Data Loss Prevention (DLP) is a technology used to secure data of an organization’s network, communications, emails, web applications, and data transfer mechanisms like FTP i.e. File transfer protocol.
DLP benefits companies on a larger scale, where it is used as a strategy by most companies. Companies that use DLP have a security strategy to detect, prevent data loss, and cyber-attacks. DLP is also used to eliminate unwanted data that will harm the system's security.
Data leakage prevention solutions are commonly used to classify and prioritize data security. The common features of DLP are as follows,
Monitoring: Provides more visibility about who is accessing the system's data and from where.
Filtering: data is filtered to restrict suspicious or unidentified activity.
Reporting: recording and maintaining reports will be done, when instant response and auditing will be needed.
Analysis: identifying weakness, suspicious behavior, and providing forensic context to security teams.
With these aspects, Data loss is prevented and managed efficiently.
DLP contains two-main technical approaches to work on the network,
Contextual analysis: This DLP technique is used only to format metadata or properties of the document like header, size, references, etc.
Content awareness: It determines if there is any sensitive information in the document. Reading and analysis of data are done for the whole document.
Modern DLP solutions combine these two to give better outcomes in cyber security. That is used for examination of data context analysis, if it’s insufficient or not fulfilling the needs, then content awareness is used to explore the data. There are multiple techniques used to trigger content analysis,
Data loss prevention is classified into three types, where all the three deliver same results with different methods.
Network DLP: Data loss prevention in-network helps to put a secure perimeter around the data that is in movement. In simple terms, network DLP is implemented on a system/network to monitor all the incoming and outgoing. It decides whether the data needs to be protected, monitored, or blocked.
Benefit: DLP can be applied on any device that is connected based on the given network.
Endpoint DLP: It monitors all endpoints i.e. servers, computers, laptops, mobile phones, and any other device on which data is used, moved, or saved. For example, USB connectors are used to connect PC and Phones, or pen drives are used to transfer data or copy data.
Benefit: This DLP software always protects data even if the system is offline, no matter if it’s a company’s network or a public network.
Cloud DLP: This DLP network service gives much stronger visibility and protection for sensitive data that will be imposed on SaaS and IaaS cloud services. Cloud data loss prevention network service includes social security, where data like emails, financial details, contacts will be made secure where access will be given to admin only.
Benefit: There is no requirement for software and hardware devices. This data loss protection server is stronger compared to other DLP solutions.
Having data loss prevention in your system will provide the following advantages,
At times even if there is high security, insiders, as well as outsiders/hackers, might get into the database. Having the mindset that the data is secure will do no good because unexpected data breaches can take place at any time. Measures should be taken and often examine also needs to be done to keep data secure.
Hence while using DLP solution, look out for the following:
Data loss prevention tools are helpful to prevent intrusion in the system and protect data. Here is a list of DLP software tools used in the prevention of data loss,
☀ SolarWinds data loss prevention
This data leakage prevention tool assists to secure data. It acts as a shield against accidental or malicious data loss. It also automates user access and activities and responds to cynical activity by investigating user events that will balance out the system needs.
It is a strong solution for larger networks, where it supports data loss prevention and monitors to support multiple standard agreements. And it saves time by creating simple visuals for a user to understand better.
☀ Symantec Data Loss Prevention
This tool/system offers data protection for endpoints, networks, cloud resources, and files from a central server.
☀ Check Point Data Loss Prevention
A collection of security products for different system services use data loss prevention as an immense protection strategy. This tool acts as SaaS i.e. Software as a Service.
☀ Teramind DLP
This tool focuses on user activity and describes to spot behavioral changes that indicate malicious activity or to discover sensitive data. It is also offered to be a SaaS or a virtual application.
☀ Digital Guardian Endpoint DLP
It acts as a data protection solution that covers windows, macOS, and Linux. For which the cloud acts as a central coordinating server.
☀ Code42 Insider
This specialized cloud-based service spots insider threats and contains a system recovery process, to redeem from loss and destruction.
☀ CA data protection
This tool is designed to protect OS i.e. operating systems mainframes that should be delivering two modules data discovery and security policy enforcement.
☀ Comodo MYDLP
This data loss prevention tool observes activities that take place on the web, emails, printers, and removable devices like CDs, pen drives, to block all system exits. It runs over Hyper-V or VMware as a virtual appliance.
Suggested course: CompTIA Security training
DLP combines technology, process controls, knowledgeable staff, and employee awareness by implementing the following best practices,
Implement a single centralized DLP program
Many organizations oppose implementing DLP cyber security practices in their system, where various business units try and implement DLP solutions. With this inconsistency, the visibility of data goes down and weak data security takes place. Hence centralizing DLP solutions is a need.
Evaluate internal resources
To create and execute a DLP plan the organization needs a staff of experts in DLP, where they should comprise DLP risk analysis, data breach reporting, data protection laws, and DLP training and awareness. And some of the regulations need organizations to either retain their external consultants or employ their internal staff with data protection knowledge.
In simple terms, the staff needs to analyze overall DLP solution resources to give security to data in a better way.
Conduct an inventory and assessment
The evolution of data types and value to the organization is an important step to implement any DLP solution. Where it should embrace data relevancy, data storage, and analyze whether the stored data is sensitive, intellectual, and confidential or does it regulate any data address.
Some of the DLP products manage to identify information assets with the help of metadata of files and record the result or analyze the content by opening the files. The next step is risk assessment, where data is analyzed and reconsidered near the exit points. If there is any loss of data then the organization is held responsible, and necessary actions are taken.
Implement in Phases
Data loss prevention is a lengthy process that is implemented in a sequence. The effective way to implement DLP is by prioritizing types of data and communication channels. Similarly, consider implementing DLP software components based on the organization's priorities, rather combining them all at once.
Create a classification system
Before an organization/company can create and execute DLP. They need to understand the framework of both structured and unstructured data. Data security categories include confidential, personally identifiable information (PII), financial data, regulated data, intellectual property, and more. DLP products are used to scan data that the organizations may later customize, to help and identify the key categories of data. While DLP software automates and accelerates classifications that will be later selected by humans and then categorized.
Establish data handling and remediation policies
After classifying frameworks, the next step is to create policies for handling different categories of data. The leading requirement specifies the DLP policies to handle sensitive data. Where DLP solutions generally apply pre-configured rules or policies based on various regulations. DLP will then customize the policies for staff according to the requirement of an organization. To control policies, DLP application products, will monitor outgoing data and provide options to handle potential data security breaches.
Implementing a DLP policy is not enough. Intimidating stakeholders and users about the data policy, its significance, and what they need to do to safeguard the organization's data.
Overall, the data loss prevention process needs a lot of thought and planning. Technical solutions need more power and control over sensitive data, DLP helps but it could be better. Data Loss Prevention Best Practices help you Implement, Evaluate, and Create solutions for structured framework.
To learn and practice more about data security and data science-related topics, visit Sprintzeal’s course page and enroll in your desired course now. Get trained by the industry experts, and start your career.
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