“Stronger cybersecurity starts with a data and analytics strategy”. In social science research, data can be collected manually or electronically, and can be quantitative or qualitative. But no matter what method we will use to collect our data, from the conceptualization of a research project to the archiving and disposal of research materials, researchers need to work with data through the complete stages of data selection, data collection, data analysis, data handling, and data reporting and publishing. Those involved in research can face integrity issues in each stage, and therefore, should be prepared deal with and address the issues that may arise from these issues.
Data integrity is a term used to refer to the accuracy and reliability of data. Data must be complete, with no variations or compromises from the original, to be considered reliable and accurate. Compromises to data integrity can happen in a number of ways. In industries where data is handled, identifying and addressing potential sources of damage to data is an important aspect of data security. Data increasingly drives enterprise decision-making, but it must undergo a variety of changes and processes to change from raw form to more usable formats that are practical for identifying relationships and facilitating informed decisions. As a key component of cybersecurity, data integrity is an issue inherent in all information systems. It is particularly important for analytics strategy in social statistics.
About Hashing and Hashing Algorithms (Section by Claude Turner)
A hashing algorithm transforms a digital message into a short “message digest” for use in digital signatures and other applications. Even a small change in the original message creates a change in the digest, making it easier to detect accidental or intentional changes to the original message. Hash functions can be used in a variety of security applications such as message authentication. They also are useful during routine software upgrades to make sure that the new software has not been tampered with. Additionally, hashing can be used to verify whether a downloaded or copied file has been intentionally or accidentally modified.
Examples of hashing algorithms are MD5, SHA-1, and SHA-3. MD5 is one of the oldest hashing algorithms and is gradually been phased out in favor of more modern and reliable algorithms. SHA-3 is latest hashing algorithms to be approved by the National Institute of Standards and Technologies (NIST).
Microsoft File Integrity Checker (Section by Claude Turner)
The Microsoft describes its File Integrity Checker (FCIV) as command line utility that computes and verifies cryptographic hash values of files. In the exercises in this module, you will use the FCIV utility to generate MD5 or SHA-1 hash values for files to verify the integrity of a copied or downloaded files. The integrity of a copied or downloaded file is established by verifying that its hashed value equals its known good value. FCIV can compare hash values to make sure that the files have not been changed. If the file is modified, the hash is different.