AI in Dental Care: How AI Cybersecurity Combats Emerging Threats
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Our previous blogs introducing the impact of artificial intelligence and how AI-powered phishing is gaining significant traction may have left you shell-shocked. For those concerned that the days of online safety are long gone, Forbes offers a sense of relief on the topic:
“While it is crucial to be vigilant against the weaponized use of AI, it is equally—if not more—important to recognize the potential of AI to improve cybersecurity and benefit society as a whole.”
Practices cannot ignore the potential damage of AI attacks and data breaches. As new capabilities give hackers access to increased levels of automation for creating and launching attacks, cybersecurity specialists are also working to develop their own toolkit. Applying AI threat detection and adaptive analysis techniques provides a framework to block sophisticated intrusion tactics with lightning-fast response times.
Machine learning capabilities in AI cybersecurity are used to create complex software that continually analyzes data and network activity to prevent cyber attacks in real time. AI technology is a self-learning system; it constantly updates and adapts to strengthen defenses and sends alerts when human interaction is required to further assess what it has detected. Cybersecurity teams use this to their advantage, providing clients continually evolving and effective protection measures to stop malicious activity.
In this post, we’ll explore how some AI cybersecurity tools, when properly applied, work efficiently to defend and protect against potential cyber risks.
AI Threat Detection
Smart algorithms used in dedicated security programs analyze large amounts of data to detect patterns and anomalies that might indicate a cyber threat or an ongoing attack. Unlike traditional methods, which rely on pre-programmed software (like legacy antivirus applications) to seek out known threats, specialized AI cybersecurity software allows professionals to continually monitor, actively analyze, and learn from new data inputs. This activity happens in real time, enabling a more effective approach to stopping new and unknown threats against your practice.
Blocking Suspicious Activity
AI cybersecurity algorithms and machine-learning infrastructure identify suspicious or abnormal activities and behaviors by monitoring network traffic, system logs, and other data sources. After detecting these irregular patterns, login attempts, or malicious activities, the program blocks access as a control measure to prevent cyber attacks without needing manual intervention.
Stopping AI attacks before they impact daily operations is a significant benefit of self-learning cybersecurity technology, but how can dental groups know whether their systems withstood an infiltration attempt?
Professional cybersecurity software providers include functionality for comprehensive post-attack forensic investigation. Compiling all possible information on successfully foiled AI attacks provides essential knowledge on vulnerabilities that may not have been considered previously.
An IRL Example of AI Attack Tactics
The front reception team never emails the CEO directly, yet a convincing AI-generated message goes from reception to the CEO’s inbox. The specialized AI cybersecurity software spots this action and isolates the affected areas on the network for further analysis.
That phishing message may have contained a malicious link that would download paralyzing ransomware, compromising an entire office's digital environment. Considering it came from a known sender, the CEO may have quickly clicked on the link on instinct, opening their business up to a potential attack.
Malware Analysis
Unlike generic antivirus options that use predetermined defense protocols, AI examines sample malware to understand its behavior and intent. Through ongoing behavioral analysis, it identifies known malware signatures and detects new malware strains. The more a cybersecurity team and its software learn, the faster they can stop cyber attacks.
Predictive Analysis
A key differentiating factor in AI threat detection is the ability to forecast potential cyber threats, analyzing historical data to better prepare for an intrusion. Identifying trends that might indicate future attacks used to be an arduous process, relying on cybersecurity professionals poring over hundreds of pages from industry and government reports.
Now, AI cybersecurity software automatically reviews information on previous attacks and viruses on its own. This ability to make inferences, recognize patterns, and perform proactive actions shows the importance of AI in preventing breaches.
User and Entity Behavior Analytics (UEBA)
Damage to your business doesn’t always come from external bad actors—the employees you least expect may have ulterior motives that lead to a loss of financial and reputational stability.
AI analyzes user/entity behavior to detect unusual or unauthorized actions, block execution, and alert IT or HR teams to confront the suspected party. AI cybersecurity solutions help identify employees engaging in malicious activities and mitigate dangerous insider actions and compromised accounts.
Accelerated Response to Active Hazards
AI uses automation to prevent cyber attacks from escalating. By isolating affected systems, blocking malicious traffic, and containing a breach before it spreads, the tangible advantage of capable AI cybersecurity is impossible to ignore. This technology is a necessity these days for healthcare organizations to protect patient data from theft. Most often, these intrusion attempts happen overnight, on weekends, or during holidays when hackers have the best chance to circumvent the security measures that IT may have in place. Utilizing AI allows for 24/7 monitoring of suspicious activity and alerts your cyber partner and IT resources to respond immediately to the threat.
Hacker Attribution
Most cybercriminals don’t give up easily; even if your software withstands a single network intrusion, they will try and try again until your digital infrastructure comes crashing down. AI cybersecurity measures aren’t only learning to stop attacks when they happen, but cutting them off at the source.
In the event of an attempted breach, AI assists in attributing the breach to a specific hacking group, comparing attack patterns, techniques, and other characteristics to historical examples. The information can then be passed to organizations that create security strategies, policies, and regulations going forward to help all businesses stay out of harm’s way.
Ready to Build Your AI Cybersecurity Strategy?
Protecting your dental practice may seem daunting as the level of sophistication of these hacking groups grows exponentially. Thankfully, you aren’t alone in this cyber war — a security assessment can spot practice vulnerabilities and risks before they are exploited. Once located, your cybersecurity partner develops a comprehensive battle plan using the latest data protection solutions. In the final part of our AI in the Dental Space series, we’ll explore how businesses of any size can safeguard against new threats with a customized approach to leveling up their security.
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AI in Dental Care: A Double-Edged Sword
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Read MoreAI in Dental Care: Your Battle Plan Against AI Hacking
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