A data breach is a security issue that affects both companies and their clients.
Information-leaking cyber incidents damage the brand image - tarnishing the reputation of businesses that aren't transparent about the incident with affected users and partners.
After a cyber threat that has resulted in a data breach, organizations face the expensive aftermath. Time and money spent on improving cybersecurity, additional training of teams, and patching vulnerabilities is only a part of it.
In the case of compromised sensitive data, there is also a potential lawsuit for failing to
meet compliance according to regulations such as GDPR and HIPAA.
What happens once the hacker gets access to private data regulated by numerous privacy laws?
If the stolen data is sensitive, customers and employees face possible identity theft.
Database compliance helps businesses safeguard their infrastructure from data breaches and protect their user's private documents.
Role of Database Compliance in Data Breach Prevention
How does database compliance avert data breaches? Several ways privacy laws can reduce the number of cyber threats that result in compromised files are:
Urging companies to apply specific security guidelines that are written to guard sensitive user data as well as the infrastructure
Limiting the abundant collection of vulnerable data
Informing the affected users early enough, warning them to be precautious of hacking signs and changing their passwords
Finding the flaws that a bad actor can exploit before they turn into incidents (e.g. data breach)
Let's break down these measures and explore what kind of roles database compliance plays in overall cybersecurity and data protection.
Enforcing Security Measures
Regulations prescribe necessary cybersecurity tools and protocols that have to be in place to safeguard personally identifiable data.
Some of the security measures that are determined by the regulatory frameworks include firewalls, data encryption, strict access controls for users, and regular assessment of security.
This decreases the chances that valuable information will be changed, stolen, or accessed by the threat actor.
Ceasing Excessive Data Collection
Data compliance frameworks govern what kind of data can be gathered and for which purposes. The restriction on the collection of personal data means that companies have less sensitive information to manage within their systems.
One of the causes of data leaks is that businesses gather more information than they really need. Having fewer files makes data more manageable.
For organizations, this means they can retain visibility of sensitive data at all times and apply top security practices that prevent illicit access to systems.
Also, if the number of files that the company has about users is limited, this means that less information will be compromised if the data breach does take place.
Notifying Users Early About the Incident
Data compliance laws also urge businesses to report the incident early. For example, GDPR states that affected customers must be notified about the attack within 72 hours of the security incident.
This helps affected individuals to become a part of the solution in time. For instance, they can change their passwords early and watch out for signs of identity theft or unusual activity within their accounts.
The same goes for early reporting of cybercrime to the right authorities. They can aid companies with threat mitigation and patching up of highly critical vulnerabilities (e.g. the kind that could endanger important documents).
Detecting Data-Compromising Weaknesses
Database compliance frameworks offer strict guidelines regarding which data can be collected, for what purpose, and how such information should be stored within the company's network.
The records of data passing through the system and the exact information of how it was managed, as well as who accessed it, offer a reference point. This is necessary information the company needs to conclude whether the data was compromised in a breach.
Regular data audits encourage businesses to oversee and manage their data regularly - instead of setting security measures and failing to update them regularly.
Such practice helps companies track any anomalies and weaknesses early - with automation; they can do it in real-time.
Automated Database Compliance
Data compliance laws are susceptible to changes. Also, businesses gather plenty of personal information to improve their customer's experience - meaning new information is being added non-stop.
All of the incoming data has to comply with the relevant data privacy protection laws.
To manage the high volumes of files collected and identified within the system, compliance, analysis, identification, and classification of data, all have to be automated.
That is, compliance has to be paired with other proper data management methods. This includes continual cataloging and identification of private data to retain an overview of it.
As a result, IT teams know where it's stored within the system, who accessed the data, who made alterations to the database, the reason behind those changes, and when it happened exactly.
This information is then compared with the roles of people and the access they normally have to the specific parts of the system.
For example, if they accessed the data they don't need for their work or tried to do so outside of their normal working hours, this could point to unauthorized access.
To Conclude
It all boils down to the protection of sensitive or confidential data that a company stores within its architecture.
This is what the data compliance laws are all about - setting the frameworks that businesses need to follow to safeguard the valuable information they collect from their users.
Non-compliance with the data privacy protection laws not only results in potential fines and data breaches for the company. It also affects the lives of users who trust the business with personally identifiable information, the kind that can open them up to possible identity fraud.
Automated data management, which continually enforces the identification and categorization of sensitive data as well as enforces compliance laws, is essential for organizations that have to manage a lot of user data.
