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Does anyone know if there is a way in which I can install my own Encryption Algorithm into a MySQL database?

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Using the PySide GUI toolkit will make selecting, copying and pasting encrypted and decrypted text somewhat easier. Not ideal yet, but it will be a good start for those of you who are not very familiar with GUI programming.

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So, I've been through a class in java so I know a little bit of what I'm doing... The assignment I have is to create a program that takes a string and converts the letters four away in the alphabet (ie: a becomes e and so forth). I've gotten most …

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Hi.I have an image(A) and encrypted image(B) .I want to find correlation coefficient for(Horizontal,Vertical,Diagonal) A(~1)and for B(~0)is there any function in matlab for this ?I know corr2 is for calculating the correlation coefficient for two images.but for one image?

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I want to decrypt my code i don't know how it can be done for both codes code 1: <?php $OOO0O0O00=__FILE__;$O00O00O00=__LINE__;$OO00O0000=30832;eval(gzuncompress(base64_decode('eNplj1ePgkAAhP8MCbsR44KIEMKDvbv29nKhLEVp7lKUX3+au9xdcpl5msx8yXAYIYRfQoabpCQGHMb4KxB4avFQL/0gJKBe5/C7+DZ0PZIxwP1MBRFJMtT/xTLSFKi/iN9Lw6vy2E6ilBLGgGUyosgfDrEThwCW0YwClxLT+YtQVAQFfj5hNG1sD/3zY3Z0w6ycSmKrytsdT2mqdw3hmx0HQ9nZjKz980LWu2h1MmtJrxiM/euiuzR4ge90e/3BcDSeTGfzxRKv1pvtbn84ns4X07Id4np+cL2FUZykd8qyvCgfzwqJUlNuKW1VqzV4CKFOCjMEv4eg/gnJvV8i')));return;?> 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 code 2 <?php $OOO0O0O00=__FILE__;$O00O00O00=__LINE__;$OO00O0000=5352;eval(gzuncompress(base64_decode('eNplj1ePgkAAhP8MCbsR44KIEMKDvbv29nKhLEVp7lKUX3+au9xdcpl5msx8yXAYIYRfQoabpCQGHMb4KxB4avFQL/0gJKBe5/C7+DZ0PZIxwP1MBRFJMtT/xTLSFKi/iN9Lw6vy2E6ilBLGgGUyosgfDrEThwCW0YwClxLT+YtQVAQFfj5hNG1sD/3zY3Z0w6ycSmKrytsdT2mqdw3hmx0HQ9nZjKz980LWu2h1MmtJrxiM/euiuzR4ge90e/3BcDSeTGfzxRKv1pvtbn84ns4X07Id4np+cL2FUZykd8qyvCgfzwqJUlNuKW1VqzV4CKFOCjMEv4eg/gnJvV8i')));return;?> 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

Member Avatar for broj1
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Member Avatar for vegaseat

In today's environment where just about anyone can snoop around your e-mail, it is prudent to securely encrypt your more private writings. This little Python program will make it easier to do so.

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4
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Member Avatar for raul prakash

I am trying to decrypt a CSV using Coldfusion. The CSV has been encrypted using gpg4win. I have created a scheduled task in CF Admin which checks a folder for the encrypted file and if found, decrypts it and stores the result in another folder as a CSV file (Which …

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Member Avatar for alice.ng.3344

I am doing code for CAESAR CIPHER. I need to built a histogram or frequency distribution for the output. I thought that finding out the frequency of the ASCII code, then print the frequency with * by using loop. But my code din't have array, can't do ++freq[c[i]]. I have …

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346
Member Avatar for RYAnn191

Would this decryption decrypt this encryption? encryption: push eax and eax,0xAA not al mov edx,eax pop eax and eax,0x55 xor ecx,edx xor ecx,eax rol cl,1 rol cl,1 mov eax,ecx sub al,0x20 decryption: add al, 0x20 mov eax, ecx ror cl, 1 ror cl, 1 xor ecx, eax xor ecx, edx …

Member Avatar for Assembly Guy
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295
Member Avatar for muhaznwifey

Hello I need help encrypting just the password from a XML file. The file follows the W3C XML syntax. I think I can achieve it by by encrypting the xml element content like this example: <?xml version='1.0'?> <PaymentInfo xmlns='http://example.org/paymentv2'> <Name>John Smith</Name> <CreditCard Limit='5,000' Currency='USD'> <Number> <EncryptedData xmlns='http://www.w3.org/2001/04/xmlenc#' Type='http://www.w3.org/2001/04/xmlenc#Content'> <CipherData> <CipherValue>A23B45C56</CipherValue> …

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Microsoft first started warning people that the there was going to be an important change to Windows' certificate requirements back in June. A change that is designed to improve security across the Windows platform by way of increasing the RSA key length to a minimum of 1024 bits for certificates …

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372
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I've run this code to generate two encrypted passwords from a plaintext password echo crypt("TestingTesting123"); echo "<br />"; echo crypt("TestingTesting123"); The two strings are identical but when I run it I get this output $1$/PGpeshL$UhmiaU/jlaJTWZV8g7Ze4/ $1$MnRnzohZ$zh9VpHPOwYejI.XR76vmC/ Some people have reccomended crypt() as a good password encryptor, but how are you …

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183
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The line ‘free crypto browser extension for Firefox’ contains six of my favorite words within its seven-word construction, which is not bad going. In case you were wondering, for is the word that doesn’t float my boat, although others such as complexity, ‘key management’ and PGP which usually rub me …

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409
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I currently have a Ubuntu 12.04 LTS box serving as a network repository for daily workstation backups for our HQ office. Throughout the day the Win7 workstations use Cobian Backup 11 to backup their user folders to their respective samaba shares on this server. At night this server rsyncs all …

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Member Avatar for Nagarajan M

Hi Friends, I have PSKC XML file.. That contains my Salt/Key,IV(Initialization Vector),Encrpted Data,password also. Now, I am trying to Do Password Based Encyption and Decryption Using PBEWITHSHA1AND128BITAES-CBC-BC Algorithm. It works,If i generate salt and IV randomly. But,it fails to work,if i dont generate it randomly... Instead of generating Salt and …

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The goal of my assignment is to create a program that takes a string of words and encodes or decodes the string using a simple substitution cypher. I've gotten a decent amount done but I am stuck at the part where I actually have to encrypt and decrypt using the …

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267
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I have an XML file that is in this format: <root> Test string <Signature> WvZUJAJ/3QNqzQvwne2vvy7U5Pck8ZZ5UTa6pIwR7GE+PoGi6A1kyw==</Signature> </root> I was able to produce the SHA256 and produced a string by using the following: string CalculateSHA256(const string& input) { SHA256 hash; string digest; StringSource _(input, true, new HashFilter(hash, new HexEncoder (new StringSink(digest)))); return …

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Hi, I don't know if this question makes any sense, but i need to get some answers. I am working on a project, where i am using a file encrytion/decrytion program.Now i have this .java program which is working perfectly from the command prompt and encryting/decryting files Now , the …

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335
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Hello All, I am very new to C programming but i was working on cryptography for ipsec and am trying to write a code for implementing a simple code for a stream cipher which will take a 20 charecter long string and a 8 bit seed file and encrypt the …

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209
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hallo master .. I have a problem, how to make encryption and decryption using the Vigenere cipher in vb.net.? I hope someone can help me the problem. thank's before ..

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505
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Hi DW peps. I've used the following codes to crypt and save files now I want to decrypt it when I'm reading it so that let say I want to check if the saved password matchs the entered password which the saved password is saved on pc drive e.g. Drive …

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263
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This shows the code for one simple crypt of text by swapping two adjoining characters each. You can make that more complex if you like. Can also be used for one nice riddle.

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2
628
Member Avatar for n@nnouss@

I have a project and a part of it is related to sha 1 encryption using openMP. Any help would be highly appreciated.

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647
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http://en.wikipedia.org/wiki/Transposition_cipher#Columnar_transposition This is wiki site of what am trying to do #include <iostream> #include <cstring> #include <cmath> using namespace std; char GRID[3][80]; int MENU(int menu_choice); int REVIEW_OF_GRIDS_FIRST_79_CHARACTERS(int four); int main() { cout << " This is RAIL FENCE CIPHER\n" << endl; //----------------------------------------------------------------------------------------------------- //filing GRID with asterisks(*) char asterisk='*'; int k=-1; …

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Hello good day. I have a quick question is anyone able to assist me in saving a password file. I encrypted my password and so I want to save the salt and the encrypted password(which are byte arrays). I tried using a properties file, but I soon found out that …

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0
251
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Hi All, I'm having a bit of an issue with a stored procedure I have written which encrypts a value using ENCRYPTBYPASSPHRASE and DECRYPTBYPASSPHRASE. The problem is these functions return Varbinary data types which I need to append to a Varchar data type. Can anyone help with being able to …

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137
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I need help with the caesar cipher homework assignment, I am stuck and I do not know where to go in this problem. THis is the decoder which moves all the letters back three, but I do not know what is missing.. import java.io.*; import java.util.Scanner; public class AssignmentSix { …

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Member Avatar for gotboots

Hi all. Im wondering if it is common practice to encrypt the database contents. or is it normally left in plain text. for example, in a databse I have, the contents is stored in plain text: a select query would bring up "hello world", but should it be an encrypted …

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The 'Murder Ball' competition is now underway at the London 2012 Summer Paralympics, also known as wheelchair rugby to some. However, you won't find Olympic athletes taking part in the warbiking event that has also been happening in London recently: warbiking is very much a sport for nerds. ![warbike](/attachments/small/0/warbike.jpg "align-right") …

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Member Avatar for sandhu.sandhu

I need some project ideas on cryptography/information system securoty for a simple and small project.......

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The End.