Data loss prevention (DLP) is a set of tools and processes, combined and implemented to ensure any regulated, confidential, business-critical and sensitive data is not stolen, misused or made accessible to unauthorized users. Most DLP implementations are driven by regulatory compliance requirements imposed by regulations such as GDPR, PCI-DSS, HIPAA, FISMA or SOX. DLP software allows for creation of rules that define violations with respect to use, copy and deletion of data, and also provides for one or more actions to be taken in the event of a violation of one or more predefined rules. The pre-defined actions can be one or a combination of alerts, warnings, blocking of the action, locking the user out, encryption of content in question, and more, with the ultimate goal to limit or prevent from accidental or malicious sharing of data, which could expose the organization to financial, regulatory and reputational risk. DLP software captures all rule violations in a log, with more advanced solutions offering full forensics data including a video recording of the actual event and reporting capabilities, with the goal to assist with incident management, forensics, breach disclosure and reporting requirements of the organization.
As this article is published, the business community at large and governments around the world are undergoing policy changes and are subject to an increased set of data privacy regulations that will require them to revisit and improve their data privacy and security implementations. According to the Privacy Rights Clearinghouse, there have been over 8,600 publicly reported data breaches since 2005. The Internet has only made data theft and leaks much easier, while making data security substantially more difficult.
Traditional DLP approaches primarily focus on network and file monitoring activity, with more modern, intelligent data loss prevention solutions taking an endpoint or user-centric approach to data loss prevention, combining multiple disciplines such as user activity monitoring, user behavior analytics, forensics and data loss prevention to substantially increase the effectiveness of the DLP implementation, and allow for better alignment between business needs and technology implementation. These next gen DLP solutions have a broader, more capable rules and policy management engine, with the ability to monitor user activity, analyze user behavior to dynamically assign risk, and identify anomalies beyond the purview of the traditional DLP systems which are primarily focused on the movement of content, and not a series of user actions. For example, an employee’s recent activity on job search sites would automatically increase the risk score for his/her activities as it pertains to extracting data from the company’s CRM system, triggering an alert for further analysis by the compliance team.
Every organization that collects, stores and uses Personally Identifiable Information (PII) about their customers and/or employees, Protected Health Information (PHI), collects or processes credit card data, or collects personal data from EU residents (in the form of name, address, email address, telephone number, etc.) is subject to a variety of regulations such as HIPAA, PCI-DSS and GDPR to appropriately store, restrict access and protect this sensitive and potentially confidential data.
In addition, organizations that create and own intellectual property need to implement appropriate data loss protection and prevention processes to minimize the risk of financial and reputational losses in the event of a data breach.
Last but not least, a data loss prevention solution can effectively monitor all data movement within an organization, monitoring data access for privileged users, third party vendors and the entire user population to identify inappropriate access or insider threats and stop data loss.
Recent policy developments have pushed businesses to increase their security efforts with new investments being made in employee education, process refinement and security technology implementations. With stronger security policies in place as a new universal business standard, data loss prevention (DLP) is once again top of mind. Many security experts see the renewed focus on DLP as being driven by heightened consumer awareness of data breaches and thus their demands to have higher levels of security for their data, as well as increased regulatory compliance and substantial fines for breach which drive companies to implement, review, and improve their data privacy and security practices with incremental investment in data loss prevention technologies, processes and oversight.
Selecting, installing, configuring and maintaining a data loss prevention system typically requires a substantial, up-front financial commitment for the software license, in addition to the hardware investment, and IT and compliance resources to manage and maintain the implementation. This leaves most SMBs exposed with respect to their compliance requirements and effective protection against malicious and accidental data loss.
At Teramind, we believe Cloud-based, managed solutions should be made available to all, removing the barriers to entry with respect to price and deployment cost. That’s why we offer Teramind DLP for Cloud, with full feature-parity to the enterprise product, with only a 5-user minimum and no commitment. Teramind DLP Cloud, 100% managed by Teramind, with no need to set up, configure and maintain a DLP platform. Teramind DLP is also available with private-cloud and on-premise deployment options for organizations who prefer to manage their DLP implementations. For more information about Teramind DLP, please visit here, take a guided tour of the platform or get a free 14-day trial with no commitment to see the platform perform with your own data.
With over 2000 customers on the Teramind platform since 2014, Teramind is a leader in Data Loss Prevention, with an integrated platform that goes beyond the traditional DLP approaches, delivering on the promise of an integrated, intelligent DLP solution that is based on user behavior, combining user activity monitoring, user behavior analytics, forensics and data loss prevention in a single unified platform, with a single common rules and policy creation and management environment, AD and SIEM integration.