Data integrity is the maintenance of, and the assurance of, data accuracy and consistency over its entire life-cycle. It is a critical aspect to the design, implementation, and usage of any system that stores, processes, or retrieves data. The term is broad in scope and may have widely different meanings depending on the specific context even under the same general umbrella of computing. It is at times used as a proxy term for data quality, while data validation is a prerequisite for data integrity.
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👉 Data integrity in the context of Cryptography
Cryptography, or cryptology (from Ancient Greek: κρυπτός, romanized: kryptós "hidden, secret"; and γράφειν graphein, "to write", or -λογία -logia, "study", respectively), is the practice and study of techniques for secure communication in the presence of adversarial behavior. More generally, cryptography is about constructing and analyzing protocols that prevent third parties or the public from reading private messages. Modern cryptography exists at the intersection of the disciplines of mathematics, computer science, information security, electrical engineering, digital signal processing, physics, and others. Core concepts related to information security (data confidentiality, data integrity, authentication and non-repudiation) are also central to cryptography. Practical applications of cryptography include electronic commerce, chip-based payment cards, digital currencies, computer passwords and military communications.
Cryptography prior to the modern age was effectively synonymous with encryption, converting readable information (plaintext) to unintelligible nonsense text (ciphertext), which can only be read by reversing the process (decryption). The sender of an encrypted (coded) message shares the decryption (decoding) technique only with the intended recipients to preclude access from adversaries. The cryptography literature often uses the names "Alice" (or "A") for the sender, "Bob" (or "B") for the intended recipient, and "Eve" (or "E") for the eavesdropping adversary. Since the development of rotor cipher machines in World War I and the advent of computers in World War II, cryptography methods have become increasingly complex and their applications more varied.
In this Dossier
- ⭐ Core Definition: Data integrity
- 👉 Data integrity in the context of Cryptography
- Data integrity in the context of Security vulnerabilities
- Data integrity in the context of Human error
- Data integrity in the context of Information assurance
- Data integrity in the context of Information security
- Data integrity in the context of User Datagram Protocol
- Data integrity in the context of Store-and-forward
Data integrity in the context of Security vulnerabilities
In computer security, vulnerabilities are flaws or weaknesses in a system's design, implementation, or management that can be exploited by a malicious actor to compromise its security.
Despite a system administrator's best efforts to achieve complete correctness, virtually all hardware and software contain bugs where the system does not behave as expected. If the bug could enable an attacker to compromise the confidentiality, integrity, or availability of system resources, it can be considered a vulnerability. Insecure software development practices as well as design factors such as complexity can increase the burden of vulnerabilities.
Data integrity in the context of Human error
Human error is an action that has been done but that was "not intended by the actor; not desired by a set of rules or an external observer; or that led the task or system outside its acceptable limits". Human error has been cited as a primary cause and contributing factor in disasters and accidents in industries as diverse as nuclear power (e.g., the Three Mile Island accident), aviation, space exploration (e.g., the Space Shuttle Challenger disaster and Space Shuttle Columbia disaster), and medicine. Prevention of human error is generally seen as a major contributor to reliability and safety of (complex) systems. Human error is one of the many contributing causes of risk events.
Data integrity in the context of Information assurance
Information assurance (IA) is the practice of assuring information and managing risks related to the use, processing, storage, and transmission of information. Information assurance includes protection of the integrity, availability, authenticity, non-repudiation and confidentiality of user data. IA encompasses both digital protections and physical techniques. These methods apply to data in transit, both physical and electronic forms, as well as data at rest. IA is best thought of as a superset of information security (i.e. umbrella term), and as the business outcome of information risk management.
Data integrity in the context of Information security
Information security (infosec) is the practice of protecting information by mitigating information risks. It is part of information risk management. It typically involves preventing or reducing the probability of unauthorized or inappropriate access to data or the unlawful use, disclosure, disruption, deletion, corruption, modification, inspection, recording, or devaluation of information. It also involves actions intended to reduce the adverse impacts of such incidents. Protected information may take any form, e.g., electronic or physical, tangible (e.g., paperwork), or intangible (e.g., knowledge). Information security's primary focus is the balanced protection of data confidentiality, integrity, and availability (known as the CIA triad, unrelated to the US government organization) while maintaining a focus on efficient policy implementation, all without hampering organization productivity. This is largely achieved through a structured risk management process.
To standardize this discipline, academics and professionals collaborate to offer guidance, policies, and industry standards on passwords, antivirus software, firewalls, encryption software, legal liability, security awareness and training, and so forth. This standardization may be further driven by a wide variety of laws and regulations that affect how data is accessed, processed, stored, transferred, and destroyed.
Data integrity in the context of User Datagram Protocol
In computer networking, the User Datagram Protocol (UDP) is one of the core communication protocols of the Internet protocol suite used to send messages (transported as datagrams in packets) to other hosts on an Internet Protocol (IP) network. Within an IP network, UDP does not require prior communication to set up communication channels or data paths.
UDP is a connectionless protocol, meaning that messages are sent without negotiating a connection and that UDP does not keep track of what it has sent. UDP provides checksums for data integrity, and port numbers for addressing different functions at the source and destination of the datagram. It has no handshaking dialogues and thus exposes the user's program to any unreliability of the underlying network; there is no guarantee of delivery, ordering, or duplicate protection. If error-correction facilities are needed at the network interface level, an application may instead use Transmission Control Protocol (TCP) or Stream Control Transmission Protocol (SCTP) which are designed for this purpose.
Data integrity in the context of Store-and-forward
Store and forward is a telecommunications technique in which information is sent to an intermediate station where it is kept and sent at a later time to the final destination or to another intermediate station. The intermediate station, or node in a networking context, verifies the integrity of the message before forwarding it. In general, this technique is used in networks with intermittent connectivity, especially in the wilderness or environments requiring high mobility. It may also be preferable in situations when there are long delays in transmission and error rates are variable and high, or if a direct, end-to-end connection is not available.