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It's Time to Embrace Cloud DLP and DSPM

March 11, 2024
4
 Min Read
Data Loss Prevention

What’s the best way to prevent data exfiltration or exposure? In years past, the clear answer was often data loss prevention (DLP) tools. But today, the answer isn’t so clear — especially in light of the data democratization trend and for those who have adopted multi-cloud or cloud-first strategies.

 

Data loss prevention (DLP) emerged in the early 2000s as a way to secure web traffic, which wasn’t encrypted at the time. Without encryption, anyone could tap into data in transit, creating risk for any data that left the safety of on-premise storage. As Cyber Security Review describes, “The main approach for DLP here was to ensure that any sensitive data or intellectual property never saw the outside web. The main techniques included (1) blocking any actions that copy or move data to unauthorized devices and (2) monitoring network traffic with basic keyword matching.”

Although DLP has evolved for securing endpoints, email and more, its core functionality has remained the same: gatekeeping data within a set perimeter. But, this approach simply doesn’t perform well in cloud environments, as the cloud doesn’t have a clear perimeter. Instead, today’s multi-cloud environment includes constantly changing data stores, infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS) and more.

And thanks to data democratization, people across an organization can access all of these areas and move, change, or copy data within seconds. Cloud applications do so as well—even faster.

Traditional DLP tools weren’t built for cloud-native environments and can cause significant challenges for today’s organizations. Data security teams need a new approach, purpose-built for the realities of the cloud, digital transformation and today’s accelerated pace of innovation.

Why Traditional DLP Isn’t Ideal for the Cloud

Traditional DLPs are often unwieldy for the engineers who must work with the solution and ineffective for the leaders who want to see positive results and business continuity from the tool. There are a few reasons why this is the case:

1. Traditional DLP tools often trigger false alarms.

Traditional DLPs are prone to false positives. Because they are meant to detect any sensitive data that leaves a set perimeter, these solutions tend to flag normal cloud activities as security risks. For instance, traditional DLP is notorious for erroneously blocking apps and services in IaaS/PaaS environments. These “false positives” disrupt business continuity and innovation, which is frustrating for users who want to use valuable cloud data in their daily work. Not only do traditional DLPs block the wrong signals, but they also overlook the right ones, such as suspicious activities happening over cloud-based applications like Slack, Google Drive or generative AI/LLM apps. Plus, traditional DLP doesn’t follow data as users move, change or copy it, meaning it can easily miss shadow data.

2. Traditional DLP tools cause alert fatigue.

In addition, these tools lack detailed data context, meaning that they can’t triage alerts based on severity. Combine this factor with the high number of false positives, and teams end up with an overwhelming list of alerts that they must sort manually. This reality leads to alert fatigue and can cause teams to overlook legitimate security issues.

3. Traditional DLP tools rely on lots of manual intervention.

Traditional DLP deployment and maintenance take up lots of time and resources for a cloud-based or hybrid organization. For instance, teams must often install several legacy agents and proxies across the environment to make the solution work accurately. Plus, these legacy tools rely on clear-cut data patterns and keywords to uncover risk. These patterns are often hidden or nonexistent because they are often disguised or transformed in the data that exists in or moves to cloud environments. This means that teams must manually tune their DLP solution to align with what their sensitive cloud data actually looks like. In many cases, this manual intervention is very difficult—if not impossible—since many cloud pipelines rely on ETL data, which isn’t easy to manually alter or inspect. 

Additionally, today’s organizations use vast amounts of unstructured data within cloud file shares such as Sharepoint. They must parse through tens or even hundreds of petabytes of this unstructured data, making it challenging to find hidden sensitive data. Traditional DLP solutions lack the technology that would make this process far easier, such as AI/ML analysis.

Cloud DLP: A Cloud-Native Approach to Data Loss Prevention

Because the cloud is so different from traditional, on-premise environments, today’s cloud-based and hybrid organizations need a new solution. This is where a cloud DLP solution comes into the picture. We are seeing lots of cloud DLP tools hit the market, including solutions that fall into two main categories:

SaaS DLP products that leverage APIs to provide access control. While these products help to protect from loss within some SaaS applications, they are limited in scope, only covering a small percentage of the cloud services that a typical cloud-native organization uses. These limitations mean that a SaaS DLP product can’t provide a truly comprehensive view of all cloud data or trace data lineage if it’s not based in the cloud. 

IaaS + PaaS DLP products that focus on scanning and classifying data. Some of these tools are simply reporting tools that uncover data but don’t take action to remediate any issues. This still leaves extra manual work for security teams. Other IaaS + PaaS DLP offerings include automated remediation capabilities but can cause business interruptions if the automation occurs in the wrong situation.  

To directly address the limitations inherent in traditional DLPs and avoid these pitfalls, next-generation cloud DLPs should include the following:

  • Scalability in complex, multi-cloud environments
  • Automated prioritization for detected risks based on rich data context
  • Auto-detection and remediation capabilities that use deep context to correct configuration issues, creating efficiency without blocking everyday activities
  • Integration and workflows that are compatible with your existing environments
  • Straightforward, cloud-native agentless deployment without extensive tuning or maintenance


Attribute Cloud DLP DSPM DDR
Security Use Case Data Leakage Prevention Data Posture Improvement, Compliance Threat Detection and Response
Environments SaaS, Cloud Storage, Apps Public Cloud, SaaS and OnPremises Public Cloud, SaaS, Networks
Risk Prioritization Limited: based only on predefined policies - not based on discovered data or data context Analyzes Data Context, Access Controls, and Vulnerabilities Threat Activity Context such as anomalous traffic, volume, access
Remediation Block or Redact Data Transfers, Encryption, Alert Alerts, IR/Tool Integration & Workflow Initiation Alerts, Revoke Users/Access, Isolate Data Breach

Further Enhancing Cloud DLP by Integrating DSPM & DDR

While Cloud Data Loss Prevention (DLP) helps to secure data in multi-cloud environments by preventing loss, DSPM and DDR capabilities can complete the picture. These technologies add contextual details, such as user behavior, risk scoring and real-time activity monitoring, to enhance the accuracy and actionability of data threat and loss mitigation. Data Security Posture Management (DSPM) enforces good data hygiene no matter where the data resides. It takes a proactive approach, significantly reducing data exposure by preventing employees from taking risky actions in the first place. Data Detection and Response (DDR) alerts teams to the early warning signs of a breach, including suspicious activities such as data access by an unknown IP address. By bringing together Cloud DLP, DSPM and DDR, your organization can establish holistic data protection with both proactive and reactive controls. There is already much overlap in these technologies. As the market evolves, it is likely they will continue to combine into holistic cloud-native data security platforms.  


Sentra’s data security platform brings a cloud-native approach to DLP by automatically detecting and remediating data risks at scale. Built for complex multi-cloud and premise environments, Sentra empowers you with a unified platform to prioritize all of your most critical data risks in near real-time.

Request a demo to learn more about our cloud DLP, DSPM and DDR offerings.

David Stuart is Senior Director of Product Marketing for Sentra, a leading cloud-native data security platform provider, where he is responsible for product and launch planning, content creation, and analyst relations. Dave is a 20+ year security industry veteran having held product and marketing management positions at industry luminary companies such as Symantec, Sourcefire, Cisco, Tenable, and ZeroFox. Dave holds a BSEE/CS from University of Illinois, and an MBA from Northwestern Kellogg Graduate School of Management.

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Yoav Regev
Yoav Regev
January 15, 2025
3
Min Read

The Importance of Data Security for Growth: A Blueprint for Innovation

The Importance of Data Security for Growth: A Blueprint for Innovation

“For whosoever commands the sea commands the trade; whosoever commands the trade of the world commands the riches of the world, and consequently the world itself.” — Sir Walter Raleigh.

For centuries, power belonged to those who ruled the seas. Today, power belongs to those who control and harness their data’s potential. But let’s face it—many organizations are adrift, overwhelmed by the sheer volume of data and rushing to keep pace in a rapidly shifting threatscape. Navigating these waters requires clarity, foresight, and the right tools to stay afloat and steer toward success. Sound familiar? 

In this new reality, controlling data now drives success. But success isn’t just about collecting data, it’s about being truly data-driven. For modern businesses, data isn’t just another resource. Data is the engine of growth, innovation, and smarter decision-making. Yet many leaders still grapple with critical questions:

  • Are you really in control of your data?
  • Do you make decisions based on the insights your data provides?
  • Are you using it to navigate toward long-term success?

In this blog, I’ll explore why mastering your data isn’t just a strategic advantage—it’s the foundation of survival in today’s competitive market - Data is the way to success and prosperity in an organization. I’ll also break down how forward-thinking organizations are using comprehensive Data Security Platforms to navigate this new era where speed, innovation, and security can finally coexist.

The Role of Data in Organizational Success

Data drives innovation, fuels growth, and powers smart decision-making. Businesses use data to develop new products, improve customer experiences, and maintain a competitive edge. But let’s be clear, collecting vast amounts of data isn’t enough. True success comes from securing it, understanding it, and putting it to work effectively.

If you don’t fully understand or protect your data, how valuable can it really be?

Organizations face a constant barrage of threats: data breaches, shadow data, and excessive access permissions. Without strong safeguards, these vulnerabilities don’t just pose risks—they become ticking time bombs.

For years, controlling and understanding your data was impossible—it was a complex, imprecise, expensive, and time-consuming process that required significant resources. Today, for the first time ever, there is a solution. With innovative approaches and cutting-edge technology, organizations can now gain the clarity and control they need to manage their data effectively!

With the right approach, businesses can transform their data management from a reactive process to a competitive advantage, driving both innovation and resilience. As data security demands grow, these tools have evolved into something much more powerful: comprehensive Data Security Platforms (DSPs). Unlike basic solutions, you can expect a data security platform to deliver advanced capabilities such as enhanced access control, real-time threat monitoring, and holistic data management. This all-encompassing approach doesn’t just protect sensitive data—it makes it actionable and valuable, empowering organizations to thrive in an ever-changing landscape.

Building a strong data security strategy starts with visionary leadership. It’s about creating a foundation that not only protects data but enables organizations to innovate fearlessly in the face of uncertainty.

The Three Key Pillars for Securing and Leveraging Data

1. Understand Your Data

The foundation of any data security strategy is visibility. Knowing where your data is stored, who has access to it, and what sensitive information it contains is essential. Data sprawl remains a challenge for many organizations. The latest tools, powered by automation and intelligence, provide unprecedented clarity by discovering, classifying, and mapping sensitive data. These insights allow businesses to make sharper, faster decisions to protect and harness their most valuable resource.

Beyond discovery, advanced tools continuously monitor data flows, track changes, and alert teams to potential risks in real-time. With a complete understanding of their data, organizations can shift from reactive responses to proactive management.

2. Control Your Data

Visibility is the first step; control is the next. Managing access to sensitive information is critical to minimizing risk. This involves identifying overly broad permissions and ensuring that access is granted only to those who truly need it.

Having full control of your data becomes even more challenging when data is copied or moved between environments—such as from private to public or from encrypted to unencrypted. This process creates "similar data," in which data that was initially secure becomes exposed to greater risk by being moved into a lower environment. Data that was once limited to a small, regulated group of identities (users) then becomes accessible by a larger number of users, resulting in a significant loss of control.

Effective data security strategies go beyond identifying these issues. They enforce access policies, automate corrective actions, and integrate with identity and access management systems to help organizations maintain a strong security posture, even as their business needs change and evolve. In addition to having robust data identification methods, it’s crucial to prioritize the implementation of access control measures. This involves establishing Role-based Access Control (RBAC) and Attribute-based Access Control (ABAC) policies, so that the right users have permissions at the right times.

3. Monitor Your Data

Real security goes beyond awareness—it demands a dynamic approach. Real-time monitoring doesn’t just detect risks and threats; it anticipates them. By spotting unusual behaviors or unauthorized access early, businesses can preempt incidents and maintain trust in an increasingly volatile digital environment. Advanced tools provide visibility into suspicious activities, offer real-time alerts, and automate responses, enabling security teams to act swiftly. This ongoing oversight ensures that businesses stay resilient and adaptive in an ever-changing environment.

Being Fast and Secure

In today’s competitive market, speed drives success—but speed without security is a recipe for disaster. Organizations must balance rapid innovation with robust protection.

Modern tools streamline security operations by delivering actionable insights for faster, more informed risk responses. A comprehensive Data Security Platform goes further by integrating security workflows, automating threat detection, and enabling real-time remediation across multi-cloud environments. By embedding security into daily processes, businesses can maintain agility while protecting their most critical assets.

Why Continuous Data Security is the Key to Long-Term Growth

Data security isn’t a one-and-done effort—it’s an ongoing commitment. As businesses scale and adopt new technologies, their data environments grow more complex, and security threats continue to evolve. Organizations that continuously understand and control their data are poised to turn uncertainty into opportunity. By maintaining this control, they sustain growth, protect trust, and future-proof their success.

Adaptability is the foundation of long-term success. A robust data security platform evolves with your business, providing continuous visibility, automating risk management, and enabling proactive security measures. By embedding these capabilities into daily operations, organizations can maintain speed and agility without compromising protection.

In today’s data-driven world, success hinges on making informed decisions with secure data. Businesses that master continuous data security will not only safeguard their assets but also position themselves to thrive in an ever-changing competitive landscape.

Conclusion: The Critical Link Between Data Security and Success

Data is the lifeblood of modern businesses, driving growth, innovation, and decision-making. But with this immense value comes an equally immense responsibility: protecting it. A comprehensive data security platform goes beyond the basics, unifying discovery, classification, access governance, and real-time protection into a single proactive approach. True success in a data-driven world demands more than agility—it requires mastery. Organizations that embrace data security as a catalyst for innovation and resilience are the ones who will lead the way in today’s competitive landscape.

The question is: Will you lead the charge or risk being left behind? The opportunity to secure your future starts now.

Final thought: In my work with organizations across industries, I’ve seen firsthand how those who treat data security as a strategic enabler, rather than an obligation, consistently outperform their peers. The future belongs to those who lead with confidence, clarity, and control.

If you're interested in learning how Sentra's Data Security Platform can help you understand and protect your data to drive success in today’s competitive landscape, request a demo today.

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Yair Cohen
Yair Cohen
January 13, 2025
4
Min Read
Data Security

Automating Sensitive Data Classification in Audio, Image and Video Files

Automating Sensitive Data Classification in Audio, Image and Video Files

The world we live in is constantly changing. Innovation and technology are advancing at an unprecedented pace. So much innovation and high tech. Yet, in the midst of all this progress, vast amounts of critical data continue to be stored in various formats, often scattered across network file shares network file shares or cloud storage. Not just structured documents—PDFs, text files, or PowerPoint presentations - we're talking about audio recordings, video files, x-ray images, engineering charts, and so much more.

How do you truly understand the content hidden within these formats? 

After all, many of these files could contain your organization’s crown jewels—sensitive data, intellectual property, and proprietary information—that must be carefully protected.

Importance of Extracting and Understanding Unstructured Data

Extracting and analyzing data from audio, image and video files is crucial in a data-driven world. Media files often contain valuable and sensitive information that, when processed effectively, can be leveraged for various applications.

  • Accessibility: Transcribing audio into text helps make content accessible to people with hearing impairments and improves usability across different languages and regions, ensuring compliance with accessibility regulations.
  • Searchability: Text extraction enables indexing of media content, making it easier to search and categorize based on keywords or topics. This becomes critical when managing sensitive data, ensuring that privacy and security standards are maintained while improving data discoverability.
  • Insights and Analytics: Understanding the content of audio, video, or images can help derive actionable insights for fields like marketing, security, and education. This includes identifying sensitive data that may require protection, ensuring compliance with privacy regulations, and protecting against unauthorized access.
  • Automation: Automated analysis of multimedia content supports workflows like content moderation, fraud detection, and automated video tagging. This helps prevent exposure of sensitive data and strengthens security measures by identifying potential risks or breaches in real-time.
  • Compliance and Legal Reasons: Accurate transcription and content analysis are essential for meeting regulatory requirements and conducting audits, particularly when dealing with sensitive or personally identifiable information (PII). Proper extraction and understanding of media data help ensure that organizations comply with privacy laws such as GDPR or HIPAA, safeguarding against data breaches and potential legal issues.

Effective extraction and analysis of media files unlocks valuable insights while also playing a critical role in maintaining robust data security and ensuring compliance with evolving regulations.

Cases Where Sensitive Data Can Be Found in Audio & MP4 Files

In industries such as retail and consumer services, call centers frequently record customer calls for quality assurance purposes. These recordings often contain sensitive information like personally identifiable information (PII) and payment card data (PCI), which need to be safeguarded. In the media sector, intellectual property often consists of unpublished or licensed videos, such as films and TV shows, which are copyrighted and require protection with rights management technology. However, it's common for employees or apps to extract snippets or screenshots from these videos and store them on personal drives or in unsecured environments, exposing valuable content to unauthorized access.

Another example is when intellectual property or trade secrets are inadvertently shared through unsecured audio or video files, putting sensitive business information at risk - or simply a leakage of confidential information such as non-public sales figures for a publicly traded company. Serious damage can occur to a public company if a bad actor got a hold of an internal audio or video call recording in advance where forecasts or other non-public sales figures are discussed. This would likely be a material disclosure requiring regulatory reporting (ie., for SEC 4-day material breach compliance).

Discover Sensitive Data in MP4s and Audio with Sentra

AI-powered technologies that extract text from images, audio, and video are built on advanced machine learning models like Optical Character Recognition (OCR) and Automatic Speech Recognition (ASR)

OCR converts visual text in images or videos into editable, searchable formats, while ASR transcribes spoken language from audio and video into text. These systems are fueled by deep learning algorithms trained on vast datasets, enabling them to recognize diverse fonts, handwriting, languages, accents, and even complex layouts. At scale, cloud computing enables the deployment of these AI models by leveraging powerful GPUs and scalable infrastructure to handle high volumes of data efficiently. 

The Sentra Cloud-Native Platform integrates tools like serverless computing, distributed processing, and API-driven architectures, allowing it to access these advanced capabilities that run ML models on-demand. This seamless scaling capability ensures fast, accurate text extraction across the global user base.

Sentra is rapidly adopting advancements in AI-driven text extraction. A few examples of recent advancements are Optical Character Recognition (OCR) that works seamlessly on dynamic video streams and robust Automatic Speech Recognition (ASR) models capable of transcribing multilingual and domain-specific content with high accuracy. Additionally, innovations in pre-trained transformer models, like Vision-Language and Speech-Language models, enable context-aware extractions, such as identifying key information from complex layouts or detecting sentiment in spoken text. These breakthroughs are pushing the boundaries of accessibility and automation across industries, and enable data security and privacy teams to achieve what was previously thought impossible.

Large volume of sensitive data was copied into a shared drive
Data at Risk - Data Activity Overview

Sentra: An Innovator in Sensitive Data Discovery within Video & Audio

Sentra’s innovative approach to sensitive data discovery goes beyond traditional text-based formats, leveraging advanced ML and AI algorithms to extract and classify data from audio, video, and images. Extracting and understanding unstructured data from media files is increasingly critical in today’s data-driven world. These files often contain valuable and sensitive information that, when properly processed, can unlock powerful insights and drive better decision-making across industries. Sentra’s solution contextualizes multimedia content to highlight what matters most for your unique needs, delivering instant answers with a single click—capabilities we believe set us apart as the only DSPM solution offering this level of functionality.

As threats continue to evolve across multiple vectors, including text, audio, and video—solution providers must constantly adopt new techniques for accurate classification and detection. AI plays a critical role in enhancing these capabilities, offering powerful tools to improve precision and scalability. Sentra is committed to driving innovation by leveraging these advanced technologies to keep data secure.

Want to see it in action? Request a demo today and discover how Sentra can help you protect sensitive data wherever it resides, even in image and audio formats.

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Team Sentra
Team Sentra
December 9, 2024
3
Min Read
Data Security

8 Holiday Data Security Tips for Businesses

8 Holiday Data Security Tips for Businesses

As the end of the year approaches and the holiday season brings a slight respite to many businesses, it's the perfect time to review and strengthen your data security practices. With fewer employees in the office and a natural dip in activity, the holidays present an opportunity to take proactive steps that can safeguard your organization in the new year. From revisiting access permissions to guarding sensitive data access during downtime, these tips will help you ensure that your data remains protected, even when things are quieter.

Here's how you can bolster your business’s security efforts before the year ends:

  1. Review Access and Permissions Before the New Year
    Take advantage of the holiday downtime to review data access permissions in your systems. Ensure employees only have access to the data they need, and revoke permissions for users who no longer require them (or worse, are no longer employees). It's a proactive way to start the new year securely.
  2. Limit Access to Sensitive Data During Holiday Downtime
    With many staff members out of the office, review who has access to sensitive data. Temporarily restrict access to critical systems and data for those not on active duty to minimize the risk of accidental or malicious data exposure during the holidays.
  3. Have a Data Usage Policy
    With the holidays bringing a mix of time off and remote work, it’s a good idea to revisit your data usage policy. Creating and maintaining a data usage policy ensures clear guidelines for who can access what data, when, and how, especially during the busy holiday season when staff availability may be lower. By setting clear rules, you can help prevent unauthorized access or misuse, ensuring that your data remains secure throughout the holidays, and all the way to 2025.
  4. Eliminate Unnecessary Data to Reduce Shadow Data Risks
    Data security risks increase as long as data remains accessible. With the holiday season bringing potential distractions, it's a great time to review and delete any unnecessary sensitive data, such as PII or PHI, to prevent shadow data from posing a security risk as the year wraps up with the new year approaching.
  5. Apply Proper Hygiene to Protect Sensitive Data
    For sensitive data that must exist, be certain to apply proper hygiene such as masking/de-identification, encryption, logging, etc., to ensure the data isn’t improperly disclosed. With holiday sales, year-end reporting, and customer gift transactions in full swing, ensuring sensitive data is secure is more important than ever. Many stores have native tools that can assist (e.g., Snowflake DDM, Purview MIP, etc.).
  6. Monitor Third-Party Data Access
    Unchecked third-party access can lead to data breaches, financial loss, and reputational damage. The holidays often mean new partnerships or vendors handling seasonal activities like marketing campaigns or order fulfillment. Keep track of how vendors collect, use, and share your data. Create an inventory of vendors and map their data access to ensure proper oversight, especially during this busy time.
  7. Monitor Data Movement and Transformations
    Data is dynamic and constantly on the move. Monitor whenever data is copied, moved from one environment to another, crosses regulated perimeters (e.g., GDPR), or is ETL-processed, as these activities may introduce new sensitive data vulnerabilities. The holiday rush often involves increased data activity for promotions, logistics, and end-of-year tasks, making it crucial to ensure new data locations are secure and configurations are correct.
  8. Continuously Monitor for New Data Threats
    Despite our best protective measures, bad things happen. A user’s credentials are compromised. A partner accesses sensitive information. An intruder gains access to our network. A disgruntled employee steals secrets. The holiday season’s unique pressures and distractions increase the likelihood of these incidents. Watch for anomalies by continually monitoring data activity and alerting whenever suspicious things occur—so you can react swiftly to prevent damage or leakage, even amid the holiday bustle. A user’s credentials are compromised. A partner accesses sensitive information. An intruder gains access to our network. A disgruntled employee steals secrets. Watch for these anomalies by continually monitoring data activity and alerting whenever suspicious things occur - so you can react swiftly to prevent damage or leakage.

Wrapping Up the Year with Stronger Data Security

By taking the time to review and update your data security practices before the year wraps up, you can start the new year with confidence, knowing that your systems are secure and your data is protected. Implementing these simple but effective measures will help mitigate risks and set a strong foundation for 2025. Don't let the holiday season be an excuse for lax security - use this time wisely to ensure your organization is prepared for any data security challenges the new year may bring.

Visit Sentra's demo page to learn more about how you can ensure your organization can stay ahead and start 2025 with a stronger data security posture.

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