Cipher-text classification with data mining

Khadivi, Pejman; Momtazpour, Marjan

doi:10.1109/ants.2010.5983530

Cited by 7 publications

(4 citation statements)

References 13 publications

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“…According to Khadivi, P and Momtazpour, [1], cryptography is essential building block for information and network security and needs advancement with increasing growth in internet. They used block cipher generation algorithm by information recording techniques.…”

Section: Exploration Of Other Approaches In Literaturementioning

confidence: 99%

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Various Approaches towards Cryptanalysis

Prajapat¹,

Thakur²

2015

IJCA

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Cryptanalysis is very important step for auditing and checking strength of any cryptosystem. Some of these cryptosystem ensures confidentiality and security of large information exchange from source to destination using symmetric key cryptography. The cryptanalyst investigates the strength and identifies the weakness of the key as well as enciphering algorithm. With the increase in key size, the time and effort required predicting the correct key increases. So, the Trend of increasing key size from 1 Byte to 8 Bytes to strengthen the cryptosystem and hence algorithm continues with compromise on the cost of time and computation. Automatic Variable Key (AVK) based symmetric key cryptosystem is an alternative to this style by fixing up key size and adding security level direction. Whenever any new cryptographic method is invented to replace existing vulnerable cryptographic method, it's deep analysis from all perspectives (Hacker / Cryptanalyst as well as User) is desirable and proper study and evaluation of its performance is must. New cryptic techniques may exploit benefits of advances in computational methods like ANN, GA, SI etc. These techniques for cryptanalysis are changing drastically to reduce cryptographic complexity. In this paper a detailed survey and direction of development work has been conducted. The work compares these new methods with state of art approaches and presents future scope and directions from the cryptic mining perspectives.

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Section: Exploration Of Other Approaches In Literaturementioning

confidence: 99%

“…Recently IOT is also gaining pace, here system and Internet is connected to the physical world via ubiquitous sensors". Following research questions are yet to be answered: (1). What are the scopes of AVK approaches of ensuring efficiency in IOT ?…”

Section: Avk Based Cryptosystem and Iotmentioning

confidence: 99%

Various Approaches towards Cryptanalysis

Prajapat¹,

Thakur²

2015

IJCA

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“…In cryptanalysis, the attacker tries to recover the original form of a secured message by analyzing hidden patterns in data or finding the secret key. One of the main ways to attack the cryptosystem is to analyze the hidden data patterns to reveal the main information of the ciphertext [1], [6], [7]. This is referred to as building a structured knowledge representation by extracting the features from the ciphertext normally using machine learning algorithms to process the information The associate editor coordinating the review of this manuscript and approving it for publication was Davide Patti .…”

Section: Introductionmentioning

confidence: 99%

A Deep Bidirectional LSTM-GRU Network Model for Automated Ciphertext Classification

et al. 2022

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Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) are a class of Recurrent Neural Networks (RNN) suitable for sequential data processing. Bidirectional LSTM (BLSTM) enables a better understanding of context by learning the future time steps in a bidirectional manner. Moreover, GRU deploys reset and update gates in the hidden layer, which is computationally more efficient than a conventional LSTM. This paper proposes an efficient network model based on deep BLSTM-GRU for ciphertext classification aiming to mark the category to which the ciphertext belongs. The proposed model performance was evaluated using well-known evaluation metrics on two publicly available datasets encrypted with various classical cipher methods and performance was compared against onedimensional convolutional neural network (1D-CNN) and various other deep learning-based approaches. The experimental results showed that the BLSTM-GRU cell unit network model achieved a high classification accuracy of up to 95.8%. To the best of our knowledge, this is the first time an RNN-based model has been applied for the ciphertext classification.INDEX TERMS Recurrent neural networks, bidirectional long short-term memory, gated recurrent unit, ciphertext classification, 1D-convolutional neural networks.

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“…In [1], a cryptosystem has been presented that records cipher generated using information recording techniques. Then, features from this information can be extracted to distinguish one cipher from others.…”

Section: Review Of Literaturementioning

confidence: 99%

Cryptic Mining in Light of Artificial Intelligence

Prajapat¹,

Thakur²,

Maheshwari³

et al. 2015

ijacsa

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Abstract-"The analysis of cryptic text is hard problem", and there is no fixed algorithm for generating plain-text from cipher text. Human brains do this intelligently. The intelligent cryptic analysis process needs learning algorithms, co-operative effort of cryptanalyst and mechanism of knowledge based inference engine. This information of knowledge base will be useful for mining data(plain-text, key or cipher text plain-text relationships), classification of cipher text based on enciphering algorithms, key length or any other desirable parameters, clustering of cipher text based on similarity and extracting association rules for identifying weaknesses of cryptic algorithms. This categorization will be useful for placing given cipher text into a specific category or solving difficult level of cipher textplain text conversion process. This paper elucidates cipher textplain text process first than utilizes it to create a framework for AI-enabled-Cryptanalysis system. The process demonstrated in this paper attempts to analyze captured cipher from scratch. The system design elements presented in the paper gives all hints and guidelines for development of AI enabled Cryptic analysis tool.

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Cipher-text classification with data mining

Cited by 7 publications

References 13 publications

Various Approaches towards Cryptanalysis

Various Approaches towards Cryptanalysis

A Deep Bidirectional LSTM-GRU Network Model for Automated Ciphertext Classification

Cryptic Mining in Light of Artificial Intelligence

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