How to Choose the Right Data Loss Prevention Architecture

Data loss prevention (DLP) is an essential aspect of modern cybersecurity. As companies generate and process more data than ever before, the risks of data breaches, leaks, and thefts are higher than ever. Data loss prevention architecture is the foundation of a strong DLP program that can protect sensitive data and intellectual property from internal and external threats.

Key Considerations

Choosing the right DLP architecture is critical to the success of any DLP program. GTB Technologies is a leading provider of DLP solutions that offer a range of architectures to meet different business needs. Here are the key considerations for choosing the right DLP architecture with GTB Technologies.

  1. Cloud-based vs. on-premises architecture: One of the first decisions to make is whether to deploy a cloud-based or on-premises DLP architecture. Cloud-based DLP solutions are hosted by a third-party provider and offer scalability, flexibility, and ease of use. On the other hand, on-premises DLP solutions are installed on the company’s own servers and offer greater control and customization. GTB Technologies offers both cloud-based and on-premises DLP solutions, allowing companies to choose the architecture that best suits their needs.
  2. Network vs. endpoint architecture: Another key decision is whether to deploy a network-based or endpoint-based DLP architecture. Network-based DLP solutions monitor network traffic to detect and prevent data leaks and breaches. Endpoint-based DLP solutions, on the other hand, focus on protecting data at the endpoint, such as laptops, desktops, and mobile devices. GTB Technologies offers both network-based and endpoint-based DLP solutions, allowing companies to choose the architecture that best fits their security posture.
  3. Rule-based vs. machine learning-based architecture: Rule-based DLP solutions use pre-defined rules and policies to detect and prevent data leaks and breaches. Machine learning-based DLP solutions, on the other hand, use artificial intelligence and machine learning algorithms to identify patterns and anomalies that may indicate a data breach. GTB Technologies offers both rule-based and machine learning-based DLP solutions, allowing companies to choose the architecture that best meets their security needs.
  4. Integration with other security solutions: DLP solutions work best when integrated with other security solutions, such as firewalls, intrusion detection systems, and SIEMs. GTB Technologies offers integrations with a wide range of security solutions, allowing companies to build a comprehensive security ecosystem that can detect and prevent data breaches, malware attacks, and other cyber threats.

Way to Success

The reality is that choosing the right DLP architecture is critical to the success of any DLP program. GTB Technologies offers a range of DLP solutions that can be customized to meet the unique needs of different businesses. By considering factors such as cloud-based vs. on-premises architecture, network vs. endpoint architecture, rule-based vs. machine learning-based architecture, and integration with other security solutions, companies can choose the DLP architecture that best fits their security posture and business objectives.

Visibility: Accurately, discover sensitive data; detect and address broken business process, or insider threats including sensitive data breach attempts.

Protection: Automate data protection, breach prevention and incident response both on and off the network; for example, find and quarantine sensitive data within files exposed on user workstations, FileShares and cloud storage.

Notification: Alert and educate users on violations to raise awareness and educate the end user about cybersecurity and corporate policies.

Education: Start target cyber-security training; e.g., identify end-users violating policies and train them.

  • Employees and organizations have knowledge and control of the information leaving the organization, where it is being sent, and where it is being preserved.
  • Ability to allow user classification to give them influence in how the data they produce is controlled, which increases protection and end-user adoption.
  • Control your data across your entire domain in one Central Management Dashboard with Universal policies.
  • Many levels of control together with the ability to warn end-users of possible non-compliant – risky activities, protecting from malicious insiders and human error.
  • Full data discovery collection detects sensitive data anywhere it is stored, and provides strong classification, watermarking, and other controls.
  • Delivers full technical controls on who can copy what data, to what devices, what can be printed, and/or watermarked.
  • Integrate with GRC workflows.
  • Reduce the risk of fines and non-compliance.
  • Protect intellectual property and corporate assets.
  • Ensure compliance within industry, regulatory, and corporate policy.
  • Ability to enforce boundaries and control what types of sensitive information can flow where.
  • Control data flow to third parties and between business units.