Data is everywhere and growing rapidly. According to some estimates, people and systems create millions of terabytes of data every day, with unstructured data accounting for an estimated 80% of a company’s information. Data in the cloud is growing the most because there is practically no physical limit on storage compared to on-premise data centers.
Unstructured data tends to be inadequately managed and challenging to monitor and control. Users often transfer sensitive files to cloud services, email them, and save them on their laptops and mobile devices. When sharing with internal and external users, files move through collaboration applications, resulting in the distribution of more information across various platforms and geographies.
How can you safeguard sensitive data when much of it may be hidden from view?
To effectively address these challenges, it is essential to have a comprehensive understanding of the data’s whereabouts, its users, and its changes over its lifecycle. Improved visibility into the utilization and movement of sensitive data is imperative for meeting privacy regulations and safeguarding content. While traditional data discovery and classification tools can aid in identifying and labeling sensitive files for subsequent control measures, tracing data lineage to maintain this level of control requires in-depth visibility to track data as it moves, as users and systems access it, and as it transforms into other file formats.
Self-reporting Files
Security, privacy, and data governance groups are in a constant battle to track sensitive files as they are accessed by multiple systems, applications, and devices. This challenge grows as data visibility is limited when documents travel and change through duplication or revisions. Without proper visibility, you are not aware of who is sharing sensitive information and how it moves and changes.
The optimal strategy to address this challenge involves implementing a self-reporting file method, which automatically monitors and records all document interactions, eliminating the need to rely on the review of disparate network, application, and device logs. Self-reporting files contain metadata or embedded information that can automatically report details such as their origin, creation date, author, or any changes made to them. This technology serves as the cornerstone of a file-centric protection approach, effectively bridging the gap between privacy and security. It provides in-depth data visibility and a robust frontline defense for safeguarding your sensitive data.
Self-reporting files utilize an embedded ID to track and document all interactions. Traditional Data Loss Prevention (DLP) and Identity and Access Management (IAM) solutions, primarily designed for perimeter security, struggle to keep track of data that migrates to the cloud or is accessed by remote workers. While privacy and legal e-discovery applications may offer some file mapping features, they operate in isolation, failing to capture all interactions, and their multiple datasets remain disjointed and incomplete.
An embedded ID that travels with the file ensures persistent tracking and self-reporting of interactions, regardless of the file’s location. This eliminates the need to piece together data from various systems and simplifies incident and privacy response, making it more efficient.
The embedded ID approach significantly enhances the performance of your existing data visibility tools. Standard discovery scans often lack the intelligence to link file derivatives that have been copied or duplicated. This makes it difficult to establish data lineage, which can be a problem when trying to comply with privacy regulations. With an embedded ID, derivatives of an original file, whether duplicated or renamed, inherit the parent ID tag along with all its security and governance policies.
Employing an embedded ID reduces the need for multiple tracking applications for different security, privacy, and legal e-discovery systems, consolidating all applications around a single source of truth for file tracing and interactions. This approach is the most effective way to establish sustainable and auditable processes while enhancing the protection of sensitive data.
Control throughout your Supply Chain
Sharing files with supply-chain partners, as well as external legal and financial professionals, beyond the corporate network can lead to a loss of data visibility. Regulatory authorities hold you accountable for ensuring the proper protection of your data, regardless of location. In the event a data breach occurs while the data is in the custody of a third party, you are required to report it. Ultimately, you are responsible for privacy breaches of your data.
This becomes more important as your partners share sensitive data with their partners. If you share a CAD file with a partner who uses subcontractors to produce components for their assemblies, you want to control access to that data. Lots of companies use third-party payment and benefits processors for their business, and those processors use subs as part of their business workflows. Again, you need to maintain control of your data throughout these workflows.
Utilizing an embedded ID allows for the same level of activity tracking as if the files were kept within the internal network or another managed location. This also enables you to establish additional controls, including setting file expiration dates and the ability to revoke access at any time for third-party recipients. By implementing granular permission controls, you can ensure that only authorized users gain access to sensitive content.
User Behavior Monitoring
Monitoring solutions that aim to detect data misuse and policy violations rely on crucial information: tracking who accesses your data, how it’s utilized, and where it’s being transferred. Data transfers to removable drives and substantial uploads to cloud services can serve as early indicators of potential malicious insider threats. You can maximize the effectiveness of user behavior analytics when data visibility tools offer a comprehensive view of user activities across all applications and storage locations.
An embedded ID provides the highest level of granularity in tracking data activity, enabling earlier detection of insider threats. These valuable data insights trigger security measures, such as the restriction of data copying to removable drives and other destinations.
Meet Privacy and Security Needs
It’s been observed that “you can have security without privacy, but you can’t have privacy without security.” Both are tightly related and today, it’s not an either-or choice.
Using an embedded file ID to maintain continuous data visibility stands as the ideal solution to meet privacy and security demands. This approach embraces a “protect-first” security strategy, which secures data through encryption and access controls, thereby obviating the need for redundant tools across various networks and endpoints. It helps you establish data lineage to understand how files link to each other. It enhances data privacy and security by confining access to authorized users and maintains real-time awareness of the precise whereabouts of your sensitive data.
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