Data Loss Prevention (DLP) refers to the application of software, tools, and techniques for maintaining confidentiality, integrity, and availability of data being processed, stored, or shared with other entities. DLP works in three simple steps i-e: (1) Discover, (2) Monitor, and (3) Protect the data. Some common terminologies used in place of Data Loss Prevention include Data Leak Prevention (DLP), Data Loss Protection (DLP), and Data Leak Protection (DLP). In DLP, deep content analysis of the target data is performed based on pre-defined policies. The categorization of DLP services is similar to SaaS (Software as a Service) and PaaS (Platform as a Service) of Cloud computing. DLP is also available as software, tools, and fully managed solution. The DLP software and tools are used to perform functions like monitoring, detecting, and sharing threat alerts with the authorities. It is the responsibility of the concerned departments to respond to the DLP alerts. On the other hand, the DLP solution is a fully managed system that can take care of all data loss prevention tasks, such as defining policies, installing tools, monitoring data flow, detecting anomalies, and applying appropriate remedies. There are a number of DLP solutions available in the market, offering a variety of services. The main objective of each DLP solution is to prevent the loss, misuse, and unauthorized access to data. However, selecting the right DLP solution is a complex job. Following is a brief summary of some important DLP features to be considered while choosing the DLP solution for businesses.
Identifying Data Protection Goals
Before searching for a DLP solution, it is important to know your data protection requirements. Organizations may require a DLP solution for personal data protection, compliance fulfillment, or intellectual property protection. Similarly, some organizations may require specific data protection features, such as endpoint security, network security, or Cloud security services. Once, these objectives are identified, it is easier to find the right DLP solution.
Data Lifecycle Protection Capabilities
The first DLP feature to consider is to see if the DLP solution offers data protection at all stages of the data lifecycle. The data lifecycle can be classified into the following phases.
Almost every organization encounters these data lifecycle phases. For example, a healthcare unit generates (1) patients’ data and saves (2) the information as Patient’s Medical Record (PMR). The PMR is later accessed (3) by the examiners while reviewing the patient’s medical history. The PMR is often shared (4) with other institutions for tasks like consultancy and clinical procedures. The data is frequently archived (5) with the production of new data. The data is destroyed (6) in circumstances like the patient’s expiration and discontinuity of medical services or consultancy. A good DLP solution provides data protection at all stages of the data lifecycle. Data generation tools and software are scanned for vulnerabilities like Trojans and other malware that can potentially harm or steal the data while being produced. Data storage is monitored to ensure no unauthorized access to the data. Smart DLP solution detects and prevents data usage by unintended users. Different safety measures like data encryption and digital signatures are used before sharing the data with other entities. The archived data is protected through various access control techniques. The unwanted sensitive data is professionally erased in a way that it cannot be retrieved by the adversaries. The organizations must inquire about the extent of data protection based on these data lifecycle steps. A DLP solution that offers standard DLP services for all stages of the data lifecycle is better than a DLP solution that provides extensive protection services for data at rest but does not guarantee the safety of data in motion.
Real-Time Data Analysis
Real-time analysis is probably the most important feature to consider while choosing a DLP solution. A DLP solution must be able to analyze data in real-time and report or respond to the anomalies. Alerts generated by a DLP solution in real-time can help organizations in taking manual actions besides the automated response by the DLP solution.
DLP Dashboard Features
The technical department or security experts may not be the only entities having access to the DLP solution dashboard. A DLP dashboard is a kind of interface that provides valuable insights and controls to the clients. Usually, administrative and security teams have access to the dashboard. But there may be non-technical personnel like managers, legal experts, etc. requiring access to the DLP dashboard as well. It is vital for a DLP solution provider to offer hierarchical-access based dashboard features to the clients. The hierarchical DLP management system helps in segmenting the technical and non-technical interfaces of the DLP dashboard, limiting the DLP controls and features to the intended users. A DLP solution that does not offer these features is not recommended for organizations that require a complete barrier between technical controls and non-technical entities having access to the DLP interfaces.
Content Analysis and Classification Techniques
An organization should know the data analysis and classification abilities of a DLP solution. A professional DLP solution knows how to analyze and classify the content using various techniques. There are many content analysis techniques like rule-based analysis, dictionary-based analysis, fingerprinting, and document matching. Each technique has its strength and weaknesses. For example, rule-based content analysis is the most common analytics technique that follows specific rules to quickly analyze structured data like credit card numbers, social security numbers, etc. However, this technique generates false-positive results for unstructured data. Therefore, it is important to understand what content analysis techniques are used by the DLP solutions. Similarly, there are many data classification techniques, such as decision tree, Bayesian classification, rule-based classification, and classification by back-propagation. A specialized DLP solution knows where to apply each classification technique in order to get the most accurate results.
There are a number of DLP solutions available claiming varying services to compete with the rival DLP solutions. Instead of falling prey to the lucrative features, organizations should look for the relevant features that must align with the data protection requirements of their businesses. The security experts of respective organizations should be given the task of identifying and verifying the desired DLP features offered by DLP solution providers.