Data Integrity in Cryptography

Introduction: – Till now you have learned about the symmetric key encryption and block ciphers. But this chapter deals with various cryptographic techniques designed for taking other security measures. Here, you will be focusing on integrity of data and various cryptographic tools and techniques implemented for achieving data integrity.

What is Integrity?
The very fundamental part of data security is its integrity. So data integrity can be defined as the consistency and accuracy of data that is stored in the server or warehouse or in cloud. This term is also used as a replacement for data quality and originality. It comprises of various data characteristics such as correct data, proper business rules, relations among data, dates and lineage.

Protecting data integrity means, protecting data or classified information stored in some server or cloud from being modified by unauthorised activists or malicious users. Let us take a simple scenario of a bank, where you keep money in a bank. After some days you heard that the server of the bank got compromised breaching the integrity of financial data. So what the malicious cyber criminal do is change (reduce) the financial value from each and every account
and somehow managed to transfer it to other account. This is one serious example of data integrity. The data is there but it is not the actual one that the bank stored before the breach occurred.

Threats of Integrity of Data: –
As you are communicating with someone and dealing with some specific values which means a lot, you need to make sure the data exchanged from sender to receiver must have the assurance that they are intact from the intended sender or receiver and are not modified (in case of MITM attack). There are two kinds of integrity threats that can cause to data. These are –

  • Active and
  • Passive

 

Active Threats:
In this case of attacks and data integrity threats, the important data get compromised and the malicious or unauthorised user changes the data with malicious intent. If data is without a digest technique, the modification can become undetectable. If it is a high level threat, even a digest technique cannot help prevent and data can be manipulated deriving new digest with the existing one. These types of attacks can be reduced with the use of Hash
functions.

 

Passive threats:
These types of threats may arise due to accidental modification in data from insiders or from auditors. Also the change in data may arise due to noise in communication medium. These types of data integrity can be reduced by taking adequate measures such as using Error correcting codes, or CRC (Cyclic Redundancy Check) techniques. Here various mathematical calculations are done to check for data being kept genuine or there is any appending of
unwanted data.

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