Security is essential for all industries, but healthcare faces more pressure than most. Hospitals store vast amounts of highly sensitive information, making them ideal targets for cybercrime, so their defenses must be extensive. User and entity behavioral analytics (UEBA) are one of the most helpful tools in that endeavor.
The medical sector is no stranger to artificial intelligence, but most medical AI applications focus on patient care or administrative work. Applying it to cybersecurity in the form of UEBA is a crucial step forward.
What Is User and Entity Behavioral Analytics?
User and entity behavioral analytics use machine learning to detect threats like breached accounts or ransomware. While protections like multi-factor authentication try to prevent attacks, UEBA instead focuses on stopping threats that slip through the cracks before they can cause much damage.
UEBA analyzes how different users and entities — like routers or Internet of Things (IoT) devices — behave on a network. After establishing baselines for normal behavior, machine learning tools can detect suspicious activity. They may see an account trying to access a database it rarely needs or downloading something at an odd time and flag it as a potential breach.
This process is similar to how your bank may freeze your credit card if you make a few unusual purchases. However, it applies the concept to network behavior and uses AI to make it faster and more accurate.
UEBA Benefits
UEBA use cases have many benefits spanning multiple applications. Here’s a brief look at some of their most significant.
Accuracy
Behavioral analytics systems are highly accurate. Machine learning can pick up on trends and patterns in data humans may miss, so UEBA tools can outperform human analysts when determining what is and isn’t suspicious. When properly applied, UEBA can also yield false positive rates as low as 3%, ensuring security teams don’t waste their time or resources.
UEBA can achieve higher accuracies than rule-based monitoring systems because it’s adaptive. Machine learning algorithms continually gather new data and adjust their decision-making as trends shift. That way, they can account for nuances like users slowly adopting new habits or activities being normal in some situations but not others.
Efficiency
Another benefit of UEBA is it’s fast. Machine learning tools can detect and classify anomalies almost instantly when it may take a human a few minutes. Even if those time savings are just a few seconds, they can make a considerable difference when dealing with cyber threats.
UEBA tools can often detect suspicious behavior before an account or breached device causes any real damage. By identifying and isolating threats earlier, they can dramatically reduce the impact of an attack. IBM found reducing data breach response timelines saves organizations $1.12 million on average.
Versatility
UEBA is also versatile compared to similar security tools. Some organizations employ user behavior analytics (UBA), which provides similar benefits but only looks at user activity. By also including entities, UEBA expands its detection capabilities to IoT attacks and other hardware breaches, helping prevent a broader range of incidents.
Machine learning tools like UEBA are also more versatile than rule-based anomaly detection. AI models can adapt to changing situations and account for situational differences, which rule-based systems can’t. That flexibility is vital for healthcare organizations, as telehealth has grown 38 times over its pre-COVID levels, meaning more medical staff may access systems from changing locations.
UEBA Use Cases in Healthcare
These benefits are impressive, but how much medical companies experience them depends on how they apply this technology. In that spirit, here are the five best user and entity behavior analytics use cases in healthcare.
1. Automating Risk Management
Risk management automation is one of healthcare organizations’ most beneficial UEBA use cases. IT monitoring is crucial in this industry, but many businesses need more time or staff to manage it manually. Cybersecurity talent faces a skills gap across all sectors, and over 70% of medical workers say they already work more hours because of electronic health records (EHRs).
UEBA reduces that burden by handling network threat detection without manual input. Hospitals don’t need large security teams to monitor their systems 24/7 because AI will do it for them.
Because UEBA is so accurate and efficient, medical staff can use electronic systems more efficiently. There will be fewer verification stops or run-ins because of false positives, helping reduce the burden of EHRs. Those time savings improve both cybersecurity and patient care.
2. Detecting EHR Breaches
UEBA has many advantageous specific use cases under the automation umbrella, too. One of the most relevant for healthcare organizations is detecting and responding to breaches in EHR systems.
Electronic records make it far easier to manage patient data, but they also introduce significant security risks. There were over 700 health record breaches of 500 records or more in 2022 alone, with an average of almost two breaches daily. Given this issue’s common and severe, UEBA is an indispensable tool.
UEBA can recognize when an app or account is accessing an unusual amount of records or interacting with them atypically. It can then lock the user or entity in question before it can delete, download, or share these files, preventing a breach.
3. Stopping Ransomware Attacks
Ransomware prevention is another leading UEBA use case in healthcare. The rise of ransomware-as-a-service has made these attacks increasingly common, and the medical industry is a prime target.
Ransomware attacks against healthcare organizations have more than doubled between 2016 and 2021. Stopping these incidents early is critical to minimizing damage and protecting patients’ privacy. UEBA provides that speed.
Before ransomware can steal or lock any files, it must access them all. However, UEBA will notice an unknown program suddenly trying to access a large amount of data. It can then restrict access and isolate the file, account or device from which the ransomware spreads before it can encrypt anything. That way, hospitals can prevent ransomware before losing any sensitive information.
4. Preventing Insider Threats
UEBA is also a valuable tool for addressing insider threats, which are particularly prevalent in healthcare. In fact, insider error accounts for more than twice as many breached medical records as malicious activity. Because UEBA detects all anomalies — not just those from outsiders — it can help find and prevent these mistakes.
If a doctor, nurse or other staff member tried to access something they don’t usually need, UEBA would flag it as suspicious. If it were just an accident, this stoppage would bring the issue to the employee’s attention, letting them see and correct their mistake; if it were a malicious insider, UEBA would stop them from abusing their privileges.
UEBA can detect more than just unusual access activity too. It can also identify and stop actions like sharing credentials or attempts to send files to unauthorized users. That way, it can prevent employees from falling for phishing attempts, which account for most insider threats.
5. Securing IoT Endpoints
As IoT adoption in healthcare grows, IoT security becomes an increasingly advantageous UEBA use case. The IoT falls out of the scope of traditional user behavior analytics use cases because UBA systems don’t account for devices, only people. By contrast, UEBA includes endpoints, so it can address IoT concerns.
Just as UEBA spots irregular behavior in user accounts, it can detect unusual connections or access attempts from IoT devices. Consequently, it can stop hackers from using a smart device with low built-in security as a gateway to more sensitive systems and data.
Stopping this lateral movement is crucial, as IoT devices typically have weak security, and hospitals use a lot of them. More than half of all medical IoT devices also feature critical known vulnerabilities, so improving IoT security is essential for the industry.
Behavioral Analytics Are a Must for Healthcare
These UEBA use cases scratch the surface of what this technology can do for medical organizations. As EHR adoption and cybercrime both rise, capitalizing on these applications will become all the more important.
The healthcare industry must take cybercrime seriously. User and entity behavioral analytics systems are some of the most effective tools for that goal.
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