AI Threat Hunting for Proactive Enterprise Cyber Defense
Using AI to Find Threats Before They Happen
Traditional cybersecurity tools only look for threats that are already known. Antivirus software looks for signatures in files, and firewalls stop connections that look suspicious. These methods are still useful, but most of the time, modern attacks don’t use known patterns. Instead, attackers stay hidden in networks for weeks or even months.
AI-driven threat hunting makes security proactive instead of reactive. Instead of waiting for malware to run, artificial intelligence looks at behavior to find strange activity before it can do any harm.
Why It’s Hard to Find Hidden Threats
Advanced attackers don’t set off alarms very often. They use real credentials, software tools that have been approved, and normal network channels. This method, which is often called “living off the land,” makes bad behavior look like normal business.
Rule-based systems may not see a compromised administrator account accessing backups at odd hours as a threat. But behavior analysis can tell that the pattern is different from what has happened in the past.
AI systems can find these small differences.
Behavioral Analytics in Business Settings
Behavioral analytics establishes a standard of typical behavior among users, devices, and applications.
The system learns things like how often you log in, how you use data, how you back up your data, and how you store it. After learning, it marks actions that are very different from what it thinks they should be.
Some examples are:
- A user who has never downloaded large archives before
- A service account changing the rules for keeping things
- Strange attempts to delete backups from repositories
- Access from places you didn’t expect
The system looks for intent instead of malware.
Detecting threats before they happen
Predictive detection is more than just watching. AI looks at events happening in different systems to guess where attacks might happen.
For instance, a sequence may happen:
- An attempt to log in that failed
- Request for privilege escalation
- Change to backup retention
- Big transfer of data
These things may not set off alerts on their own. Together, they show that preparations are being made for ransomware to be used. AI finds the pattern early and lets administrators know before encryption starts.
Keeping Backup and Storage Systems Safe
Backup platforms are the main targets of ransomware. Before starting encryption, attackers try to delete recovery copies. Behavioral analytics is very useful in this case.
AI monitoring can find:
- Changes to backup plans
- Attempts to delete snapshots
- Changes to many permissions
- Unexpected actions by the administration
Organizations can stop attacks before they happen instead of after they happen by keeping an eye on storage behavior instead of just endpoints.
AI Monitoring and Synology Storage Security
Logging and auditing systems that keep track of every file operation, login attempt, and configuration change are built into modern storage platforms. These logs are useful for AI-based monitoring systems.
Centralized storage environments make it possible to look at behavior across file access, backups, and administrative actions all in one place. This visibility makes it easier to spot strange behavior, like deleting snapshots in a strange way, changing replication in a strange way, or trying to access something without permission.
By using detailed activity logging and predictive analytics tools together, companies can get early warnings of attacks on their data protection systems.
Use Cases for Businesses
How to Stop Ransomware
Find strange patterns in encryption and stop access before files are locked.
Finding Insider Threats
Find users who are accessing data that isn’t part of their job or who have done so in the past.
Finding Compromised Credentials
Even when the credentials are correct, you can still see strange login patterns.
Watching for compliance
Keep an eye on changes to retention or audit policies that aren’t allowed.
About the Epis Technology
Epis Technology uses security monitoring methods that are made just for enterprise storage and backup settings. They use behavioral analytics and centralized backup platforms together to find threats that are trying to get to important data stores.
Epis Technology helps businesses spot suspicious activity early and keep backups that can be recovered even during advanced attacks by combining infrastructure hardening, monitoring, and recovery planning. Their method focuses on keeping both the systems that run the business and the data that businesses need safe.