HCC: A hash function using error correcting codes

1997 ◽  
pp. 110-117
Author(s):  
Sami Harari
Keyword(s):  
Hash Function ◽  
Error Correcting Codes

Penerapan Kriptografi Keamanan Data Administrasi Kependudukan Desa Pagar Jati Menggunakan SHA-1

2020 ◽  
Vol 3 (2) ◽  
pp. 182-186
Author(s):  
Lisnayani Silalahi ◽  
Anita Sindar
Keyword(s):  
System Application ◽  
Data Security ◽  
Hash Function ◽  
Security System ◽  
Cryptographic Hash Function ◽  
Security Costs ◽  
Encryption Method

Data security and confidentiality is currently a very important issue and continues to grow. Several cases concerning data security are now a job that requires handling and security costs that are so large. To maintain the security and confidentiality of messages, data, or information so that no one can read or understand it, except for the rightful recipients, a data security system application with an encryption method using an algorithm is designed. The SHA-1 cryptographic hash function that takes input and produces a 160-bit hash value which is known as the message iteration is usually rendered as a 40-digit long hexadecimal number.

Construct Hash Function from Plaintext to C34Curves

2012 ◽  
Vol 35 (9) ◽  
pp. 1868 ◽  
Author(s):  
Wei YU ◽  
Kun-Peng WANG ◽  
Bao LI ◽  
Song TIAN
Keyword(s):  
Hash Function

Authentication protocol of mobile RFID based on Hash function

2013 ◽  
Vol 33 (5) ◽  
pp. 1350-1352
Author(s):  
Peng LIU ◽  
Changhong ZHANG ◽  
Qingyu OU
Keyword(s):  
Hash Function ◽  
Authentication Protocol ◽  
Mobile Rfid

Data Integrity

2017 ◽  
Author(s):  
Keith M. Martin
Keyword(s):  
Hash Function ◽  
Hash Functions ◽  
Data Integrity ◽  
Message Authentication ◽  
Authenticated Encryption ◽  
Authentication Codes ◽  
Basic Model ◽  
Function Design ◽  
Security Properties ◽  
Different Levels

This chapter discusses cryptographic mechanisms for providing data integrity. We begin by identifying different levels of data integrity that can be provided. We then look in detail at hash functions, explaining the different security properties that they have, as well as presenting several different applications of a hash function. We then look at hash function design and illustrate this by discussing the hash function SHA-3. Next, we discuss message authentication codes (MACs), presenting a basic model and discussing basic properties. We compare two different MAC constructions, CBC-MAC and HMAC. Finally, we consider different ways of using MACs together with encryption. We focus on authenticated encryption modes, and illustrate these by describing Galois Counter mode.

An Enhanced Two Stage MMSE Equalizer for Coded FBMC/OQAM Systems

2019 ◽  
Vol 10 (1) ◽  
pp. 69-82 ◽  
Author(s):  
Mohammad Rizk Assaf ◽  
Abdel-Nasser Assimi
Keyword(s):  
Error Propagation ◽  
Channel Model ◽  
Error Correcting Codes ◽  
Two Stage ◽  
Probability Of Error ◽  
Second Stage ◽  
Different Types ◽  
Mmse Equalizer ◽  
And Performance ◽  
Ici Cancellation

In this article, the authors investigate the enhanced two stage MMSE (TS-MMSE) equalizer in bit-interleaved coded FBMC/OQAM system which gives a tradeoff between complexity and performance, since error correcting codes limits error propagation, so this allows the equalizer to remove not only ICI but also ISI in the second stage. The proposed equalizer has shown less design complexity compared to the other MMSE equalizers. The obtained results show that the probability of error is improved where SNR gain reaches 2 dB measured at BER compared with ICI cancellation for different types of modulation schemes and ITU Vehicular B channel model. Some simulation results are provided to illustrate the effectiveness of the proposed equalizer.

A robust and high capacity data hiding method for JPEG compressed images with SVD-based block selection and advanced error correcting techniques

2021 ◽  
pp. 1-11
Author(s):  
Kusan Biswas
Keyword(s):  
Data Hiding ◽  
High Capacity ◽  
Error Correcting Codes ◽  
Human Vision ◽  
Data Embedding ◽  
Compressed Images ◽  
Matrix Encoding ◽  
Dct Coefficients ◽  
Capacity Data ◽  
Value Decomposition

In this paper, we propose a frequency domain data hiding method for the JPEG compressed images. The proposed method embeds data in the DCT coefficients of the selected 8 × 8 blocks. According to the theories of Human Visual Systems  (HVS), human vision is less sensitive to perturbation of pixel values in the uneven areas of the image. In this paper we propose a Singular Value Decomposition based image roughness measure (SVD-IRM) using which we select the coarse 8 × 8 blocks as data embedding destinations. Moreover, to make the embedded data more robust against re-compression attack and error due to transmission over noisy channels, we employ Turbo error correcting codes. The actual data embedding is done using a proposed variant of matrix encoding that is capable of embedding three bits by modifying only one bit in block of seven carrier features. We have carried out experiments to validate the performance and it is found that the proposed method achieves better payload capacity and visual quality and is more robust than some of the recent state-of-the-art methods proposed in the literature.

scholarly journals Algorithms for q-ary error-correcting codes with limited magnitude and feedback

2021 ◽  
Vol 344 (2) ◽  
pp. 112199
Author(s):  
Christian Deppe ◽  
Vladimir Lebedev
Keyword(s):  
Error Correcting Codes
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