5 Data Security Trends You Should Pay Attention To

Data plays one of the most critical roles in many businesses and organizations today. It is undoubtedly one of the most valuable assets that organizations possess. From customer data to proprietary business information, data is essential for driving business growth and innovation. However, with the growing reliance on digital technologies and data-driven processes, data security has become a critical concern for organizations of all sizes and across all industries. Because of its importance to many different industries, it is the main target of attacks and it’s under the threat of being stolen or accessed by malicious agents.

In this blog, we will explore five data security trends that organizations should pay attention to nowadays. These trends cover various aspects of data security, including cloud security, zero-trust security, data privacy regulations, identity and access management, and the use of artificial intelligence and machine learning in data security. By understanding these trends, organizations can better protect their data, stay compliant with data protection regulations, and stay ahead of evolving cyber threats.

We will provide insights into each trend and discuss practical strategies and best practices that organizations can adopt to improve their data security posture. With the right data security measures in place, organizations can protect their sensitive data and maintain the trust of their customers, partners, and stakeholders.

Data Security context

Cybersecurity threats such as data breaches, ransomware attacks, and insider threats pose a significant risk to organizations, and the consequences of a data breach can be severe. Cyberattacks are getting more difficult to predict, and hackers are constantly developing more intricate attack methods. Attackers often use highly advanced techniques and access the data via security exploits. Security specialists are constantly working out new solutions to reduce the threat to data stored locally, in the cloud or on the endpoints.

Beyond the immediate financial costs of a breach, organizations can suffer reputational damage, legal liability, and loss of customer trust. Therefore, it is essential for organizations to stay up-to-date with the latest data security trends and adopt proactive measures to protect their data.

What are the five data security areas organizations should pay attention to?

The digital landscape constantly evolves, with new technologies and solutions popping up almost daily. These create new possibilities for companies and organizations looking to improve their efficiency and effectiveness and allow cybercriminals to access unknown attack vectors. To prevent those attacks, security specialists have been heavily focusing on the following areas:

  • Cloud, SaaS, and enterprise-level applications security

With the rise of cloud computing, organizations are increasingly adopting cloud-based applications and services. This has made cloud security a critical area of concern for data protection. Organizations need to ensure that their cloud environments are secure, and data is protected both in transit and at rest.

Today’s business landscape is evolving more rapidly than ever, and organizations and companies must use various methods to stay ahead of their competition. To do this, most firms nowadays look beyond traditional enterprise-level applications and are increasingly turning towards the implementation of cloud and SaaS solutions. This trend is gaining serious momentum, with various industry experts such as Gartner predicting that global spending on cloud services will reach approximately $600 billion in 2023. By leveraging cloud and SaaS solutions, organizations can improve their effectiveness and response time to deliver their service faster and more efficiently. However, this shift has also brought with it its own set of security threats to the IT structures of various companies. To combat these dangers, security specialists worldwide have been turning to different solutions which can help them protect cloud-based environments.

  • Growing portfolios of applications 

With more SaaS solutions available to organizations worldwide, IT specialists have turned to more different apps than ever. There are now more different apps used to solve various issues. While applications allow for easy and efficient work, security teams must also control all the data that goes through these apps. However, this creates a danger of shadow IT within organizations. Accessing sensitive data with unauthorized applications or sending important company information over an unsecured communication app seriously jeopardizes the data. Some research shows that as much as 56% of apps used across various industries are not approved by IT administrators thus being a part of shadow IT. Security specialists are now facing a challenge in preventing cases of shadow IT within their organizations.Zero Trust security is an approach that assumes that all devices and users, whether inside or outside the network, are potentially malicious. This means that access to data and resources is granted on a need-to-know basis, and only after proper authentication and authorization. This approach can help organizations to reduce the risk of data breaches and insider threats.

  • Constantly expanding data regulations.

Data privacy regulations, such as GDPR, CCPA, and LGPD, have become more stringent and complex. Organizations need to ensure that they are compliant with these regulations and protect sensitive data from unauthorized access, disclosure, and misuse.

As more and more data is being gathered by organizations and companies worldwide, governments and legal organizations are working to create new data retention policies. Depending on what type of service your company offers or what data it might hold in its IT structures, the organization might be subject to different legal regulations. These mostly dictate who can access the data and how the data should be stored, and for how long. Organizations that fail to meet the criteria dictated by the data retention legislature are subject to severe financial and legal disciplinary measures. Because of this, IT specialists are continuously looking to develop solutions that will allow them to create a data retention policy that adheres to all legal standards.

  • Improved malware effectiveness

While IT specialists constantly develop new methods to combat threats to their data structures, cybercriminals are not resting either. Today malware is more intricate than ever, and hackers are constantly devising new strategies and figuring out unknown attack vectors. Today’s malware can take your security specialists by surprise, as vectors of attack are often previously new security exploits. Add to this long dwell time of modern malware, and many cyber attacks go undetected until it’s too late. To prevent these dangers from occurring, security specialists must invest in solutions that allow them to stay one step ahead.

Siloed applications and other potential barriers, such as organization size and scope, can make protecting against much modern malware more difficult. Complex organization structure and data policies often lower overall data visibility, making it difficult for your IT specialists to coordinate and respond to threats. In addition, this can also lower the overall recovery time, which makes a potential attack all the more devastating.

  • Identity and Access Management (IAM) 

IAM has become an increasingly important aspect of data security in recent years due to the growing trend of remote work and the rise of cloud computing. IAM refers to the processes and technologies used to manage and control access to a company’s digital resources, such as data, applications, and networks. By implementing IAM, organizations can ensure that only authorized users have access to sensitive information, thereby reducing the risk of data breaches.

One of the key data security trends related to IAM is – mentioned earlier – the move towards a Zero Trust model. Another important trend in data security related to IAM is the increased use of multifactor authentication (MFA). MFA requires users to provide more than one form of identification in order to access resources, such as a password and a fingerprint scan. This approach adds an extra layer of security and makes it more difficult for cybercriminals to gain access to sensitive information, even if they are able to steal a user’s password.

Overall, Identity and Access Management is a critical aspect of data security, especially as organizations face new challenges related to remote work, cloud computing, and cyber threats. By implementing IAM solutions such as Zero Trust and MFA, companies can reduce the risk of data breaches and protect sensitive information from unauthorized access.

How Can Organizations Protect Their IT Structures?

As you can see, the IT security landscape is constantly evolving, with new threats and solutions continually popping up. Although many dangers online can put your most important data at risk, your organization can ensure maximum data security, even when risks to your data are constantly growing. Here are some of the steps you can take to protect your organization’s IT structures:

  • Centralized backup platform

One of the best ways to safeguard your data is to use a centralized backup platform to secure data across the enterprise. A comprehensive backup solution, with features such as encryption, multi-factor authentication, Role-Based Access Control or Air-Gap Backup can help you significantly improve the security of your most important data. A centralized backup platform is a software solution that allows an organization to back up and store data from multiple sources. The platform typically provides a single interface for managing backup policies, scheduling backup jobs, and monitoring backup status across an organization’s IT infrastructure.

Centralized backup platforms can support a variety of backup types, including full backups, incremental backups, differential backups, and continuous backups. They can also provide advanced features such as data deduplication, compression, and encryption. By centralizing backups, organizations can improve data protection and recovery capabilities, reduce backup costs and simplify backup management.

In addition, centralized backup platforms can facilitate disaster recovery by providing easy access to repository for restoring data in the event of a data loss or system failure. This can help to minimize downtime and ensure business continuity in the face of unexpected disruptions.

  • Machine learning solutions

Machine learning (ML) has been a hot topic among IT specialists for some time now, as ML solutions can quickly process a lot of information and further enhance your IT security. Effective ML solutions can spot potentially malicious changes to your data. Machine learning (ML) data protection solutions use advanced algorithms to analyze and classify data, identify risks, and protect sensitive information from unauthorized access. These solutions can help organizations to manage and secure their data in a more efficient and effective way.

Here are some insights into machine learning data protection solutions:

• Data classification: ML algorithms can be trained to identify and classify sensitive data based on patterns, content, and context. This can help organizations to identify and protect critical data more effectively.

• Risk analysis: ML algorithms can be used to analyze data access patterns and detect anomalies that may indicate a potential security threat. This can help organizations to identify and respond to security incidents more quickly.

• User behavior analytics: ML algorithms can be used to analyze user behavior and detect suspicious activity, such as unauthorized access attempts or unusual data transfer patterns. This can help organizations to prevent data breaches and insider threats.

• Automated policy enforcement: ML algorithms can be used to automatically enforce data protection policies, such as access controls, data encryption, and data masking. This can help organizations to reduce the risk of human error and ensure consistent compliance with policies and regulations.

• Continuous improvement: ML algorithms can be used to continuously learn from data patterns and improve data protection capabilities over time. This can help organizations to stay ahead of evolving security threats and maintain a high level of data protection.

Overall, machine learning data protection solutions can help organizations to improve their data protection capabilities, reduce the risk of data breaches and cyber attacks, and ensure compliance with data protection regulations.

  • SIEM/SOAR integration

Implementing SIEM/SOAR integrated solutions in your IT structures can help your IT team respond quickly to potential security threats, enabling cross-functional collaboration between teams. SIEM/SOAR integration refers to the process of integrating a Security Information and Event Management (SIEM) system with a Security Orchestration, Automation, and Response (SOAR) platform.

A SIEM system is designed to collect, correlate, and analyze security event data from various sources to detect and alert on security threats. On the other hand, a SOAR platform is designed to automate and orchestrate security operations, allowing security teams to respond to security incidents more quickly and efficiently.

The integration of SIEM and SOAR platforms allows for a more comprehensive and streamlined security operation. The SIEM system can collect and analyze security event data and then send alerts and information to the SOAR platform. The SOAR platform can then use this information to automatically respond to security incidents, such as containing an infected system or disabling a compromised account.

Overall, SIEM/SOAR integration helps to improve the speed and accuracy of threat detection, reduce response times, and increase overall security posture.

  • Automated data discovery solution

An automated data discovery solution can help your IT team to identify vulnerable data. With solutions of this type, your team should be able to see which data is the most visible and at risk and use this information to make your IT security more effective.An automated data discovery solution is a software tool or platform that is designed to automatically scan an organization’s network, systems, databases, and other repositories to locate, classify, and organize sensitive and valuable data.

Automated data discovery solutions use a variety of techniques, including scanning, crawling, and indexing, to locate data across an organization’s IT infrastructure. These solutions can identify different types of data, including personally identifiable information (PII), financial data, health records, and intellectual property. Once the data is located, the automated data discovery solution can classify the data according to its level of sensitivity, and apply appropriate data protection policies such as access controls, data encryption, and data masking.

Automated data discovery solutions help organizations to comply with data protection regulations such as GDPR, CCPA, HIPAA, and others, by ensuring that sensitive data is properly identified, classified, and secured. These solutions can also help organizations to identify and mitigate data breaches, minimize data exposure, and reduce the risk of data loss.

  • Automated policy enforcement

Data retention policy can be a constant struggle between the efficiency of your workloads and fulfilling any legal obligations your organization might have regarding its data. With solutions that automate policy enforcement, your IT specialists can instead dedicate the resources necessary to more critical tasks, allowing you to adhere to all the regulations while ensuring maximum work effectiveness.

Automated policy enforcement refers to the process of automatically enforcing policies, rules, and regulations across an organization’s IT infrastructure. This can include enforcing security policies, compliance regulations, data governance policies, and other types of policies. Automated policy enforcement can be implemented through various means, such as access controls, data encryption, network segmentation, application whitelisting, and endpoint management. It typically involves the use of automated tools or platforms that can monitor, detect, and respond to policy violations in real-time.

For example, an automated policy enforcement tool can detect when a user attempts to access a resource that they do not have permission to access, and block that access automatically. Similarly, an automated tool can detect when a user attempts to download or transfer sensitive data outside of the organization, and prevent that action from occurring. By automating policy enforcement, organizations can reduce the risk of human error and ensure consistent compliance with policies and regulations. This can help to improve overall security posture, reduce the risk of data breaches, and avoid costly regulatory penalties.

To Conclude

Overall, organizations need to stay vigilant and adopt a proactive approach to data security, to protect their sensitive data and stay ahead of evolving cyber threats. In any situation where the security of company data is at stake, a reliable backup solution comes in handy. Get the free Trial or contact us if you are interested in a one-on-one demo.

Paweł Mączka Photo

text written by:

Pawel Maczka, CTO at Storware