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Data Leakage Prevention

data leakage prevention

What we offer

Alert: Reduce the risk from social engineering and malware attacks exfiltrating data in targeted attacks

Protective: Stop Insider threats and accidental data sharing with a tight set of policies around crucial information while also gathering data for education and official action

Governing: Oversee flows and policies of all critical data in your organization for governance and compliance purposes

Frequently Asked Questions on Data Leakage Prevention

1. What is Data Leakage?

Data leakage is the unauthorised exfiltration of information from within a network to an external recipient.

2. What are the categories of data leakage?

To understand data leakage prevention, you must first understand the different types:

  • Accidental Breach- For instance, an employee may unintentionally leak sensitive data by accidentally choosing the wrong recipient and sending an email containing confidential data
  • Data exfiltration/Insider Threat – An employee may leak confidential information maliciously on purpose.
  • Malware – Malicious software is often purpose-designed to exfiltrate data from high-value targets within the organisation.

3. How can data leakage be prevented?

Data loss prevention (DLP) ensures a tight set of rules and policies around data use, particularly extraction, in an organisation. These policies are then enforced by specialised software.

Best practice for minimising data leakage on your network includes:

i. Classify data according to value and the sensitivity

Know the structured or unstructured data can be shared and who should access the data you store and use this to form policies.

ii. Proactively identify and mitigate using DLP solutions

Proactively identify and mitigate risks effectively by automating progressive DLP solutions.

4. What Tools Should Be Layered With DLP?

  • For basic individual Data Leakage Prevention, tools such as an Intrusion Detection System (IDS) alert when an attacker attempts to access sensitive data.
  • Another primary data loss prevention tool is Antivirus software which prevents attackers from compromising sensitive environments holding data in the first place.
  • Alternatively, a firewall blocks unauthorised access to systems storing sensitive data.

5. What Are The Major Categories Of Data Leaks?

a). Customer Information

One of the most significant data breaches will include customer data leaks which involve Personally Identifiable Information (PII). Each business’s customer information is unique. Any of the following could be considered for protecting sensitive data such as:

  • Customer names
  • Email addresses
  • Phone number
  • Usernames
  • Passwords
  • Credit card numbers
  • Product browsing habits

b). Company Information

Such data dumps sometimes come under fire from dishonest companies trying to copy their rivals’ marketing strategies.

Some of the company data leaks include:

  • Marketing strategies
  • Internal communications
  • Performance metrics
  • Financial data

c). Trade Secrets

This type of data breach poses the greatest threat to a company. Intellectual property theft ruins a company’s potential and runs it to the ground. Trade secret leakages could have different data types, including:

  • Software coding
  • Upcoming product plans
  • Proprietary technology information

d). Analytics

Cybercriminals are drawn to substantial data pools, and large data sets feed analytics dashboards. The necessity to monitor analytics software arises from its role as an attack vector.

Analytic data leaks could include:

  • Customer behaviour data
  • Modelled data
  • Psychographic data

6. Is There A Difference Between A Data Leak And A Data Breach?

A data breach results from a planned cyber attack, while a data leak is an accidental exposure of sensitive data by an organisation. Cybercriminals don’t create data leaks. Instead, they find them and use them to execute data breach attacks.

Poor security practices often lead to data leaks. Unfortunately, these vulnerabilities are difficult to detect and fix since they occur throughout a broad attack landscape.

7. What Are The Components Of DLP

Data loss prevention (DLP) is a protection strategy with data leak prevention as a core component. Data loss prevention solutions automate its key features. Thus software providers can assist organisations in streamlining their DLP strategy.

The components of DLP include:

a). Data Identification

Many organisations use automation techniques to speed up data identification, including machine learning and artificial intelligence (AI).

b). Secure Data in Motion

Companies can install DLP software at the network’s edge to filter traffic for false positives and detect sensitive data being sent in violation of security policies.

c). Secure Endpoints

Endpoint DLP agents can monitor user activity in real-time and manage data transfers between specified parties, such as through instant messaging apps.

d). Securing Data at Rest

DLP products enforce encryption algorithms, access control, data storage policies and regulatory compliance requirements to protect archived data.

e). Secure the Data in Use

The comprehensive DLP tools monitors and flag any unauthorised behaviour, such as unauthorised users’ privilege escalation on an app.

f). Data Leak Detection

Rapid remediation is essential to prevent a data breach if data leak prevention techniques fail. Practical strategies for finding data leaks can search the deep and open web for data exposures, including S3 buckets and GitHub repositories, allowing quicker removal of possible breach vectors.

8. What Are The Main Use Cases Of DLP?

Data loss prevention addresses three primary goals that are typical problems for many organisations:

a). Personal Information Protection / Compliance

Do you gather and keep Personally Identifiable Information (PII), Protected Health Information (PHI), or Payment Card Information (PCI) in your organisation? If so, you are subject to compliance laws that require you to safeguard your clients’ sensitive data, such as HIPAA (for PHI) and GDPR (for personal data of EU citizens).

A DLP program can recognises, categorise, and tag sensitive data and keep an eye on the actions and events surrounding it. Furthermore, reporting capabilities can provide the information required for compliance audits.

b). Data Visibility

Do you want more insight into how data is moving within your organisation? Then, you can view and keep tabs on your data on endpoints, networks, and the cloud with a complete business DLP solution.

Your organisation’s users’ interactions with data will be visible to you.

c). IP Protection

Does your organisation possess valuable intellectual property, trade secrets, or state secrets that, if lost or stolen, could jeopardise its financial stability and reputation?

DLP tools that employ context-based classification can categorise organised and unstructured intellectual property types. You can prevent the unintentional exfiltration of this data by putting policies and controls in place.

Secure Your Data Today

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