Integrity involves maintaining the consistency and trustworthiness of data over its entire life cycle. Data must not be changed in transit, and precautionary steps must be taken to ensure that data cannot be altered by unauthorized people.
Data integrity maintenance is an information security requirement. Integrity is a major IA component because users must be able to trust information. Untrusted data is devoid of integrity. Stored data must remain unchanged within an information system (IS), as well as during data transport. Events like storage erosion, error and intentional data or system damage can create data changes. For example, hackers may cause damage by infiltrating systems with malware, including Trojan horses, which overtake computer systems, as well as worms and viruses. An employee may create company damage through intentionally false data entry. Data integrity verification measures include checksums and the use of data comparisons.
It’s also a central focus of many data security programs. Achieved through a variety of data protection methods, including backup and replication, database integrity constraints, validation processes, and other systems and protocols, data integrity is critical yet manageable for organizations today.