Learning Efficient Hash Codes for Fast Graph-Based Data Similarity Retrieval

Author(s):  
Jinbao Wang ◽  
Shuo Xu ◽  
Feng Zheng ◽  
Ke Lu ◽  
Jingkuan Song ◽  
...  
2021 ◽  
Author(s):  
Mingyue Li ◽  
Lixin Du ◽  
Jiangying Xu ◽  
Chen Guo

2019 ◽  
Vol 9 (15) ◽  
pp. 3097 ◽  
Author(s):  
Diego Renza ◽  
Jaime Andres Arango ◽  
Dora Maria Ballesteros

This paper addresses a problem in the field of audio forensics. With the aim of providing a solution that helps Chain of Custody (CoC) processes, we propose an integrity verification system that includes capture (mobile based), hash code calculation and cloud storage. When the audio is recorded, a hash code is generated in situ by the capture module (an application), and it is sent immediately to the cloud. Later, the integrity of the audio recording given as evidence can be verified according to the information stored in the cloud. To validate the properties of the proposed scheme, we conducted several tests to evaluate if two different inputs could generate the same hash code (collision resistance), and to evaluate how much the hash code changes when small changes occur in the input (sensitivity analysis). According to the results, all selected audio signals provide different hash codes, and these values are very sensitive to small changes over the recorded audio. On the other hand, in terms of computational cost, less than 2 s per minute of recording are required to calculate the hash code. With the above results, our system is useful to verify the integrity of audio recordings that may be relied on as digital evidence.


Author(s):  
Donglin Zhang ◽  
Xiao-Jun Wu ◽  
He-Feng Yin ◽  
Josef Kittler

Author(s):  
Pengyi Hao ◽  
Youdong Ding ◽  
Yuchun Fang ◽  
Ranran Zhang ◽  
Shuhan Wei
Keyword(s):  

2021 ◽  
Vol 90 ◽  
pp. 127-128
Author(s):  
P. Krondorfer ◽  
D. Slijepčević ◽  
F. Unglaube ◽  
A. Kranzl ◽  
C. Breiteneder ◽  
...  

2019 ◽  
Vol 117 ◽  
pp. 74-82 ◽  
Author(s):  
Kun Su ◽  
Gongping Yang ◽  
Lu Yang ◽  
Dunfeng Li ◽  
Peng Su ◽  
...  

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