AI Prevents Next-Gen Data Loss

Protecting sensitive data is more difficult than ever in a cloud-dominated world. Traditionally implemented DLP solutions are unable to keep pace with today’s needs. Their inefficiency, complexity and slowness hamper team productivity. Artificial intelligence and machine learning enabled DLP tools might be the best solution here. Being intuitive, cost-effective, and goal-specific, these tools are more effective. Sounds interesting, doesn’t it?

Learn how AI can prevent next-gen data loss

Learn a bit more about AI and DLP.

Let’s be clear on the what before moving on to the why or the how.

Artificial intelligence – Computers and machines using self-learning algorithms can think like humans thanks to artificial intelligence. These algorithms can recognize speech, solve problems, learn and plan.

Machine learning: A field of artificial intelligence in which algorithms predict outcomes without human intervention.

Data Loss Prevention: A way to protect sensitive data using technology. It scans, inspects and encrypts data at rest and in motion.

But is data loss prevention an urgent need?

Security is considered a must in all industries when it comes to DLP. This is not only recommended but required to comply with regulatory standards in highly regulated industries. However, there are differences between DLP solutions. It’s important to remember that DLP has been around since the 1990s. Workplaces have changed a lot since then.

DLP is sometimes referred to as an aging technology due to its rate of evolution. With traditional DLP methods, which sanitize sensitive email content, it is impossible to maintain enterprise security in the cloud-centric world of Zoom and Teams. The reason is that it relies on conventional approaches to describing and identifying data. Business workflow relies heavily on unstructured data, which these solutions cannot analyze.

As the workplace has evolved, many DLP vendors have changed with it – and new players have entered the game with DLP solutions that meet the changing challenges of data protection in a hybrid world. Consider the amount of data your organization generates: personal information, trade secrets, and sensitive information can be scattered across spreadsheets. We could only imagine Word documents and Slack chats on countless devices in different places. A data breach can only be prevented if you find, classify and secure this data. A need for relief, AI-Enhanced DLP was born out of this need. Read on to find out how it works.

So what’s the deal with AI-powered DLP?

When infused with artificial intelligence and machine learning, DLP finds critical information faster and more accurately than existing solutions. The self-learning nature of this DLP also frees up time for IT teams, allowing them to focus on other important tasks instead of constantly responding to false alarms. What else can AI prevent next-gen data loss? Check!

Track amorphous data

Using AI and machine learning, data can be analyzed at lightning-fast speeds and remain as accurate as if done by a human. Not to mention error-free results as a result. Managing dispersed and unstructured data is an inherent specialty. To improve AI, they need to analyze as much data as possible. The more information they investigate, the more accurate and effective the solution will be.

Accelerate data loss prevention.

The security team often has to update policies and rules every week, which continually puts them and their data at risk. AI, however, makes DLP self-learning. This tool identifies sensitive data by examining logs, rules, and previous patterns, even when no strict policies are in place. Additionally, AI-based DLP can prevent an insider threat in real time while increasing end-user awareness of data security through robust user behavior analysis.

Empower your IT team with AI

Swamp is a common complaint among cybersecurity professionals. An overwhelming number of false positives contribute to burnout. You can make the work of security teams easier by adding AI/ML to DLP. Automatic decision making helps focus on more critical tasks. It’s important to remember that AI-powered DLP does not replace security analysts. Classifying and redacting data are some of the most tedious and time-consuming tasks she handles to help people respond to threats in real time.

Enjoy cloud computing securely.

A single data security incident can damage your reputation, brand image, compliance fines and downtime. Even when data travels through cloud applications, you can protect your organization’s data with the right DLP solution.

To finish, Next-gen AI and machine learning can help organizations understand how their data is exposed on the deep dark web. By refining and developing models and methodologies, organizations can better detect data loss and avoid catastrophic events that could harm their business operations, finances, and reputation.

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