Understanding EDM and IDM in Data Loss Prevention


Updated on:

I’ve seen the devastating consequences of data loss prevention failures. The loss of sensitive information not only harms a company’s reputation, but it can also lead to serious legal consequences. That’s why it’s crucial to have a comprehensive understanding of all the tools in your arsenal, including EDM and IDM.

EDM, or Event Data Management, is a vital component of Data Loss Prevention (DLP) systems. It helps detect and analyze data breaches, enabling us to take rapid action in mitigating the situation before it becomes unmanageable. IDM, or Identity and Access Management, on the other hand, is the control and management of user identities and their access to data, helping to prevent unauthorized data access, theft, or modification.

Understanding EDM and IDM is essential for any cyber security expert looking to protect sensitive information from potential breaches. The psychology of hackers is that they look for the easiest path of entry in your systems, which makes EDM and IDM necessary components of a successful data loss prevention strategy. In this article, we’ll explore both EDM and IDM in more detail and how they work together to keep your data secure.

What is EDM and IDM in DLP?

EDM and IDM are both techniques used in data loss prevention (DLP) to identify and evaluate data. EDM stands for Exact Data Matching and IDM stands for Intelligent Data Matching. While they might sound similar, they are actually used in different ways.

  • EDM is used to identify individual cell values within an object, such as a spreadsheet or database. For example, if you want to make sure that a spreadsheet containing credit card numbers doesn’t leave your organization, you can use EDM to identify those specific cell values so that you can take action to prevent them from being shared.
  • IDM, on the other hand, looks at all the contents of an object and evaluates them against a known source. For instance, if you have a policy that says your organization’s confidential information should never leave your network, IDM can be set up to evaluate all outgoing communication against that policy. If a communication contains any information that matches the known confidential data, IDM can trigger a response to prevent the data from leaving your network.
  • Overall, DLP is a vital part of data security, and techniques like EDM and IDM can help organizations to prevent sensitive data from leaving their control.

    ???? Pro Tips:

    1. Understand the concept of DLP: To fully grasp the idea of EDM and IDM in DLP, it is crucial to first understand what DLP means. DLP stands for Data Loss Prevention which is a set of tools and policies to prevent unauthorized access, use, or transmission of sensitive information.

    2. Define EDM and IDM: EDM stands for Exact Data Matching which refers to the technique of comparing data values in a given database to data values in another database. IDM stands for Inexact Data Matching which refers to the attempt to match data that is not exactly the same.

    3. Know the difference between EDM and IDM: While both techniques – EDM and IDM – are used to compare data sets, the main difference is that EDM compares data strings that have to be exact matches while IDM looks for similarities but not necessarily a perfect match.

    4. Recognize the benefits of EDM and IDM in DLP: The use of EDM and IDM in DLP systems can significantly improve the accuracy and speed of detecting and preventing data leaks and insider threats. This is particularly useful for large organizations with extensive data sets.

    5. Understand the limitations of EDM and IDM: While EDM and IDM are useful techniques, they are not foolproof and may not be 100% accurate. Human errors in data entry, formatting, or duplication can lead to data mismatches, which can result in false positives or false negatives. Therefore, it is essential to have a thorough understanding of DLP, EDM, IDM, and their limitations.

    Understanding DLP

    Data Loss Prevention (DLP) is a vital security measure adopted by many organizations to safeguard their valuable and sensitive data. It is essentially a set of tools and technologies that are designed to ensure the confidentiality, integrity, and availability of sensitive data within the organization’s environment. DLP solutions come in many forms, including hardware, software, and cloud-based services, but they all share the common goal of preventing data leaks and unauthorized access to critical data.

    One of the key features of DLP solutions is their ability to classify and identify various forms of sensitive data within an organization. This is achieved through the use of content-aware technologies, which enable DLP systems to analyze data as it moves through the network and identify sensitive information based on predefined criteria. Two of the most commonly used content-aware technologies in DLP are EDM and IDM.

    What is EDM?

    EDM stands for Exact Data Matching, and it is a content-aware technology used in DLP to identify individual “cell” values within an object. In simpler terms, it refers to a process that matches an exact set of data to detect instances of data duplication. For instance, if a set of data contains an employee’s Social Security number, EDM can be used to identify any instances where that same Social Security number appears within the organization’s data fabric.

    How does EDM work in DLP?

    EDM works by analyzing data in real-time as it moves through the network. The DLP system maps the identified data, and when the system discovers an exact match, it triggers an alert or takes an appropriate action, such as encrypting or blocking the data. This process allows organizations to identify and prevent data leaks at the point of origin or even before the data can be sent.

    Benefits of using EDM in DLP

    Using EDM in DLP provides several benefits, including:

    • Ensuring the consistency of data across the organization
    • Detection of sensitive data duplication and misuse
    • Reduced risk of data loss and breach incidents

    EDM is an effective content-aware technology that can help organizations detect, prevent and remediate sensitive data exposure, misuse, and duplication.

    What is IDM?

    IDM stands for Inexact Data Matching, and it is a content-aware technology used in DLP to evaluate all content of an object against a source that is known by a certain percentage. IDM usually works with binary content such as images, audio, and video.

    IDM’s role in DLP

    IDM evaluates an entire object and compares it to an existing document’s source document to determine the similarity between them. For instance, suppose an employee tries to email a picture of a sensitive company document. In that case, IDM can analyze and compare the content of the image against the source document to determine if they are the same. Inexact Data Matching can also be used to identify content that is related to a sensitive document, but not an exact duplicate, such as an edited version of the document or a new document created using a portion of the original document.

    Advantages of using IDM in DLP

    Using IDM in DLP provides several benefits, including:

    • Detection of similar content that might be related to an original document but not an exact copy
    • Detection of sensitive data by analyzing binary content such as images, audio, and video
    • Reducing false positives by using a percentage threshold to compare documents.

    Using IDM in DLP helps organizations to identify all kinds of sensitive data and relate it to source documents. This content-aware technology can help organizations prevent data breaches, leaks, and misuse of sensitive information.

    In conclusion, DLP solutions play a critical role in safeguarding sensitive data within organizations. EDM and IDM are essential content-aware technologies used in DLP to ensure the confidentiality, integrity, and availability of sensitive data. EDM is used to identify individual “cell” values within an object, while IDM evaluates the entire content of an object and compares it to a source document with a certain percentage threshold. Using both technologies in DLP provides organizations with a comprehensive solution to address the risk of sensitive data exposure, misuse, and duplication.