Data Loss Prevention 2018 & Data Loss Prevention 2020

TL;DR:

• Data Loss Prevention (DLP) technologies have evolved significantly in 2018 and 2020 to safeguard sensitive data.
• DLP solutions integrated with cloud services, enhanced encryption techniques, and incorporated AI and machine learning.
• They addressed risks like data breaches, regulatory compliance, and insider threats.
• An ideal DLP solution should offer comprehensive coverage, advanced detection capabilities, user-friendly interface, and compliance management.
• Strac is a leading DLP solution with built-in & custom detectors, compliance support, ease of integration, accurate detection, extensive SaaS integrations, and endpoint DLP capabilities.

In today's digital age, safeguarding sensitive data is paramount. The evolution of Data Loss Prevention (DLP) technologies has been significant over the years, with notable advancements in 2018 and 2020. In this blog post, we will delve into what Data Loss Prevention 2020 and Data Loss Prevention 2018 entailed, the risks and problems they solved, and what an ideal solution should include. We'll also highlight how Strac, a leading DLP solution, stands out in this field.

What is Data Loss Prevention 2020 and Data Loss Prevention 2018?

Data Loss Prevention 2018 and Data Loss Prevention 2020 refer to the measures, technologies, and strategies implemented during these years to prevent unauthorized access, use, disclosure, disruption, modification, or destruction of sensitive data. These periods saw significant enhancements in DLP capabilities, driven by evolving cybersecurity threats and regulatory requirements.

Examples from 2018:

1. Integration with Cloud Services: In 2018, DLP solutions began to integrate more seamlessly with cloud services. For instance, organizations could apply DLP policies to data stored in cloud applications like Google Drive and OneDrive, ensuring that sensitive information was protected regardless of where it resides.
2. Enhanced Encryption Techniques: For data loss prevention, 2018 saw the introduction of more robust encryption techniques. Companies could encrypt sensitive data at rest and in transit, making it nearly impossible for unauthorized users to access the information without the appropriate decryption keys.

Examples from 2020:

1. AI and Machine Learning: Data Loss Prevention 2020 incorporated AI and machine learning to enhance detection and response capabilities. These technologies allowed for more accurate identification of sensitive data and potential threats, reducing false positives and improving overall security posture.
2. Endpoint DLP: In 2020, endpoint DLP solutions gained traction, providing protection at the device level. This meant that data on laptops, desktops, and mobile devices could be monitored and controlled to prevent leaks, even when employees worked remotely.

What Risks or Problems Do Data Loss Prevention 2020 and Data Loss Prevention 2018 Solve?

Data Loss Prevention 2018 and Data Loss Prevention 2020 addressed several critical risks and problems faced by organizations:

1. Data Breaches: Both in 2018 and 2020, data breaches were a significant concern. DLP solutions helped mitigate this risk by ensuring that sensitive data was not exposed to unauthorized users. For example, in 2018, a major hotel chain experienced a data breach that exposed the personal information of millions of guests. A robust DLP solution could have detected and prevented the unauthorized access.
2. Regulatory Compliance: Compliance with regulations such as GDPR, HIPAA, and PCI-DSS was a driving force behind DLP advancements. Data Loss Prevention 2020 and Data Loss Prevention 2018 solutions provided the tools necessary to adhere to these regulations by monitoring, detecting, and protecting sensitive data.
3. Insider Threats: Insider threats, whether malicious or accidental, pose a significant risk. DLP solutions in 2018 and 2020 included features to monitor employee actions and prevent the unauthorized sharing or mishandling of sensitive information. For instance, an employee attempting to download large amounts of confidential data could be flagged and stopped by the DLP system.

What Does an Ideal Data Loss Prevention 2020 and Data Loss Prevention 2018 Solution Need to Have?

Data loss prevention (DLP) solutions have evolved significantly over the years, particularly in 2018 and 2020, driven by the increasing sophistication of cyber threats and evolving regulatory requirements. An ideal solution for data loss prevention 2020 and data loss prevention 2018 should encompass several key features to effectively protect sensitive information.

1. Comprehensive Coverage: A robust DLP solution must offer comprehensive coverage across all data touchpoints. This includes protection for endpoints, networks, cloud services, and applications. In 2018, the rise of cloud computing necessitated DLP solutions that could secure data stored in cloud environments such as Google Drive, OneDrive, and other SaaS applications. By 2020, the shift to remote work further emphasized the need for endpoint protection, ensuring that data on laptops, desktops, and mobile devices remained secure. Comprehensive coverage ensures that sensitive data is safeguarded regardless of where it is stored or accessed, preventing unauthorized access and data breaches.
2. Advanced Detection and Response: Leveraging AI and machine learning, an ideal DLP solution should accurately detect sensitive data and potential threats with minimal false positives. In 2018, DLP solutions began incorporating machine learning algorithms to improve the accuracy of data classification and threat detection. By 2020, advancements in AI allowed for more sophisticated analysis of user behavior and data patterns, enabling proactive identification of anomalies that might indicate a security threat. Real-time monitoring and automated response capabilities are essential for quick and effective incident management. This means that as soon as a potential data loss incident is detected, the system can take immediate action, such as blocking the transfer, alerting administrators, or encrypting the data.
3. User-Friendly Interface and Integration: Ease of use and integration with existing systems are crucial for the successful implementation of a DLP solution. In 2018, many organizations struggled with the complexity of integrating DLP solutions into their existing IT infrastructure. By 2020, DLP providers recognized this challenge and focused on developing more intuitive interfaces and seamless integration capabilities. An ideal DLP solution should offer intuitive dashboards that provide clear visibility into data protection activities and allow for easy management of DLP policies. Additionally, it should seamlessly integrate with cloud services, email platforms, and endpoint devices to ensure comprehensive protection without disrupting business operations.
4. Compliance Management: Regulatory compliance is a major driver for DLP adoption. An effective DLP solution must help organizations comply with relevant regulations by providing tools to monitor, report, and manage sensitive data in accordance with legal requirements. In 2018, the introduction of the General Data Protection Regulation (GDPR) in Europe highlighted the need for stringent data protection measures. By 2020, other regulations like the California Consumer Privacy Act (CCPA) and the Health Insurance Portability and Accountability Act (HIPAA) further emphasized the importance of compliance. An ideal DLP solution should offer built-in compliance templates and customizable policies that align with these regulations, ensuring that organizations can demonstrate compliance and avoid hefty fines.

In summary, an ideal solution for data loss prevention 2020 and data loss prevention 2018 should offer comprehensive coverage, advanced detection and response capabilities, a user-friendly interface with seamless integration, and robust compliance management. By incorporating these key features, organizations can effectively safeguard their sensitive data and stay ahead of evolving cyber threats.

Strac: Leading the Way in Data Loss Prevention

Strac stands out as a premier SaaS and Cloud DLP solution, offering a comprehensive suite of features designed to protect sensitive data effectively. Here are some of the key aspects of Strac:

• Built-In & Custom Detectors: Strac supports detectors for PCI, HIPAA, GDPR, and other confidential data. It also allows for customization, enabling customers to configure their own data elements. Strac is unique in its ability to detect and redact sensitive information in images (jpeg, png, screenshot) and perform deep content inspection on various document formats, such as PDFs and Word docs. Explore Strac’s full catalog of sensitive data elements.
• Compliance: Strac helps organizations achieve compliance with PCI, SOC 2, HIPAA, ISO-27001, CCPA, GDPR, and NIST frameworks. For more details, check out Strac's compliance resources for PCI, SOC 2, HIPAA, ISO 27001, CCPA, and NIST.
• Ease of Integration: Strac allows for quick integration, enabling customers to see DLP/live scanning/live redaction on their SaaS apps within minutes.
• Accurate Detection and Redaction: Utilizing custom machine learning models trained on sensitive PII, PHI, PCI, and confidential data, Strac ensures high accuracy with low false positives and negatives.
• Rich and Extensive SaaS Integrations: Strac offers the widest and deepest number of SaaS and Cloud integrations. Discover all integrations.
• AI Integration: Strac integrates with LLM APIs and AI websites like ChatGPT, Google Bard, and Microsoft Copilot, providing protection for AI applications and sensitive data. Learn more in Strac's Developer Documentation.
• Endpoint DLP: Strac is a comprehensive DLP solution that works across SaaS, Cloud, and Endpoint environments. Explore Strac's Endpoint DLP.
• API Support: Strac offers APIs for developers to detect or redact sensitive data. Check out the Strac API Docs.
• Inline Redaction: Strac can redact (mask or blur) sensitive text within any attachment.
• Customizable Configurations: Strac provides out-of-the-box compliance templates and flexible configurations to meet specific business needs, ensuring alignment with data protection measures.

• Happy Customers: See what our customers are saying about Strac on G2

In conclusion, Data Loss Prevention 2020 and Data Loss Prevention 2018 brought significant advancements in protecting sensitive information. Strac, with its modern features and robust capabilities, remains a leader in the DLP space, offering comprehensive solutions that address the diverse needs of organizations.