Contents
- 1 Introduction
- 2 1. What Is DLP? Define DLP, Meaning and how it relates to Data Loss Prevention.
- 3 2. Data Loss Prevention Software- Why It Is Important
- 4 3. DLP Software Features
- 5 4. DLP Software Benefits
- 6 5. Ethics of DLP, privacy and compliance.
- 7 6. Real World Use Cases Across Industries.
- 8 7. Choosing The Right DLP Software For Your Needs.
- 9 8. Implementation Best Practices
- 10 9. Trends and Future Considerations Related to DLP Software
- 11 Conclusion
Introduction
- Quick context – given how we work today, particularly with the shift to virtual-remote working, protecting data has become critically baked into our efforts in many respects.
- Introduce DLP, meaning data loss prevention software.
1. What Is DLP? Define DLP, Meaning and how it relates to Data Loss Prevention.
- DLP Meaning – Data Loss Prevention: feel free to use other means to ensure we get across DLP meaning.
- Define data loss prevention as it relates to data loss, data movement or data misuse.
- Emphasize -(very simply) that data loss prevention is different than many traditional security tools.
2. Data Loss Prevention Software- Why It Is Important
- Define DLP Software- what it means for organizations today.
- Emphasize the significantly growing DLP Software importance for organizations in terms of compliance, productivity and the need to prevent data leaks.
- Discuss the adjacency of DLP for those organizations that handle sensitive information (HR files, client files, intellectual property).
3. DLP Software Features
- Insider Threat Prevention
- Misconduct Detection
- User Behavior Analytics
- Data Continuous Monitoring and analysis
- Employee Monitoring
- Discuss how the features work together to keep organization safe, and to provide organization wide oversight and organizational secrecy.
4. DLP Software Benefits
- Provides protection against malicious insiders and unintentional errors (ie. sending a sensitive document to the wrong person via email).
- Increases confidence in the auditing and compliance process.
- Decreases both financial and reputation risk.
5. Ethics of DLP, privacy and compliance.
- Discuss privacy concerns: How DLP will be used ethically and legally.
- Emphasize being transparent with employees and importance of compliance with GDPR, HIPAA, CCPA, etc.
- Discuss balancing the need for monitoring employees with keeping employees engaged and trusting.
6. Real World Use Cases Across Industries.
- Healthcare (for example, ensuring protections for patient data).
- Finance (for example, from a compliance perspective, PCI-DSS).
- Legal & Government (for example, ensuring protections are in place for confidential files).
- Tech & Manufacturing (for example, able to protect their intellectual property).
7. Choosing The Right DLP Software For Your Needs.
- Scalability, Integration, Ease of Use, Policy controls based to your needs
- Consider the needs of your business, and select the appropriate feature set.
- Select vendors that offer strong reporting and alert capabilities.
8. Implementation Best Practices
- Have a clearly defined data classification policy that makes the workflow intuitive.
- Be collaborative – IT, HR, Legal should all be engaged.
- Set realistic goals for implementation, and do roll out phase-in based.
- Teach your employees in training about DLP, how it works, and for improved data awareness and compliance.
9. Trends and Future Considerations Related to DLP Software
- AI and Behavioral Analysis
- Look for software that have cloud-native DLP solutions and can accommodate hybrid work because of increased demand for this space.
- Learn how the solution can integrate with the larger cyber security ecosystem (SIEM tools).
Conclusion
- Reiterate DLP need against data loss prevention software in our rapidly changing work environments.
- Summarize DLP meaning.
- Encourage organizations to realise DLP as not just a product, but a responsible and secure data management strategy.
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