The NIST defines encryption as the cryptographic transformation of data (called “plaintext”) into a form (called “ciphertext”) that conceals the data’s original meaning to prevent it from being known or used. The cybersecurity community understands the necessity to encrypt sensitive data resources to protect them from misuse or access by unauthorized users. End-to-end encryption to secure data throughout its lifecycle is therefore recommended to provide maximum security for valuable data assets.
Code encryption is another type of encryption that involves encrypting source code to prevent intellectual property (IP) theft and protect proprietary software from reverse engineering. However, most of the time, when the term “encryption” is used, data encryption is what comes to mind. As a result, many companies are unaware of the various types of encryption that can help protect their sensitive data.
In this article, we’ll describe code encryption, how it works as a code obfuscation technique, and how it fits into your data loss prevention (DLP) strategy.
What Is Code Encryption?
While data encryption is a well-known security measure, the term code encryption may not be so familiar. Code encryption uses similar techniques to those used in data encryption to encrypt the source code that powers applications, utilities, and software solutions. Encrypting makes the source code unreadable by humans and useless unless it is decrypted. Threat actors cannot steal the intellectual property contained in encrypted source code.
What Is Code Obfuscation?
Code encryption is one of many tactics employed in code obfuscation. Obfuscation attempts to make a program hard for human readers to understand. Programmers typically obfuscate code to protect intellectual property and prevent the reverse engineering of proprietary software. Valuable trade secrets on which software empires are created are protected with code obfuscation.
Code obfuscation provides an organization with several benefits including:
- The secrecy that protects code from malicious attacks and interested competitors;
- Built-in security that protects programs running in an untrusted environment;
- Efficiency when certain obfuscation techniques such as removing unused code are employed.
Code obfuscation typically involves a combination of several techniques designed to make the code unreadable to anyone attempting to understand how it works. Layering multiple methods is generally more effective than using a single technique.
The following are some of the methods commonly used in code obfuscation.
- String encryption: In this method, strings in the executable code are encrypted to make it difficult to search for specific code snippets. The strings are decrypted when they are needed for program execution.
- Transposition: This technique simply moves blocks of code within the program without affecting its functionality.
- Metadata removal: Removing the metadata such as comments that provide additional information to readers makes a program harder for a human to understand.
- Instruction transformation: This technique replaces instructions with more complex and less familiar alternative code structures that provide the same functionality.
- Inserting dummy code: Dummy code that does not affect performance can be added to a program to make it harder to read.
- Renaming: Variables and functions can be renamed using invisible characters that make it difficult for readers to determine program logic.
A drawback of employing encryption as a code obfuscation method is that decryption is required to run the program, which, in turn, can negatively impact performance. Other techniques do not require this additional processing and could be a more efficient choice, depending on the code that is being protected.
Code Encryption and Data Loss Prevention
A data loss prevention (DLP) solution identifies and classifies an organization’s data resources and provides enhanced protection for sensitive information. A DLP tool enforces a company’s data handling policy to ensure that information is not misused, lost, or subject to unauthorized access. The valuable information that needs to be secured often encompasses proprietary software and code that requires the same level of protection as customer health records or payment card information.
When developing an organization’s data handling policies, consideration should be given to the degree of protection that needs to be provided to the source code. Content and context-based classification should identify source code that may need to be encrypted or otherwise afforded special handling in specific usage scenarios. A viable DLP tool should seamlessly handle protecting a company’s source code as well as its sensitive financial and personal data.
A Modern Approach to Data Loss Prevention
Fortra DLP offers companies a modern DLP solution that provides full visibility into data assets that need to be protected. It’s a cloud-delivered and cross-platform solution that supports Windows, macOS, and Linux systems and endpoints. The tool gives companies the ability to protect their valuable information by automatically enforcing data handling policies.
Fortra DLP employs a no-compromise approach to data protection that keeps your valuable information safe. The solution provides flexible controls that can be configured to perform fine-grained actions when enforcing a data handling policy. Enforcement activities are determined by the classification of a data element, the context of the action being taken with the information, and the defined data policy handling controls.
Talk to Fortra today; schedule a free demo and see for yourself how a modern DLP tool can help your company protect its valuable data and source code.
