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Data In Use
Data in use is an information technology term referring to active data which is stored in a non-persistent digital state typically in computer random-access memory (RAM), CPU caches, or CPU registers. Scranton, PA data scientist Daniel Allen in 1996 proposed ''Data in use'' as a complement to the terms ''data in transit'' and '' data at rest'' which together define the three states of digital data. Alternative definitions Data in use refers to data in computer memory. Some cloud software as a service (SaaS) providers refer to data in use as any data currently being processed by applications, as the CPU and memory are utilized. Concerns Because of its nature, data in use is of increasing concern to businesses, government agencies and other institutions. Data in use, or memory, can contain sensitive data including digital certificates, encryption keys, intellectual property (software algorithms, design data), and personally identifiable information. Compromising data in use ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data
In the pursuit of knowledge, data (; ) is a collection of discrete values that convey information, describing quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures. Data may be used as variables in a computational process. Data may represent abstract ideas or concrete measurements. Data is commonly used in scientific research, economics, and in virtually every other form of human organizational activity. Examples of data sets include price indices (such as consumer price index), unemployment rates, literacy rates, and census data. In this context, data represents the raw facts and figures which can be used in such a manner in order to capture the useful information out of it. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ARM Cortex-A8
The ARM Cortex-A8 is a 32-bit processor core licensed by ARM Holdings implementing the ARMv7-A architecture. Compared to the ARM11, the Cortex-A8 is a dual-issue superscalar design, achieving roughly twice the instructions per cycle. The Cortex-A8 was the first Cortex design to be adopted on a large scale in consumer devices. Features Key features of the Cortex-A8 core are: * Frequency from 600 MHz to 1 GHz and above * Superscalar dual-issue microarchitecture * NEON SIMD instruction set extension * 13-stage integer pipeline and 10-stage NEON pipeline * VFPv3 Floating Point Unit * Thumb-2 instruction set encoding * Jazelle RCT (Also known as ThumbEE instruction set) * Advanced branch prediction unit with >95% accuracy * Integrated level 2 Cache (0–4 MiB) * 2.0 DMIPS/MHz Chips Several system-on-chips (SoC) have implemented the Cortex-A8 core, including: * Allwinner A1X * Apple A4 * Freescale Semiconductor i.MX51 * Rockchip RK2918, RK2906 * Samsung Exyn ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Privacy-enhancing Technologies
Privacy-enhancing technologies (PET) are technologies that embody fundamental data protection principles by minimizing personal data use, maximizing data security, and empowering individuals. PETs allow online users to protect the privacy of their personally identifiable information (PII), which is often provided to and handled by services or applications. PETs use techniques to minimize an information system's possession of personal data without losing functionality. Generally speaking, PETs can be categorized as hard and soft privacy technologies. Goals of PETs The objective of PETs is to protect personal data and assure technology users of two key privacy points: their own information is kept confidential, and management of data protection is a priority to the organizations who hold responsibility for any PII. PETs allow users to take one or more of the following actions related to personal data that is sent to and used by online service providers, merchants or other users ( ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Blinding (cryptography)
In cryptography, blinding is a technique by which an agent can provide a service to (i.e., compute a function for) a client in an encoded form without knowing either the real input or the real output. Blinding techniques also have applications to preventing side-channel attacks on encryption devices. More precisely, Alice has an input ''x'' and Oscar has a function ''f''. Alice would like Oscar to compute for her without revealing either ''x'' or ''y'' to him. The reason for her wanting this might be that she doesn't know the function ''f'' or that she does not have the resources to compute it. Alice "blinds" the message by encoding it into some other input ''E''(''x''); the encoding ''E'' must be a bijection on the input space of ''f'', ideally a random permutation. Oscar gives her ''f''(''E''(''x'')), to which she applies a decoding ''D'' to obtain . Not all functions allow for blind computation. At other times, blinding must be applied with care. An example of the latter is ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Format-preserving Encryption
In cryptography, format-preserving encryption (FPE), refers to encrypting in such a way that the output (the ciphertext) is in the same format as the input (the plaintext). The meaning of "format" varies. Typically only finite sets of characters are used; numeric, alphabetic or alphanumeric. For example: * Encrypting a 16-digit credit card number so that the ciphertext is another 16-digit number. * Encrypting an English word so that the ciphertext is another English word. * Encrypting an ''n''-bit number so that the ciphertext is another ''n''-bit number (this is the definition of an ''n''-bit block cipher). For such finite domains, and for the purposes of the discussion below, the cipher is equivalent to a permutation of ''N'' integers where ''N'' is the size of the domain. Motivation Restricted field lengths or formats One motivation for using FPE comes from the problems associated with integrating encryption into existing applications, with well-defined data models. A typical ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Non-interactive Zero-knowledge Proof
Non-interactive zero-knowledge proofs are zero-knowledge proofs where information between a prover and a verifier can be authenticated by the prover, without revealing any of the specific information beyond the validity of the transaction itself. This function of encryption makes direct communication between the prover and verifier unnecessary, effectively removing any intermediaries. The core trustless cryptography "proofing" involves a hash function generation of a random number, constrained within mathematical parameters (primarily to modulate hashing difficulties) determined by the prover and verifier. With this cryptographic engine, the prover must demonstrate the validity of the transaction, by solving the hash of a random number. Finally, proof of the answer is returned to the verifier, without revealing its value. There are many different methods for establishing a cryptographic proof of hash validity. Perhaps the most notable method, proof of work, involves computing the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Secure Multi-party Computation
Secure multi-party computation (also known as secure computation, multi-party computation (MPC) or privacy-preserving computation) is a subfield of cryptography with the goal of creating methods for parties to jointly compute a function over their inputs while keeping those inputs private. Unlike traditional cryptographic tasks, where cryptography assures security and integrity of communication or storage and the adversary is outside the system of participants (an eavesdropper on the sender and receiver), the cryptography in this model protects participants' privacy from each other. The foundation for secure multi-party computation started in the late 1970s with the work on mental poker, cryptographic work that simulates game playing/computational tasks over distances without requiring a trusted third party. Note that traditionally, cryptography was about concealing content, while this new type of computation and protocol is about concealing partial information about data while comp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Zero-knowledge Proof
In cryptography, a zero-knowledge proof or zero-knowledge protocol is a method by which one party (the prover) can prove to another party (the verifier) that a given statement is true while the prover avoids conveying any additional information apart from the fact that the statement is indeed true. The essence of zero-knowledge proofs is that it is trivial to prove that one possesses knowledge of certain information by simply revealing it; the challenge is to prove such possession without revealing the information itself or any additional information. If proving a statement requires that the prover possess some secret information, then the verifier will not be able to prove the statement to anyone else without possessing the secret information. The statement being proved must include the assertion that the prover has such knowledge, but without including or transmitting the knowledge itself in the assertion. Otherwise, the statement would not be proved in zero-knowledge because it ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Homomorphic Encryption
Homomorphic encryption is a form of encryption that permits users to perform computations on its encrypted data without first decrypting it. These resulting computations are left in an encrypted form which, when decrypted, result in an identical output to that produced had the operations been performed on the unencrypted data. Homomorphic encryption can be used for privacy-preserving outsourced storage and computation. This allows data to be encrypted and out-sourced to commercial cloud environments for processing, all while encrypted. For sensitive data, such as health care information, homomorphic encryption can be used to enable new services by removing privacy barriers inhibiting data sharing or increase security to existing services. For example, predictive analytics in health care can be hard to apply via a third party service provider due to medical data privacy concerns, but if the predictive analytics service provider can operate on encrypted data instead, these priva ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Homomorphic Encryption
Homomorphic encryption is a form of encryption that permits users to perform computations on its encrypted data without first decrypting it. These resulting computations are left in an encrypted form which, when decrypted, result in an identical output to that produced had the operations been performed on the unencrypted data. Homomorphic encryption can be used for privacy-preserving outsourced storage and computation. This allows data to be encrypted and out-sourced to commercial cloud environments for processing, all while encrypted. For sensitive data, such as health care information, homomorphic encryption can be used to enable new services by removing privacy barriers inhibiting data sharing or increase security to existing services. For example, predictive analytics in health care can be hard to apply via a third party service provider due to medical data privacy concerns, but if the predictive analytics service provider can operate on encrypted data instead, these priva ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Secure Multi-party Computation
Secure multi-party computation (also known as secure computation, multi-party computation (MPC) or privacy-preserving computation) is a subfield of cryptography with the goal of creating methods for parties to jointly compute a function over their inputs while keeping those inputs private. Unlike traditional cryptographic tasks, where cryptography assures security and integrity of communication or storage and the adversary is outside the system of participants (an eavesdropper on the sender and receiver), the cryptography in this model protects participants' privacy from each other. The foundation for secure multi-party computation started in the late 1970s with the work on mental poker, cryptographic work that simulates game playing/computational tasks over distances without requiring a trusted third party. Note that traditionally, cryptography was about concealing content, while this new type of computation and protocol is about concealing partial information about data while comp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Software Guard Extensions
Intel Software Guard Extensions (SGX) is a set of security-related instruction codes that are built into some Intel central processing units (CPUs). They allow user-level and operating system code to define protected private regions of memory, called ''enclaves''. SGX is designed to be useful for implementing secure remote computation, secure web browsing, and digital rights management (DRM). Other applications include concealment of proprietary algorithms and of encryption keys. SGX involves encryption by the CPU of a portion of memory (the ''enclave''). Data and code originating in the enclave are decrypted on the fly ''within'' the CPU, protecting them from being examined or read by other code, including code running at higher privilege levels such the operating system and any underlying hypervisors. While this can mitigate many kinds of attacks, it does not protect against side-channel attacks. A pivot by Intel in 2021 resulted in the deprecation of SGX from the 11th and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
