Cryptic Mining in Light of Artificial Intelligence

(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 8, 2015 Cryptic Mining in Light of Artificial Intelligence Shaligram Prajapat Kajol Maheshwari Maulana Azad National Institute of Technology Bhopal, India International Institute of Professional Studies Devi Ahilya University, DAVV Indore, India Aditi Thakur Ramjeevan Singh Thakur International Institute of Professional Studies Devi Ahilya University, DAVV Indore, India Maulana Azad National Institute of Technology Bhopal, India 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. Keywords—Cipher text; Cryptic algorithm; Artificial Intelligence (AI) I. analysis; Encryption Fig. 1. Components of Cryptic Mining INTRODUCTION Originally data mining techniques are concerned with information extraction at application level or for business and commercial need of individual or organization. The term "Cryptic-Mining" is used for low level information domain. This knowledge area increases the security level of information and power of cryptic algorithms by helping cryptanalyst. In order to strengthen the cryptosystem, automated tools can be developed that intelligently exploits patterns among cipher-text, plain-text, key size, key life time and log of partially recovered plain-text-cipher text derived knowledge. Cryptic mining domain assumes that cipher texts present in the network or stored encrypted files/logs are not 100% random and exhibits some patterns. These patterns may be useful to exploit weakness using mining algorithms. Imagine the perspective of a cryptanalyst, who is interested to know about the type of enciphering algorithm. He is also interested in obtaining the plain text from encrypted text by exploiting patters or weakness. The obvious way to deal these intractable situations is mimic different theoretical and lengthy approaches by a human mind. Other alternative is to use AI and computational intelligence techniques that solves similar problems. In subsequent sections of this research work, a framework for AI enabled cryptic analysis system has been presented. This performs the cipher detection and successful conversion into plain-text in efficient way. This AI enabled system would help us to understand and analyze the various problems of cryptanalysis excluding strength and weaknesses of cryptic algorithms. This system would accept cipher texts generated from some algorithms and would try to extract meaningful information using some novel model or frameworks. Elucidation of cipher text-plain-text process has been shown on substitution cipher, such manner will resembles with the human way approach to solve the same problem. Later this concept would be generalized. The flow diagram for schema of AI-enabled Cryptosystem has been depicted in the fig.3.It accepts a given cipher text (Substitution cipher), and attempts to transform it back to corresponding plaintext using process similar to human experts. 62 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 8, 2015 system testing also has been discussed for using different examples to check functioning of each module. At the end future enhancements and new directions for further research work has been discussed in detail. II. BASIC TERMINALOGIES Cryptogram: A segment (word) of cipher text of length 1...n Fig. 2. Components of AI-Enabled cipher text to plain text conversion Cryptographic Algorithms: The procedure that transforms messages (or plain-text) into cryptograms (or cipher text) and vice-versa. Key Space: The set of possible keys K is called the keyspace. Substitution Cipher: It is the method of encoding by which units of plain-text are replaced with some other text. Intractable Problem: Theoretically a solvable problem that takes too long time, in practice, for their providing useful solutions (e.g. deciphering cryptograms). Different alphabets are used in order to better distinguish plaintext and ciphertext, respectively. In fact these alphabets are the same. A cryptosystem “S” can be defined by a 7-tuple: S = (M, C, Kd, Ke, F, E, D) where: M = Set of all possible plaintext m i.e. M= {m1, m2 .......}. Each message mi is the text to be encrypted (plaintext) and usually written in the lowercase alphabet: M = {a,b,c… x,y,z}. C = Set of all possible cipher text c i.e. C = {c1,c2.......}.Each encrypted message (cipher text) ci is usually written in uppercase alphabet: C = {A, B, C… X, Y, Z}. Kd= Set of all possible decryption key k i.e. Kd = { k1,k2,....} Ke=Set of all possible encryption key k‟ i.e. Kd= { k1 „,k2 „ ...} Fig. 3. Schematic flow of AI-enabled cipher analysis system In current typical cryptanalysis process, we limit ourselves to single substitution ciphers and we focus around “Transformation of cryptogram (cipher text) into message (plaintext) and vice-versa using single substitution cipher”. In order to develop a cipher analysis system that transforms the cipher text into plaintext following steps are important: (1) Implementation of Cryptographic algorithms for producing substitution ciphertext. (2) Formulating the process of cryptanalysis. (3) Development of framework of AI-Enabled-cipher analysis system. (4) Implementation of framework for substitution ciphertext. (5) Extending the idea for categorization of cipher text generated from various symmetric key based cryptic algorithm (such as AES, DES, RC4, Blowfish and two Fish) (6) Evaluation of space and time complexity of new system. In subsequent sections of this paper, we will describes the analysis of research topic using different examples and chalk down the system design based upon the proposed conceptual framework to be built. It includes various class diagrams and data flow diagrams describing the “dashboard”. Further, F: Kd Ke is a mapping from decryption key with corresponding encryption key. For Symmetric Cryptosystem Kd = Ke and F=I where Encryption and Decryption keys are same. E is the relation E: Ke (MC) that maps encrypting keys ke into encrypting relations eke: MC. Each eke must be total and invertible, but need not be a deterministic function or onto. D: K(CM) is the mapping that maps decrypting keys k into decrypting functions dk: CM. Each dk must be a deterministic function and onto. E and D are related in that Ke = F (k) D (k) =dk = eke-1 = E (ke)-1 m = D [k] (E [F (k)] (M)) Often eke are one to one and onto. III. REVIEW OF LITERATURE 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. Also, these features can be used to transform from future information into cipher-text. 63 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 8, 2015 In [2] analysis of cipher text was presented by combed algorithms simultaneously to transform cipher-text into plaintext information and addressed some problems like:{Block Length detection, stream detection, entropy analysis, recurrence analysis, dictionary based analysis, decision tree based problems}. In [3], pattern recognition based enciphering algorithms have been presented for the identification of patterns using different classification techniques like:{ SVM, Naive Bayesian , ANN, Instance based learning , Bagging , AdaBoostM1, Rotation Forest, and Decision Tree }. It can be noted that, these approaches requires improvement in accuracy with increase in number of encryption keys. In [4], some methods have been presented with application of tools like support vector machine to identify block-ciphers for different inputs. The first one works on cipher text and second method takes partially decrypted text derived from a cipher text as input. The SVM based method performs regression using hetero-association model to derive the partially decrypted text. Nuhn and Knight [5], worked towards automation of deciphering of ciphers. They have analyzed large number of encrypted messages found from libraries and archives, and trained by human effort only by a small and potentially interesting subset. Their work attempts to reduce human effort as well as error in decryption. Also they were interested to develop a distinguisher (first trained and then predict) to know which enciphering method has been used to generate a given cipher text. In [6], ANN based tool has been used for decoding of a ciphertext by a pattern classification problem. A survey of AI techniques for development of cipher analysis has been demonstrated in [7], here main objective was to investigate usage of advanced AI techniques in cryptography and they found that AI based security measures can be developed but their performance will depends on the data representation and problem formulation. In [8], Deciphering of messages from encrypted one using genetic algorithm has been presented. It searches the key space in encrypted text. They identified limitation that it didn‟t work with a two rotor problem in times comparable to those obtained using the iterative technique. Frequency analysis in cipher-text provides a significant direction to cryptanalyst. According to Ragheb Toemeh and colleague in [9], this frequency analysis technique is used for framing objective function of cryptography. They studied the applicability of other methods like genetic algorithms for searching the key space of encryption scheme and presented cryptanalysis of polyalphabetic by applying Genetic algorithm. Another survey based on parameters like queries, heuristics, erroneous information, group key exchange, synaptic depths has been conducted in [10], by Chakraborty and team . These parameters are suggested to improve the time complexity of algorithmic interception or decoding of the key during exchange. In [11], A mathematical black-box model was proposed by Alallayah, AbdElwahed and Alhamami that builds the foundation for the development of Neuro-Identifier for determining the key from any given plain text-Cipher text pair. Some system identification techniques were combined with adaptive system techniques were used for the creation of the model. All the above works and techniques follow in the direction of established long-fixed key sized algorithms. These algorithms rely on the ciphers would be secure enough if they are generated with keys of longer size. But in literature there are ciphers being generated through keys of short-fixed-length keys[12,13] varying with session to sessions. Ciphers generated through these AVK mechanism [14,15] are to be converted back into plain text. IV. EXPERIMENTAL DESIGN For designing experimental setup it is necessary to first understand the complete mechanism of how the cipher analysis process works? How cryptanalysis applies rules of English grammar? For this various grammar rules will be applied on the given cryptogram at different stages for each replacement which will aid in obtaining the desired plain-text. Given following examples will be used to develop design model. Let us assume that cryptanalyst has captured following cryptogram: “q azws dssc kas dxznn dasnn”. Now cryptanalyst may process according to following steps: 1) To develop a model we take a hypothesis of solving a plain-text [Table 1]with one initial seed point .[Hint : wv] 2) Secondly the sentence is searched for smallest word (word with least number of letters), which in this case is the one-letter word ‘q’. This word is replaced by plain letter ‘A’ as it has the highest priority for one-letter word according to the English grammar. 3) Next the first occurrence of double letter is searched in the sentence which is ‘ss’. As it is in the middle of consonants, therefore it has to be a vowel according to English grammar and ‘s’ is replaced by plain letter ‘E’ which has highest priority in this case. 4) Further the next smallest word is searched which is ‘kea’. With this pattern the word with highest priority is ‘THE’. Hence ‘k’ and ‘an’ are replaced by ‘T’ and ‘H’ respectively. 5) Now the word having the maximum number of letters replaced is ‘HzVE’ which can possibly be ‘HIVE’(‘have’ cannot be taken as ‘A’ is already used). Therefore ‘z’ is replaced with plain letter ‘I’. 6) Next word ‘dEEc’ can be ‘SEEN’,’BEEN’,’FEEL’ etc. This word will be a verb, so we replace this word with ‘SEEN’. 7) Now our sentence includes ‘A HIVE SEEN’, which is not possible as a hive cannot see. This states that we have possibly made some mistake with our assumptions before. Backtracking to the first assumption which was qa and 64 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 8, 2015 changing qi to correct the sentence. Also the assumption zi has to be changed to za. 8) Further in the next word ‘SxAnn’, the double letter ‘nn’ will be a consonant according to the English language. Therefore ‘n’ is replaced by plain letter ‘L’ which has the highest possibility in this case. 9) Now ‘SxALL’ can possibly be ‘SMALL’ or ‘SHALL’. But observing the sentence structure it can be a noun or an adjective so ‘SMALL’ is used. Hence ‘x’ is replaced by plain letter ‘M’. 10) Finally we obtain the plaintext from the cryptogram given. The above process can be summarized in Table1: TABLE I. CRYPTANALYSIS STEPS WITH KNOWLEDGE SOURCE USED INTERFERENCE V. EXPERIMENTAL FINDING It can be observed that a central place (like Dashboard) is needed to apply sources of knowledge. It would be useful to align with the assumptions made and to reason the consequences. Knowledgebase (a Data structure) KS will maintain log of many different sources of knowledge such as: Knowledge about grammar, spelling and vowels. At some point of time, specialization process (moving down) is followed (General to specific) during the replace of cryptogram with n=3 and ending with “e”. (for THE ) and at some other points, Generalization process i.e. moving Up process is followed (from Specific to General) during the processing of cryptogram with n=4 and having pattern “?ee?”Which may be from {deer, beer, seen} but at the third position the word must be a verb instead of a noun, so “seen” should be final choice. VI. Sno 1. 2 3 4 5 6 7 8 Cryptogram q azws dssc kas dxznn dasnn q azVs dssc kas dxznn dasnn A azVs dssc kas dxznn dasnn A azVE dEEc kaE dxznn daEnn A HzVE dEEc THE dxznn dHEnn A HIVE dEEc THE dxInn dHEnn Inference Knowledge Source wv qa Reference/ Remark using hint /KS=direct substitution KS=small word ( n-gram :n=1) se, KS=double letter kt, ah KS=small word (n-gram: n=3) In order to build a system flow of information from one component of system to other is depicted by fig.4, fig.5 and fig.6. Fig. 4. Context flow diagram zi pattern matching ( valid small word dictionary) Dictionary ds, cn pattern matching ,valid smallworld dictionary, sentence structure (position of word) KS=Patterns Sentence structure , KS=IsSolved Backtracking A HIVE SEEN THE SxInn qi, za SHEnn I HAVE SEEN THE SxAnn nl SHEnn FLOW DIAGRAM KS=Double letter, KS=word structure 9 I HAVE SEEN THE SxALL xm SHELL KS=word structure, pattern matching,KS=Sentence structures 10 I HAVE SEEN THE SMALL SHELL KS=IsSolved Fig. 5. First level data flow diagram 65 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 8, 2015 function 3.-def transposition( ) This function displaces the cipher letter with plain letter according to the displacement in the plain letter with its corresponding cipher letter (key) in the assumption (dictionary). If the words replaced don‟t have correct spelling then the transposition is reverted back and the plain letters are again replaced with corresponding cipher letters which were added to assumption dictionary. function 4.-def backtrack(word) If no pattern match is found for a word then that word is passed as the argument to backtrack, it will replace the plain letter with their corresponding original cipher letter as the #assumptions made before was not correct function 5.-def trans_status( ) After doing transposition it checks transposition made was correct or not. whether the function 6.-def revert_trans( ) If the transposition made was correct then it displays the final sentence otherwise revert all the #changes made during transposition process Fig. 6. Second level data flow diagram function 7.-def pat_rep(lst, fil, cnt) pat_rep function replaces the words from list with suitable word from file according to condition. It has three arguments: lst: list of specific words(i.e 2-letter, 3-letter etc) if the sentence containing cipher. fil: text file of containing 2-letter-letter etc plain-letter words corresponding to list. cnt: counter to mention the position in the file function 8.-def pattern(word, fil, cnt) If the word contains one or more plain letter pattern function matches the word with every word in file and replaces if a pattern is matched. It has 3 arguments: word: word from sentence containing a capital letter fil: corresponding file(for ex: 4_word file for 4-letter word) cnt: counter that mentions position in the file Fig. 7. 2-Level Data flow diagram for process 2.0 VII. MODULAR STRUCTURE For implementation of cryptosystem and cryptanalysis of substitution different cipher function structures are described below: function1-def spell_check(word) This module checks the spelling of the word and returns true if the spelling is correct. function 2-def replacefunc(word, file_word) This module replaces the word with a word from file and adds the entry in assumption(dictionary containing cipher Letter-plain, Letter pair) function 9.-def double_letter(word) This function checks if a word (input) contains any double letter, if yes it replaces the double letter cipher with appropriate plain letter according to its position (i.e. if in middle it will be a vowel and if end it will be a consonant according to English grammar rules) function 10.-def one_letter( ) If the sentence contains one-letter-word in cipher then this function will replace that cipher with the possible plain oneletter-word and will make entry according to the assumption. function11-def find_key(value) This function finds the corresponding cipher(key) letter of the plain letter(value) given as argument from the dictionary “assumption” 66 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 8, 2015 VIII. TEST CASE DEVELOPMENT Test cases are developed to validate and verify the working of system in two situations. Case-1 and Case-2. Case-2: For testing english grammar Input Sentence supplied by user: sent = “dwer er ed” Case-1: For testing transposition Let sentence given by user: sent_1 = “k co c iktn” TABLE II. S.no Module name 1. Enter valid cipher sentence STEPS FOLLOWED FOR CASE 1 Test Cases Result Response Check chars of sent Returns true if the sentence contains only alphabets otherwise false OK Replace one-letter cipher word with the plain word chosen from the file containing one-letter words OK sent=”I Ao A iItn” OK 2. one_letter() 3. one_letter() sent=”k co c iktn” action performed on sent Finds the difference between the replaced cipher letter and its corresponding plain letter and replace remaining cipher letter with OK plain letter with same difference 4. transposition() 5. transposition() sent = “I Ao A iItn” action performed on sent 6. spell_check (word) spell_check (“I”) spell_check 6.2. (“AM”) spell_check 6.3. (“A”) spell_check 6.4. (“GIRL”) 6.1 correct spelled word correct spelled word correct spelled word correct spelled word 7. trans_status() 8. trans_status() sent=”I AM A GIRL” all words are correct spelled TABLE III. S.no Module name 1. main() 2. pat_rep(lst,fil,cnt) Test Cases 7. transposition() 12. replacefunc(er,OF) Returns true OK Returns true OK Returns true OK Returns true OK Returns false if spelling of any of the word in sent is wrong else true OK returns true OK Replace each chars of word with the corresponding chars of file_word and made the entry of pair(cipherletter:plainletter) in the dictionary „assumption‟ Search the word from list according to the pattern formed Reverts back the previous assumptions made if pattern is not found for word i.e replace the plain text with their original ciphertext in sent Checks the grammar of sentence and returns true if correct else false 6. check_sent(sent) pat_rep(two_w,tw,cnt2) two_w = [er,ed] OK Response OK Search the word from list from file according to conditions met OK 5. backtrack(word) 11. Returns true if correct spelling else false Result Calls all functions according to condition 4. pattern(word,fil,cnt) 9. main() started 10. sent = “dwer er ed” OK STEPS FOLLOWED FOR CASE 2 3. replacefunc(word,file_word) 8. Enter valid cipher sentence sent = “I AM A GIRL” Check each characters of sent check for smallest word Actions performed on the words of list two_w,hence on sent Replacement done on sent OK OK OK OK Finds the difference between the replaced cipher letter and its corresponding plain letter and replace remaining cipher letter with plain letter with same difference OK Returns true if the sentence contains only alphabets otherwise false OK Two-letter word found OK Replaces „er‟ with „OF‟(first word in fil tw) sent = “dwOF OF Od” OK Replaces „er‟ with „OF‟(first word in fil tw) sent = “dwOF OF Od” OK 67 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 8, 2015 assumption={„e‟:‟O‟ , ‟r‟:‟F‟} pattern(Od,etw,e2cnt) 13. etw: file containing 2-letter words at ending position of sent Search matched word 14. backtrack(Od) Replaced all the plain letter i.e. F and O with corresponding Action performed on sent and cipher letter from assumption and calls main() again assumption 15. main() called 16. sent = “dwer er ed” pat_rep(two_w,tw, cnt2) 16.1 two_w = [er, ed] Check for smallest word 16.1.1 replacefunc(er,TO) Replacement done on sent pattern(Td,etw,e2cnt) 16.1.2 etw: file containing 2-letter words at ending position of sent Search matched word 16.1.2.1 backtrack(Td) 17. main() called 18.1 sent = “dwer er ed” pat_rep(two_w,tw, cnt2) 19. two_w = [er, ed] No pattern found for pattern=‟O.‟ OK OK Two-letter word found OK Start search for the word in “tw” according to condition after the OK word last searched Replaces „er‟ with „TO‟ sent = “dwOF TO Od” OK assumption={„e‟:‟T‟ , ‟r‟:‟O‟} No pattern found for pattern=‟T.‟ OK Replaced all the plain letter i.e. T and O with corresponding Action performed on sent and cipher letter from assumption and calls main() again assumption OK Check for smallest word OK 19.1.1 replacefunc(er,IS) Replacement done on sent pattern(Id,etw,e2cnt) 19.1.2 etw: file containing 2-letter words at ending position of sent Search matched word Two-letter word found Start search for the word in “tw” according to condition after the word last searched Replaces „er‟ with „IS‟ sent = “dwIS IS Id” assumption={„e‟:‟I‟ , ‟r‟:‟S‟} Match found for pattern=‟I.‟ match = “IT” sent = “TwIS IS IT” assumption={„e‟:‟I‟ , ‟r‟:‟S‟, „d‟:T} OK OK OK 20 return to main() Check difference between Difference is not same, therefore returns False cipher letter and plain letter Check for word having length Four-letter word found greater than two 21 transposition() 22 sent = “TwIS IS IT” 22.1 pat_rep(four_w,fw, cnt4) four_w = [TwIS] pattern(TwIS,sfw,s4cnt) 22.2 sfw: file containing 4-letter words at starting position of sent Search matched word OK As word contains plain letter so calls pattern() OK Match found for pattern=‟T.IS‟ match = “THIS” sent = “THIS IS IT” assumption={„e‟:‟I‟ , ‟r‟:‟S‟, „d‟:‟T‟, „w‟:‟H‟} OK sent = “THIS IS IT” and assumption={„e‟:‟I‟ , ‟r‟:‟S‟, „d‟:‟T‟, „w‟:‟H‟} Check grammar of sent 23 check_sent(sent) IX. Returns true X. CONCLUSION This paper is an attempt to demonstrate the demonstrate cipher text -plain text conversion process for analysis of cryptic text. AI has been used to get the feasible solution of hard problem. By generalizing the conversion process system for obtaining plain-text from input cipher text is the central objective. The developed system would analyze and learn for pruning. This paper has demonstrated cipher text-plain text process completely and created a framework for AI-enabledCryptanalysis system, Data Flow Diagrams and appropriate test cases. This schema and plan would be suitable for development of AI enabled Cryptic analysis tool and in turn they will evaluate strength of any cryptosystem. FUTURE ENHANCEMENT AI-based-crypto system works correctly for the basic cipher-text to plain-text conversion process. To extend this further to fulfill various requirements following enhancements are suggested. 1) Current work can be extended to incorporate ciphers other than substitution and transposition cipher. That is, present system response is fine for transposition cipher and substitution cipher, but cipher types are more than two. This will require testing with different algorithm, method and cipher text. So that extended version is fit and deciphers it accordingly. 68 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 8, 2015 2) Incorporating plain-text of multiple languages in the process is also desirable. That is, current elucidation demonstrated in this work deciphers and outputs result in English. Maximum number of ciphers gives English plain-text on decryption. But over the communication channel languages local, non-English languages are also exchanged. For decryption of cipher text yielding other language plain text, the grammar rules of that particular language has to be applied. 3) Extension of character set with adding special characters and symbols will make the current system more flexible. The reason behind this is, day-by-day increasing amount of data transferred, and the need to encrypt it in a more complex way is mandatory for securing information from unauthorized users. Hence special characters and numbers are used to generate a more complex cipher patterns. Deciphering these ciphers using algorithm with condition for checking these symbols together with the English alphabets will be necessary. 4) Extension for n-gram (n>4) will increase the power of cipher analysis. That is checking cipher words with having length more than 4 and words which are not present in any knowledge source, needs to be worked out. Currently the Knowledge source, include files having upto 4-letter words. 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