reliable but can be more easily spotted by outsiders, so they are more vulnerable for security applications. Fortunately, mixing these two types of channels results in a solution that is both more reliable and secure for performing a key exchange.

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