In general words, entropy is referred to as the measurement of particular data in digital values. Similar to this, the term **File Entropy **is the representation of data sets in a specific file.

That is, the phrase **File Entropy **is used to measure the amount of data that is present in a selected file. For example, if you have some files and desire to calculate the entropy value for that, then it will be very simple by accessing the methods of **File Entropy **and its calculation process.

If you are unfamiliar with what exactly means the entropy exactly and how to calculate an entropy value for particular files, just refer to the details that are present below. The following details will provide the complete info about what is entropy and how it is helpful to calculate the exact value of given data.

**How it is work**

In simple and exact terms, entropy is defined as the measurement of unpredictable value or informative content. This definition may include different changes according to the sector or platform that uses the feature of entropy value. But, all types of measurement that are related to entropy calculation include only digital format information. Usually, the **File Entropy **is denoted by using different formulas depending on the form of selected data. The equation which is used by Shannon is the simple format to calculate the entropy value of data sets in a particular file. This equation includes the measurement of random value, which will be calculated as a result by using the number of given data sets.

The result value of the Shannon equation is generally represented between the values of zero and eight. So, the entropy value of a particular file is represented by using the digital values of 0 to 8. The result is either near to 0 or 8 as well as in-between these two numeric values. The final result will be concluded on the basis of value which is derived from the given data sets. For example, if the measured value is closer to zero, then it represents that the value of the given data set is a non-random or orderly format. Otherwise, if the value is closer to eight, then the given set is a random or un-orderly format. This is the basic concept of **File Entropy **calculation, which is related to the Shannon equation.

**Uses of entropy measurement**

The feature of entropy calculation is applicable for different purposes. But, it is mainly applicable for finding the values of encrypted data and compressed files. Generally, the random data is not similar to the normal kind of user data. For this purpose, the users apply the feature of **File Entropy **to calculate the value of given data that is represented by the format of non-uniform. Due to the inconvenient format of random data when compared to typical user data, the executable files are generally encrypted with the feature of a synchronized decryption algorithm. So, the users can access the data volumes in an easy way and can find the entropy values for those files efficiently.

**File Entropy and malware research**

**File Entropy** is also used in the field of malware protection, in the process of malware analysis as there are all kinds of security-related tools that you check on the file to extract all kinds of information from the file, to determine if the file is malware or legit file, and if it is a malware this can be useful on the malware file entropy can be a useful method to quickly check if the malware file had been packed with one of the packed software it is also a good method to check if the file encrypted by one of the encryption algorithms.

Don’t forget to check our pe header tool and our Windows File Analyzer article.

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