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What is Enterprise DLP? What are Key Requirements of DLP?

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Category: Cybersecurity PRISM
The data is at the heart of whole IT and is the chief concern of cybersecurity…
 
Your company data consists of its intellectual property (IP), financial info and personal identifiable information (PII) of your customers and employees. All data that is confidential in nature, it vulnerable to attacks from cyber-attackers. There are so many potential issues which may expose your important data to outside world. 
 
 
 
 
An IBM report has suggested that - in 2020, the average cost of one data-breach was estimated at $3.86 million. Companies in sectors like healthcare, education, pharmaceuticals, financial services, and communications etc had to bear the higher cost per breach. Data breaches not only cost your business, they cause irreparable reputational harm to your company. The report also suggested that it takes an average of 280 days to identify and contain a breach.
 
Data leakage or breach is an ongoing challenge that requires continuous vigilance by your security teams. It’s vital for your organization to adopt data loss prevention (DLP) strategies to prioritize data security.
 
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👉 What is Enterprise Data Loss Prevention?
 
Data loss prevention (DLP) is a security STRATEGY that ensures that your sensitive or confidential information doesn’t leak outside of your corporate network in a way that is unsafe or non-compliant as per regulations.
 
Your company might be collecting some massive amounts of data, but where it stores this data?
 
Most likely, you data is stored at so many places. It can be stored at public clouds, it can be at your private cloud, it can be stored at SaaS applications' platforms, it can be stored at your data-center at HQ, it can be stored at your branch office networks.
 
Not only your data is spread at so many places, the access patterns of your users and employees are also create a number of security challenges too, as they access your data from number of locations, using a number of computing methods, devices, and mobile technologies.
 
The combination of these factors alone creates some severe challenges for security of your data...For example,
 
  • You company may NOT have a granular visibility into what, how, and where your employees access and use your data, or transfer and share it with others.
  • Your company may have only limited control over your data that is stored in the cloud, which creates security gaps.
  • You company may have inconsistency of data security due to the varying security capabilities of public and private cloud providers, network security, and SaaS, etc.
  • You company may be facing a growing number of data breaches and insider threats caused by well-meaning employees, malicious insiders, and/or by outside cyber-criminals.
 
An effective Data Loss Prevention (DLP) strategy is an answer to these challenges. You must develop a sound DLP strategy that requires you to discover and secure your data while it is at rest, in use, and in motion. You need to build mechanisms to monitor the transmission of data both inside and outside of your organization. You need solutions to proactively detect and stop data leakage/breach.
 
DLP is a fundamentally different approach when we compare it to Threat-Prevention systems. DLP systems watch for data on the move and restrict where it can go. They are there to MONITOR what is being moved and then CONTROL its movement. Let me give you some examples...
 
  • DLP systems can look for someone sending a huge database full of personal info (PII).
  • DLP systems can even look at an image file that has a screenshot and detect a single social security number, if it is being sent to internet by an insider.
 
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👉👉 What are Key Requirements of DLP?

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 1. DISCOVERY, RETENTION, SEARCHING
 
You DLP solution should be able to analyze your networks for data At Rest (on endpoints, servers, and file shares), In Use, and In Motion (on the network, over email, over messaging apps, and in web traffic, as well as any data being copied onto external devices). Here, I am trying to elaborating upon this set of features, you would need in your DLP implementation...
 
[A] Discovery :
It should have ability to automatically discover the following data:
 
  • Unmarked or unknown data Marks, indexes, and securely retains them
  • Unfiltered data analyzed by network sensors
  • Unfiltered files that have been analyzed from end points and servers
  • Unfiltered files analyzed from Wiki, FTP and Web servers
  • Documents sent over unfiltered traffic
 
[B] Retention
Your DLP solution should be capable of fingerprinting files of all types. It should register all files of folders by fingerprinting. Since fingerprinting may take a lot time, it should quickly build an inventory of all files, regardless they have been fingerprinted or not.
 
 
[C] Search
Since the search feature is one of most important requirements, you want that your DLP solution is capable of presenting search results based on number of parameters. For example,
  • Search based on specified time periods
  • Search for indexed content based on: Keywords, expressions, content patterns, document type (Word, Excel, CAD, etc.)
  • Hash functions (i.e., MD5 hash)
  • Location, system/device type File owner, port, path, age of file
 
Here, you would expect some built-in Actions and tools related to:
 
  • The operating system (e.g., clipboard, screen capture)
  • Email and email attachments, based on specified sender/recipient
  • Applications, including Web applications
  • Other tools (i.e., not covered by existing rules, client defined)
 
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2. MONITORING
 
It is mandatory that they can discover, identify, correlate, analyze, and log EVERY INSTANCE of sensitive data movement or use (removal, modification, or attempted transmission).
 
3. ALERTING
 
DLP system should be able to define and generate ALERTS that need to be taken when a violation or incident is detected based on the CONTENT (markers/registration), CONTEXT (how data is behaving), application, user, and location.
 
4. ENFORCEMENT
 
Given the same set of CONTENT, CONTEXT, application, user, and location, your DLP system should be capable of implementing some pre-defined ACTIONS (e.g., allow, block, reject, quarantine, encrypt, drop, and delete) as measures of enforcement when a violation or incident is detected.
 
5. RULE SUPPORT
They should provide you an ability to centrally define, manage, and deploy flexible RULES as well as automate remediation actions based on policy violation.
 
 
If a potential violation is found, a DLP solution will trigger a remediation based on policies and rules defined by your organization, for example, they can alerting IT, they can automatically enforcing encryption of data, or locking down a user to prevent sharing data that could put your organization at risk. DLP solutions will also produce reporting that can help your organization meet regulatory compliance.
 
But issue is that the legacy DLP systems were never designed with the cloud in mind. Hence they don't do a good job when it comes to dealing with cloud-based storages as SaaS applications in particular.
 
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 👉 Enterprise DLP Platforms Have An Ultra-Edge
 
  1. Enterprise DLP technologies, are focused on the task of preventing sensitive data loss and providing comprehensive coverage. They provide coverage across the complete spectrum of leakage vectors.
  2. Significantly, Enterprise DLP addresses the full range of network protocols, including email, HTTP, HTTPS, FTP and other TCP traffic.
  3. Another critical distinction of most Enterprise DLP solutions is the depth and breadth of their sensitive data detection methodologies, which translates into that you will have a meaningful increases in your DLP effectiveness.
  4. Another unique and critical feature of these DLP solutions is a central management console. This means that you will not need for multiple management interfaces and it would significantly reduce the management overhead of your DLP initiative.
  5. Most modern DLP solutions are capable of protecting your data on cloud too...It does not matter to them where your data is located actually. They can effectively discover your all data, and automatically categorize into meaningful categories, by separating your most critical data from remaining data.
  6. They let you define the granular policies to protect each data category appropriately. They also come with ready-made templates to meet almost all sorts of regulatory compliances. They are superb in Alerting capabilities too.
  7. You can set up your custom-rules too. But the beauty is that most modern Enterprise DLP solutions are cloud-based and backed up by Machine Learning (ML)...That lets you to fine-tune your existing RULES far more efficiently than before. 
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This Article Was Written & published by Meena R,  Senior Manager - IT, at Luminis Consulting Services Pvt. Ltd, India. 

Over the past 16 years, Meena has built a following of IT professionals, particularly in Cybersecurity, Cisco Technologies, and Networking...

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