Square attack on Mini-AES and Simplified AES using all variants of active nibble position

2016 ◽  
Author(s):  
Bara Hitapuru ◽  
Santi Indarjani
Keyword(s):  
Square Attack

Adaptive Square Attack: Fooling Autonomous Cars with Adversarial Traffic Signs

2020 ◽  
pp. 1-1
Author(s):  
Yujie Li ◽  
Xing Xu ◽  
Jinhui Xiao ◽  
Siyuan Li ◽  
Heng Tao Shen
Keyword(s):  
Traffic Signs ◽  
Autonomous Cars ◽  
Square Attack

scholarly journals Square Attack on 7-Round Kiasu-BC

2016 ◽  
pp. 500-517 ◽  
Author(s):  
Christoph Dobraunig ◽  
Maria Eichlseder ◽  
Florian Mendel
Keyword(s):  
Square Attack

scholarly journals Deteksi Steganografi Berbasis Least Significant Bit (LSB) Dengan Menggunakan Analisis Statistik

2013 ◽  
Vol 5 (2) ◽  
Author(s):  
Nur Rokhman ◽  
Juwita Maharanti
Keyword(s):  
Least Significant Bit ◽  
Stego Image ◽  
Chi Square ◽  
Square Attack

Abstrak— Pada  penelitian  ini dicoba dideteksi penyisipan pesan pada sebuah citra yang dilakukan dengan  teknik Least Significant Bit. Deteksi dilakukan dengan teknik Chi-square attack. Pada teknik ini dibandingkan distribusi frekuensi yang diharapkan secara teori dengan beberapa distribusi sampel yang diamati pada stego-image.Pada penelitian ini dilakukan steganalisis terhadap 10 macam citra yang disisipi dengan sebuah pesan yang berukuran 1kb, 2 kb dan 5 kb. Dicobakan juga 2 penyisipan berbeda, yakni dengan program Stegano dan StegoGraphyBMP.Dari percobaan yang dilakukan pada sepuluh stego-image dengan panjang pesan 1kb, 2kb, dan 5kb, Chi-square attack berhasil 80% mendeteksi pesan yang disisipkan pada sebuah citra dengan program Stegano dan berhasil 70% mendeteksi pesan yang disisipkan pada sebuah citra dengan program StegoGraphyBMP. Disamping itu diperoleh hasil bahwa ukuran pesan tidak berpengaruh pada proses steganalisis. Keywords—  Steganalisis, Chi-square.

New Steganography System Based on Huffman Coding and Fibonacci Decomposition

2018 ◽  
Vol 31 (1) ◽  
pp. 231
Author(s):  
Fadheela Sabri Abu-Almash
Keyword(s):  
Computer Security ◽  
Information Hiding ◽  
Random Distribution ◽  
High Capacity ◽  
Security System ◽  
Cover Image ◽  
Huffman Coding ◽  
Chi Square ◽  
Secret Code ◽  
Square Attack

   Hiding secret information in the image is a challenging and painstaking task in computer security and steganography system. Certainly, the absolute intricacy of attacks to security system makes it more attractive.in this research on steganography system involving information hiding,Huffman codding used to compress the secret code before embedding which provide high capacity and some security. Fibonacci decomposition used to represent the pixels in the cover image, which increase the robustness of the system. One byte used for mapping all the pixels properties. This makes the PSNR of the system higher due to random distribution of embedded bits. Finally, three kinds of evaluation are applied such as PSNR, chi-square attack, and HVS attack.            

New Square Attack on Zodiac

2010 ◽  
Vol 32 (11) ◽  
pp. 2790-2795
Author(s):  
Peng Zhang ◽  
Rui-lin Li ◽  
Chao Li
Keyword(s):  
Square Attack

On the Removal of Steganographic Content from Images

2016 ◽  
Vol 66 (6) ◽  
pp. 574 ◽  
Author(s):  
P.P. Amritha ◽  
M. Sethumadhavan ◽  
R. Krishnan
Keyword(s):  
Bit Error Rate ◽  
Transform Domain ◽  
Chi Square ◽  
First Order ◽  
Difference Image ◽  
Image Histogram ◽  
Acceptable Range ◽  
Transmission Of Information ◽  
Square Attack

Steganography is primarily used for the covert transmission of information even though the purpose can be legitimate or malicious. The primary purpose of this work is to build a firewall which will thwart this transmission. This will be achieved by radiometric and geometric operations. These operations will degrade the quality of cover image. However these can be restored to some extent by a deconvolution operation. The finally deconvolved image is subjected to steganalysis to verify the absence of stego content. Experimental results showed that PSNR and SSIM values are between 35 dB - 45 dB and 0.96, respectively which are above the acceptable range. Our method can suppress the stego content to large extent irrespective of embedding algorithm in spatial and transform domain. We verified by using RS steganalysis, difference image histogram and chi-square attack, that 95 per cent of the stego content embedded in the spatial domain was removed by our showering techniques. We also verified that 100 per cent of the stego content was removed in the transform domain with PSNR 30 dB - 45 dB and SSIM between 0.67-0.99. Percentage of stego removed in both domains was measured by using bit error rate and first order Markov feature.

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