Data integrity in the context of Rollback (data management)

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 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.

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.

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.

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.

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.

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.

Real-time communication (RTC) is a category of software protocols and communication hardware media that gives real-time guarantees, which is necessary to support real-time guarantees of real-time computing. Real-time communication protocols are dependent not only on the validity and integrity of data transferred but also the timeliness of the transfer. Real-time communication systems are generally understood as one of two types: hard real-time (HRT) and soft real-time (SRT). The difference between a hard and soft real-time communication system is the consequences of incorrect operation. Safety-critical systems capable of causing catastrophic consequences upon a fault, such as aircraft fly-by-wire systems, are designated as hard real-time, whereas non-critical but ideally real-time systems, such as hotel reservation systems, are designated as soft real-time. The designation of a real-time communication system as hard or soft has significant influence on its design.

A checksum is a small-sized block of data derived from another block of digital data for the purpose of detecting errors that may have been introduced during its transmission or storage. By themselves, checksums are often used to verify data integrity but are not relied upon to verify data authenticity.

The procedure which generates this checksum is called a checksum function or checksum algorithm. Depending on its design goals, a good checksum algorithm usually outputs a significantly different value, even for small changes made to the input. This is especially true of cryptographic hash functions, which may be used to detect many data corruption errors and verify overall data integrity; if the computed checksum for the current data input matches the stored value of a previously computed checksum, there is a very high probability the data has not been accidentally altered or corrupted.

Hypertext Transfer Protocol Secure (HTTPS) is an extension of the Hypertext Transfer Protocol (HTTP). It uses encryption for secure communication over a computer network, and is widely used on the Internet. In HTTPS, the communication protocol is encrypted using Transport Layer Security (TLS) or, formerly, Secure Sockets Layer (SSL). The protocol is therefore also referred to as HTTP over TLS, or HTTP over SSL.

The principal motivations for HTTPS are authentication of the accessed website and protection of the privacy and integrity of the exchanged data while it is in transit. It protects against man-in-the-middle attacks, and the bidirectional block cipher encryption of communications between a client and server protects the communications against eavesdropping and tampering. The authentication aspect of HTTPS requires a trusted third party to sign server-side digital certificates. This was historically an expensive operation, which meant fully authenticated HTTPS connections were usually found only on secured payment transaction services and other secured corporate information systems on the World Wide Web. In 2016, a campaign by the Electronic Frontier Foundation with the support of web browser developers led to the protocol becoming more prevalent. HTTPS has since 2018 been used more often by web users than non-secure HTTP, primarily to protect page authenticity on all types of websites, secure accounts, and keep user communications, identity, and web browsing private.

Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model.

Normalization entails organizing the columns (attributes) and tables (relations) of a database to ensure that their dependencies are properly enforced by database integrity constraints. It is accomplished by applying some formal rules either by a process of synthesis (creating a new database design) or decomposition (improving an existing database design).

The database schema is the structure of a database described in a formal language supported typically by a relational database management system (RDBMS). The term "schema" refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases). The formal definition of a database schema is a set of formulas (sentences) called integrity constraints imposed on a database. These integrity constraints ensure compatibility between parts of the schema. All constraints are expressible in the same language. A database can be considered a structure in realization of the database language. The states of a created conceptual schema are transformed into an explicit mapping, the database schema. This describes how real-world entities are modeled in the database.

"A database schema specifies, based on the database administrator's knowledge of possible applications, the facts that can enter the database, or those of interest to the possible end-users." The notion of a database schema plays the same role as the notion of theory in predicate calculus. A model of this "theory" closely corresponds to a database, which can be seen at any instant of time as a mathematical object. Thus a schema can contain formulas representing integrity constraints specifically for an application and the constraints specifically for a type of database, all expressed in the same database language. In a relational database, the schema defines the tables, fields, relationships, views, indexes, packages, procedures, functions, queues, triggers, types, sequences, materialized views, synonyms, database links, directories, XML schemas, and other elements.