Will Database Security Win The Battle Against Malicious Data Usage?

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In today’s digital age, data is a vital asset to many individuals and businesses alike. From personal information to sensitive financial records, the value of data can not be understated. However, with the increase in the amount of data being stored online, the risks of security breaches have also increased. Every day, cybercriminals are finding new ways to exploit vulnerabilities and get their hands on valuable data. For this reason, data security has become a critical concern for many individuals and organizations.

Whether you are a business owner looking to protect your company’s sensitive information or simply an individual wanting to keep your data safe, this post is for you. Having said that, let’s explore the importance of data security, steps to protect against data breaches, and innovations and trends to protect data more efficiently.

Will Database Security Protect Sensitive Data from Risks?

What if I tell you that database security is an incredible solution to protect the entire database independently?

Database security encloses a variety of techniques intended to protect database management systems against hostile cyber-attacks and illegitimate use. Database security programs are intended to safeguard not only the data stored within the database, but also the entire data management system and any applications that access it, against misuse, damage, and intrusion.

Database security contains tools, processes, and methodologies which establish and maintain database confidentiality, availability, integrity, and security inside a database environment.

Meanwhile, Immuta, a leader in data security, is bringing significant improvements to its Data Security Platform for Databricks, enabling data teams to secure access to cloud data, including sensitive data discovery, data security, access control, data activity monitoring, and deep integrations, while maintaining a robust data security posture. Fortune 500 organizations and government agencies across the world rely on the company to secure their data.

Nevertheless, ‘Database Security in DBMS’ and ‘Vulnerability Databases’ are two essential techniques that keep the database safe from threats, which can affect the database system. With this in mind, let’s learn how these methods work against database threats.

Does a Vulnerability Database Have the Potential to Safeguard a Database?

Now here is an essential mechanism to help database security protect sensitive data. You must have wondered, what exactly it is. Let me clear it up for you, It is a vulnerability database. It is a mechanism that allows access to information on known flaws or vulnerabilities. Database specialists gather, verify and share information with a large community in order to advance cybersecurity knowledge. Vulnerability databases help organizations in identifying, tracking, and correcting vulnerabilities in their systems. A vulnerability scanner is an automated testing tool based on vulnerability databases that search for vulnerabilities and defects in the system.

Vulnerability scanners are fully automated and only look for vulnerabilities and highlight potential risks. Following that, a penetration test is performed to track the possible attacks on the system.

Databases shield against several vulnerabilities and threats and these differ from one another depending on their purpose. Vulnerabilities include the following:

  • Hardware: This vulnerability includes weak encryption, component deterioration, and firmware defects.
  • Software: User interface problems, privilege-confusion errors, memory assignment bugs, timing errors, and design bugs are included in this vulnerability.
  • Network: This includes insecure architecture, insufficient authentication, and unrestricted access.

Can a Reinforcement of Database Security in DBMS Save the Database?

After learning about vulnerability databases, another technique for protecting and securing a database against intentional or unexpected threats is database security in DBMS. Security issues not only involve the data stored in an organization’s database but also harm other system components and consequently affect the database structure. As a result, database security includes hardware and software components, as well as human resources and data.

Effective security requires appropriate controls, depending on the specific goal and purpose of the system. The demand for effective security, which was often overlooked or neglected in the past, is now being scrutinized by many businesses due to increased theft, fraud, loss of data privacy, data integrity, secrecy, and data availability.

Will Emerging Innovations and Trends Shape the Future of Database Security?

Database security is progressing with new technologies and innovations, so let’s find out which innovations are playing an important role in making database security more prominent.

●     Artificial Intelligence (AI)

AI has emerged as a potential solution to addressing the occurring threats to database security in the era of AI and IoT. With the wealth of sensitive information stored in databases that hackers can capitalize on, there is a demand for securing these databases. AI-driven security tools can help manage the risks and threats to data security by offering real-time monitoring, analysis, and incident response that can’t be easily achieved in a manual way.

However, like any technology, AI also comes with challenges and risks, such as model poisoning, data privacy, and vulnerability to attacks. In this context, AI should be paired with best practices and solutions to protect databases from accidental and intentional threats. Several companies offer AI-driven database security solutions, and enterprises need to adopt the best practices and solutions to secure their databases.

Intel has launched confidential AI, a hardware-based security solution that combines confidential computing and AI to help protect data via a unique application called isolation technology. This technology allows the sharing of AI models and data without exposing intellectual property or sensitive data to other software or cloud providers.

●     Blockchain

Blockchain enhances cloud security by improving data security, specifically data confidentiality, integrity, and availability. Businesses can define the required security levels for the system as a whole, and the individual record level, depending on the blockchain solution and technology employed. Because cloud computing often includes the delegation of trust to a provider, requiring new ways to ensure data security.

Oracle is providing blockchain technology, including a cloud service, an on-premises edition, and a SaaS application for the supply chain. This technology will help businesses to secure their data in an advanced way.

●     Internet of Things (IoT)

While the Internet of Things (IoT) has the potential to transform many industries and businesses, it also possesses the ability to safeguard databases. Securing databases using IoT involves the use of sensors and other connected devices to monitor and protect the database environment. IoT devices can be used to identify and report security vulnerabilities and can also be used to implement preventive measures.

IoT-based database security solutions can be developed to monitor and protect databases from a range of threats, such as hacking, phishing, and data breaches. Companies implementing IoT-based database security should prioritize best practices such as timely software and hardware updates, strong passwords, and access controls to prevent malicious actors from exploiting vulnerabilities in the database.

Microsoft has launched Azure IoT, a cloud-hosted managed service that connects, monitors, and manages billions of IoT assets, including operating and security systems for devices and appliances, with data and analytics. The service helps businesses build, deploy and manage IoT applications.

●     Zero Trust

The Zero Trust security framework is designed in such a way that it requires all users, including inside and outside of the organization’s network system, to be verified and authorized before being granted access to data. It operates by verifying all users and devices attempting to access an organization’s network or data, even if they are already inside the organization’s perimeter. As a security framework, Zero Trust can help ensure that database security is maintained by establishing access policies, authentication protocols, and encryption methods, among others.

In the context of database security, Zero Trust architecture requires strong database security measures such as database encryption, access control, audit, and monitoring. The architecture can also include role-based access control, multifactor authentication, micro-segmentation, and risk-based adaptive policies, among others. Additionally, data protection policies can also be implemented to ensure that sensitive data is protected and made available to authorized personnel only.

Dell Technologies is expanding its industry expertise in data protection machines and software. Their AI-powered resilience and operational security innovation accelerate the adoption of Zero Trust architectures, assisting organizations in protecting themselves from the growing threat of cyberattacks.

What Does the Future Hold for Data Security?

So far We have already learned about database security, but the question may arise here: what’s next? And what it has to offer in the future?

As technology continues to evolve, so do the methods of database security, and the future of database security is one of constant improvement and innovation. The future of database security is likely to focus on advanced security solutions, innovative technologies, and increased attention to best practices to ensure maximum protection for valuable data.

Artificial intelligence (AI)-powered security solutions, the Zero Trust framework, blockchain technology, computer computing, and IoT technology are among the potential trends to watch out for. Additionally, advancements in securing data using encryption and access control measures will likely continue to evolve along with the growth in the amount of data generated.

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