Security and protection in information systems should be built taking into account a comprehensive approach to the construction of a protection system, which involves combining into a single set of necessary measures and means of information protection at all levels of the information support system.
The information security system should be aimed at preventing the loss of information, its distortion, unauthorized access, and its illegal use during the design, implementation, and operation of information subsystems.
From this point of view, the creation and maintenance of the database protection and security system are one important aspect of the development and functioning of any information system.
Definition – What Does Data Security Mean?
Data security refers to the protective digital privacy measures applied to prevent unauthorized access to computers, databases, and websites. Data security also protects data from corruption. Data security is an important aspect of IT for organizations of all sizes and types.
Data security is also known as information security (IS) or computer security.
What Makes Data Security Crucial?
Data security is the technique of preventing digital data from being accessed by unauthorized parties, corrupted, or stolen at any point in its lifespan. It is a notion that covers all facets of information security, including administrative and access controls, logical security of software programs, and physical security of hardware and storage devices. Organizational policies and procedures are also included.
Robust data security measures, when executed correctly, guard against insider threats and human mistakes, which continue to be among the primary causes of data breaches in the modern day while also safeguarding an organization’s information assets from cybercriminal activity. Implementing tools and technology that improve the organization’s visibility into where its crucial data is located and how it is utilized is a key component of data security. In a perfect world, these technologies would be able to automate reporting, apply safeguards like encryption, data masking, and redaction of sensitive information, and apply protections like encryption, data masking, and compliance with regulatory standards.
Every facet of how organizations today operate and compete is being radically changed by digital transformation. Enterprises are producing, storing, and manipulating an ever-increasing amount of data, which increases the need for data governance. Computing environments are also more sophisticated than they used to be, frequently encompassing the public cloud, the business data center, and a variety of edge devices, including robots, remote servers, and Internet of Things (IoT) sensors. The increased attack surface that results from this complexity makes it harder to secure and monitor.
Consumer understanding of the value of data privacy is growing concurrently. Numerous new privacy laws have recently been passed, like the California Consumer Protection Act and Europe’s General Data Protection Regulation (GDPR), in response to growing public demand for data protection efforts (CCPA). The Sarbanes-Oxley Act (SOX), which shields shareholders in publicly traded companies from accounting errors and financial fraud, and the Health Insurance Portability and Accountability Act (HIPAA), which protects electronic health records, are among the long-standing data security regulations that these new regulations join. Every business has a significant financial motive to guarantee compliance, given the potential penalty of millions of dollars.
Data’s commercial worth has never been higher than it is right now. Intellectual property (IP) loss can have an effect on future developments and profitability. With a whopping 75% of consumers indicating that they won’t make a purchase from a company they don’t trust to secure their data, it is clear that trustworthiness is becoming more and more crucial to customers.