scholarly journals Nondeterministic Algorithm for Breaking Diffie-Hellman Key Exchange using Self-Assembly of DNA Tiles

Author(s):  
Zheng Cheng
2010 ◽  
Vol 7 (5) ◽  
pp. 856-861
Author(s):  
Zhen Cheng ◽  
Yufang Huang ◽  
Zhihua Chen ◽  
Xiaolong Shi ◽  
Jin Xu

Author(s):  
Yibo Liu ◽  
Xuejing Hao ◽  
Yanjun Mao

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.


2021 ◽  
Vol 11 (19) ◽  
pp. 9276
Author(s):  
Alfred Anistoroaei ◽  
Adriana Berdich ◽  
Patricia Iosif ◽  
Bogdan Groza

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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