Blockchain's Data Integrity and Reliability

Introduction

Data integrity is the quality that the information utilized in a solution is accurate, trustworthy, and beneficial to all parties. The term “data integrity” is used in this context to refer to the completeness, timeliness, and correctness of the data throughout its entire lifespan as well as a resistance to unintentional data alteration, which is a broad concept that is widely used in the supply-chain business. Today, data is a valuable resource. In a wide range of industries, from finance and insurance to health, education, and public administration, strategy should inform all corporate decisions. Trusting data has therefore become essential as more and more human activities helped by computers rely on it (Boureanu et al., 2020). The importance of data has also made it a prime target for cyber-attacks that seek to undermine the key CIA qualities (Confidentiality, Integrity, and Availability) that data must possess in order to be trusted.

Figure 1.

Prime target for cyber-attacks

Globally, data security has grown to be a serious problem. There are many data threats out there. These security risks, which might take the shape of flaws, hacks, data breaches, insider threats, staff mistakes, etc., certainly exist, but they must be minimized to prevent harm. Although it might be difficult to stop the risks, they can actually be reduced. Depending on which CIA properties are attacked online, distinct data trust impairments result. In particular, destroying availability only temporarily prohibits data from being obtained; however, processes can be restarted as soon as data are once again accessible. While breaching confidentiality results in the disclosure of private data that cannot be undone, the original data are still accessible and usable, at least to the extent permitted by the damage that was caused (i.e., an organization victim of data leakage may have to face economic consequences) (Hasanat et al., 2020). In contrast, altering data integrity is a seriously harmful attack that almost always creates serious problems for data trust. In fact, tampering with data can go unnoticed and fuel malevolent operations by removing individual entries (i.e., to erase bothersome traces) or altering specific chunks of data (i.e., to change the behavior of data consumers). When integrity is breached, unlike with confidentiality and availability, the original data cannot be recovered and is permanently destroyed. Integrity attacks are therefore difficult to detect and highly effective (Bumblauskas et al., 2020).

Data integrity problems are made worse in cloud computing environments because data owners have no control over how, where, and by whom their data are accessed. However, a growing number of both public and private organizations are outsourcing their data because “It reduces the expense of local data storage as well as the weight of maintenance costs.” Therefore, it has become necessary to address the issue of assuring data integrity features in cloud computing systems.

Analyses Of Current Methods For Data Integrity Assurance

By computing checksum values and comparing them to reference values and methods based on cryptographic techniques, such as key and keyless hashing, means of electronic signature, there are various known ways to ensure data integrity. The drawback of these approaches is the inability to guarantee their integrity without adding an additional mechanism for data recovery. The use of several sorts of reservations employing RAID technology (Redundant Array of Independent Disks) (RAID arrays) implemented in hardware or software, duplication techniques, and redundant coding techniques are further ways to guarantee the integrity of data. These techniques' significant redundancy is a drawback (Cristofaro, 2020).