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Unsupervised Cipher Cracking Using Discrete GANs [article]

Aidan N. Gomez, Sicong Huang, Ivan Zhang, Bryan M. Li, Muhammad Osama, Lukasz Kaiser
2018 arXiv   pre-print
We then prove that the technique used in CipherGAN avoids the common problem of uninformative discrimination associated with GANs applied to discrete data.  ...  We demonstrate that CipherGAN is capable of cracking language data enciphered using shift and Vigenere ciphers to a high degree of fidelity and for vocabularies much larger than previously achieved.  ...  DISCRETE GANS Applying GANs to discrete data generation is still an open research problem that has seen great interest and development.  ... 
arXiv:1801.04883v1 fatcat:shzhzs5wbveufpjyzpeg5wr6yi

Steganography GAN: Cracking Steganography with Cycle Generative Adversarial Networks [article]

Nibraas Khan, Ruj Haan, George Boktor, Michael McComas, Ramin Daneshi
2020 arXiv   pre-print
In this paper, we succeed in cracking the Least Significant Bit (LSB) steganography algorithm using Cycle Generative Adversarial Networks (CycleGANs) and Bayesian Optimization and compare the use of CycleGANs  ...  Ever since the creation of covert communication methods, steps have been taken to crack cryptography and steganography algorithms.  ...  Unlike Cipher GANs, which aim to crack discretized data in the form of text and cipher sequences, we aim to crack embedded images by learning the steganographic alogrithm with which they're encoded [11  ... 
arXiv:2006.04008v1 fatcat:6j6havzlzjeu3fxu36ngiwn4iy

Adversarial Text Generation via Feature-Mover's Distance [article]

Liqun Chen, Shuyang Dai, Chenyang Tao, Dinghan Shen, Zhe Gan, Haichao Zhang, Yizhe Zhang, Lawrence Carin
2020 arXiv   pre-print
cracking.  ...  Instead of using the standard GAN objective, we propose to improve text-generation GAN via a novel approach inspired by optimal transport.  ...  Unsupervised decipher Our model can also be used to tackle the task of unsupervised cipher cracking by using the framework of CycleGAN [62] .  ... 
arXiv:1809.06297v2 fatcat:cmmks4mif5dpdkxzt4m6chqlry

Unsupervised Text Style Transfer using Language Models as Discriminators [article]

Zichao Yang, Zhiting Hu, Chris Dyer, Eric P. Xing, Taylor Berg-Kirkpatrick
2019 arXiv   pre-print
Binary classifiers are often employed as discriminators in GAN-based unsupervised style transfer systems to ensure that transferred sentences are similar to sentences in the target domain.  ...  By using a continuous approximation of discrete sampling under the generator, our model can be trained using back-propagation in an end- to-end fashion.  ...  Gomez et al. (2018) use GAN-based approach to decipher shift ciphers.  ... 
arXiv:1805.11749v3 fatcat:3xr3i5zunvgsrebq73xcdwdvku

How Generative Adversarial Networks and Their Variants Work

Yongjun Hong, Uiwon Hwang, Jaeyoon Yoo, Sungroh Yoon
2019 ACM Computing Surveys  
In this paper, we aim to discuss the details of GAN for those readers who are familiar with, but do not comprehend GAN deeply or who wish to view GAN from various perspectives.  ...  Finally, we enumerate the GAN variants that are applied to various tasks and other fields for those who are interested in exploiting GAN for their research.  ...  In addition, new types of GANs have been proposed for new applications such as cipher cracking [34] and object tracking [114] .  ... 
doi:10.1145/3301282 fatcat:z2xe6jdh5nd2dmovkes3rav3ke

A Survey on Generative Adversarial Networks: Variants, Applications, and Training [article]

Abdul Jabbar, Xi Li, Bourahla Omar
2020 arXiv   pre-print
The Generative Models have gained considerable attention in the field of unsupervised learning via a new and practical framework called Generative Adversarial Networks (GAN) due to its outstanding data  ...  We survey, (I) the original GAN model and its modified classical versions, (II) detail analysis of various GAN applications in different domains, (III) detail study about the various GAN training obstacles  ...  [180] , mobile user profiling [181] , data augmentation [182, 183] , heterogeneous information networks [184] , privacy-preserving [185 -188] , social robot [189] , cipher cracking [190] , auxiliary  ... 
arXiv:2006.05132v1 fatcat:gyjezuh5sfdilkp43ydsea5cwa

Image Steganography: A Review of the Recent Advances

Nandhini Subramanian, Omar Elharrouss, Somaya Al-Maadeed, Ahmed Bouridane
2021 IEEE Access  
Since the model is a unsupervised generative model, the authors have named the model Self-supervised Steganographic GAN (SSteGAN).  ...  At the receiving end, the cipher text is converted into plain text using a decryption key.  ... 
doi:10.1109/access.2021.3053998 fatcat:obezfqxgivg43mugsmmcxdceri

Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
for Unsupervised Few-Shot Object Recognition DAY 1 -Jan 12, 2021 Hung, Shih-Kai; Gan, John Q. 996 Augmentation of Small Training Data Using GANs for Enhancing the Performance of Image Classification  ...  Evaluation of Finger Veins Using the CNN Triplet Loss Bonettini, Nicolo; Bestagini, Paolo; Milani, Simone; Tubaro, Stefano 1497 On the use of Benford's law to detect GAN-generated images DAY 2 -Jan 13  ... 
doi:10.1109/icpr48806.2021.9412725 fatcat:3vge2tpd2zf7jcv5btcixnaikm

Exploring Artificial Neural Networks in Cryptography – A Deep Insight

Manikandan N
2020 International Journal of Emerging Trends in Engineering Research  
This plethora of information regarding how each neural network was used in different types of cryptosystems is mainly contributed to future researchers to aid their novel works in this discipline.  ...  Tan Li et al [80] proposed this method first in his work using Convolutional Neural Network (CNN) with unsupervised learning from a stack of auto-encoders.  ...  In [69] authors proved that it is difficult to crack a key-exchange protocol that uses TPM synchronization [63] . Table 4 lists the contributions of neural key exchange protocols.  ... 
doi:10.30534/ijeter/2020/146872020 fatcat:wqtgwcxwgbbt3pr2tpinq2goiu


Dr. Agusthiyar . R
2022 Zenodo  
Initially, the advancements were in the form of mono-alphabetic ciphers, polyalphabetic substitution ciphers, transposition ciphers and block ciphers (Aung et al., 2019).  ...  Hybrid Cipher Algorithm.  ...  [2] has talked about how a Wikipedia-based Wikifier can be used to train any corpus to obtain an entitymention graph using page rank values.  ... 
doi:10.5281/zenodo.7024997 fatcat:2v4vxqlfxbgn3dl43zr4y2d26y

Machine and Deep Learning for IoT Security and Privacy: Applications, Challenges, and Future Directions

Subrato Bharati, Prajoy Podder, Jinbo Xiong
2022 Security and Communication Networks  
Unsupervised ML.  ...  Unsupervised DL.  ... 
doi:10.1155/2022/8951961 fatcat:n4rb7rtgrjbybmen66oyrzkhle

Deep Neural Mobile Networking [article]

Chaoyun Zhang
2020 arXiv   pre-print
The potential of a range of unsupervised deep learning tools including AE, RBM and GAN remains to be further explored.  ...  Beyond protecting networks from attacks, deep learning can also be used for attack purposes, bringing huge potential to steal or crack user passwords or information.  ... 
arXiv:2011.05267v1 fatcat:yz2zp5hplzfy7h5kptmho7mbhe

Towards Training AI Agents with All Types of Experiences: A Standardized ML Formalism

Zhiting Hu
In Part II, we show the formalism is a natural framework for making use of arbitrary available experiences to learn models of i [...]  ...  ., supervised, unsupervised, active, reinforcement, adversarial learning), models, optimization techniques, not mentioning countless approximation heuristics and tuning tricks, plus ombinations of all  ...  Sentiment Manipulation We have demonstrated that the language model can successfully crack word substitution cipher. However, the change of substitution cipher is limited to a one-to-one mapping.  ... 
doi:10.1184/r1/19629837.v1 fatcat:xwjexr3ggrbdtlvszl3glwheie

Security and privacy for 6G: A survey on prospective technologies and challenges [article]

Van-Linh Nguyen, Po-Ching Lin, Bo-Chao Cheng, Ren-Hung Hwang, Ying-Dar Lin
2021 arXiv   pre-print
Energy consumption of AES and related cipher suites is least in all cryptographic algorithms.  ...  AI cannot help to explain why attacks occur or the causal relationships of discrete events to potential intrusions.  ... 
arXiv:2108.11861v1 fatcat:o7fgtm4tobfk5knltojut6xpyi

Privacy Management of Multi User Environment in Online Social Networks (OSNs)

P. Amrutha
2013 IOSR Journal of Computer Engineering  
For correct validation, discretization square is used which is the tolerance area around the original click point. The user should click on the discretization area.  ...  Instead, we use it to provide strong guarantees for the encrypted content and the log files, such as protection against chosen plaintext and cipher text attacks.  ...  Accountability [2] is the obligation to act as a responsible for preserving the personal information of others and appropriate use of that information beyond mere legal requirements, and to be accountable  ... 
doi:10.9790/0661-1320107 fatcat:rdpsdcqelbbzvkg5rm4og4tzba
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