How Important DLP is  

Data loss can result in several consequences: 

• Damage the company's reputation 
  Company reputation may be at stake, because public users will think that the respective company is incompetent in protecting the data they have or is even detrimental. 

• Decreased productivity 
  The productivity of certain functions/companies may decrease because they lose data to process for their daily activity. 

• Destroy to certain function 
  Data loss can also result in damage to certain functions, especially if the lost data has dependencies on other data/functions. certain business function. 

• Financial implication 
  When a company experiences data loss, user trust can decrease, so it is possible that the company will also lose users or even lose some of their assets if the data has selling value. 

Therefore it is very important for companies to implement Data Loss Prevention (DLP).  

Causes of DLP

Before discussing Data Loss Prevention, we must first know the things that can cause data loss.  

1. Software corruption 
   Software corruption may cause the data to be corrupted, so that we are no longer able access the data. 

2. Human error 
   Not a few data loss is caused by human error, where the data is accidentally deleted or formatted which can result in the loss of some data or even all data. 

3. Hacker attacks 
   Hacker activity also may cause data loss, where the hackers try to take the data or even destroy the function so that we are no longer able to access the data or even using the function. 

4. Theft of property 
   Theft of property become basic root cause from the data loss, where they want to get money from selling the property and we loss the data inside the property. 

5. Viruses or Malware infection 
   Sometimes viruses and or malwares infection not only affect to the hardware, but also may impact to the data. Certain data may be deleted and or corrupted, so that we are no longer able to use or access the data. 

6. Mechanical failure 
   We may experience data loss due to the hardware suddenly stopped working and or unable to access the respective data. 

7. Malfunction of certain hardware 
   The hardware may still working during the data processing but with an inappropriate or correct process, so that we are no longer able access the data. 

8. Power failure 
   Power failure could interrupt delicate write processes and or leave certain process that may corrupt the data so that we are no longer able to access the data. 

9. Disaster 
   Disaster may become one of causes of data loss because it could destroy physical data or hardware. 

Types of DLP  

There are several different types of Data Loss Prevention (DLP) solutions, including: 

1. Network DLP
   This type of DLP solution monitors network traffic for sensitive data and can take action if it detects any violations. Network DLP solutions are typically implemented at the network perimeter, such as at a firewall or router, and can monitor both inbound and outbound traffic. 

2. Endpoint DLP
   This type of DLP solution is installed on endpoint devices, such as laptops, desktops, and servers, and monitors for sensitive data on those devices. Endpoint DLP solutions can also monitor data that is being sent or received by the endpoint device, such as email or instant messaging. 

3. Cloud DLP
   This type of DLP solution is used to protect sensitive data that is stored in the cloud. Cloud DLP solutions can monitor data in cloud storage services, such as Amazon S3 or Microsoft OneDrive, and can also monitor data that is being sent or received in cloud-based applications, such as Office 365 or Google Workspace. 

4. Mobile DLP
   This type of DLP solution is used to protect sensitive data on mobile devices, such as smartphones and tablets. Mobile DLP solutions can monitor data on the device itself, as well as data that is being sent or received by the device, such as email or instant messaging. 

5. Database DLP
   This type of DLP solution is used to protect sensitive data that is stored in databases. Database DLP solutions can monitor data in databases, such as SQL Server or Oracle, and can also monitor data that is being sent or received by the database. 

While these are some of the main categories of DLP solutions, there can be variation and overlap in the capabilities and implementation methods of different DLP solutions depending on the vendor and the specific use case. 

DLP Best Practices 

Now we know that there are so many risks that can be caused by Data Loss to the sustainability of a company or business. Likewise the causes of Data Loss are also very diverse. Thus we must begin to understand the importance and how to implement Data Loss Prevention. Data Loss Prevention is a combination of people, processes, and technology that works to detect and prevent data leakage. Here are some strategies that can be implemented: 

1. Data Loss Prevention strategy 
   Set protective measures, such as encryption, and monitoring, and controlling endpoint activities. Below are several best practice that can be applied: 

   1. Data classification – we can implement DLP policy to identify sensitive data 

   2. Data Encryption – we can make sure the unauthorized user won't be able to access the data even if they gain access to its solution 

   3. Patch management – to ensure there are no vulnerabilities being introduced into the organization 

   4. Automation - we can minimize human error and scale the need from the organization 

   5. Use anomaly detection – we can monitor abnormal behavior using machine learning and or analytic tools 

2. Backup 
   Backup company data at least one copy of data to ensure that we will not easily lose data during certain processes or due to technical errors or human errors 

3. Firewall and Antivirus 
   Installing a firewall or antivirus is one way to protect or prevent threats from accessing sensitive data. Apart from that, we also have to ensure regularly that the software used is updated 

4. Power failure prevention 
   Install a power supply that cannot be interrupted when there are power outages and allow the system to save data or close the system without causing data loss 

5. Encrypting data 
   Encrypting sensitive data can help protect it from unauthorized access, even if it is lost or stolen. Encryption can be applied to data at rest (stored on a device) or in transit (being transmitted over a network). 

6. Using Data Loss Prevention (DLP) solutions 
   DLP solutions can monitor and analyze data as it is being created, stored, and transmitted to ensure that it is not being misused or mishandled. 

7. Implementing access controls 
   Access controls, such as user authentication and authorization, can help prevent unauthorized access to sensitive data. 

8. Review and update security policies 
   Regularly reviewing and updating security policies can help to ensure that they are up to date and effective in protecting sensitive data. 

9. Employee education and training:  
   Regularly educating employees about the importance of data security and best practices for protecting sensitive data can help to reduce the risk of data loss through human error. 

10. Monitoring and auditing  
    Regularly monitoring and auditing systems and networks can help to detect potential threats and respond to them quickly. 

It's important to note that preventing data loss is a continuous process and requires a combination of different methods, technology, and human efforts. 

DLP Solutions and Tools  

DLP solutions typically monitor and analyze data as it is being created, stored, and transmitted to ensure that it is not being misused or mishandled. 

DLP solutions can be implemented on different levels, such as network-level, endpoint-level, cloud-level, mobile-level, or database-level, depending on the specific use case and the type of data that needs to be protected. 

DLP solutions typically work by identifying sensitive data based on predefined policies and rules, which can include data classification such as credit card numbers, Social Security numbers, and other personal information, as well as confidential business information such as trade secrets and financial data. Once the sensitive data is identified, DLP solutions can take automated actions, such as blocking the transmission of the data or alerting a security administrator. 

DLP solutions can also use various techniques such as pattern matching, regular expressions, and keyword searching to identify sensitive data, as well as use machine learning and artificial intelligence to improve the accuracy and efficiency of identifying sensitive data. 

DLP solutions can also integrate with other security technologies, such as intrusion detection systems, firewalls, and encryption to provide a more comprehensive security solution. 

You can also use security tool like SentryPage to alert you as soon as possible whenever there is suspicious activity happens on your webpage. We provide free 1,000 credits for initial usage.