The FREE Cybersecurity Glossary by Thor Pedersen!

Data Emanation: The unintentional radiation or transmission of electrical signals from electronic equipment, such as a computer or a network device, which can potentially disclose sensitive information. Adversaries can intercept and decode these signals, also known as compromising emanations, to gain unauthorized access to the information, making mitigation techniques such as shielding, signal jamming, or the use of secure communication protocols essential.

Data Encryption Standard (DES): A symmetric-key algorithm for encrypting electronic data. Developed in the 1970s and once widely used, DES encrypts data in 64-bit blocks using a 56-bit key. It was eventually found to be vulnerable to brute-force attacks and has been largely replaced by more secure standards like the Advanced Encryption Standard (AES). However, DES was pivotal in the development and study of modern encryption techniques.

Data Execution Prevention (DEP): A security feature included in most modern operating systems. Its primary function is to help prevent damage to your system from viruses and other security threats by monitoring programs to ensure they use system memory safely. When DEP detects a program using memory incorrectly, it closes the program and notifies the user, thus helping to limit the impact of both malicious and unintentionally harmful software.

Data Farm: A large-scale data storage facility or a collection of servers that work together to store, manage, and process vast amounts of data. Similar to a server farm or data center, a data farm provides the infrastructure necessary to support big data applications, cloud computing services, and extensive databases. Data farms are designed for reliability, scalability, and high availability to ensure ongoing access to critical data resources and support the processing requirements of complex analytical tasks.

Data Flow: The movement or transfer of data through a system, from one component or process to another, often visualized in diagrams to represent the path that data takes through software, systems, or networks. Data flow analysis is crucial in designing systems for efficiency and understanding how data is processed and utilized.

Data Flow Control: Mechanisms that regulate the rate at which data is sent or received in a network to avoid overwhelming a recipient or communications channel. This ensures reliable data transfer and efficient use of network resources and can enhance overall system performance. Flow control can be implemented via software at the application, transport, or network layers and is integral to network protocols like TCP.