As healthcare companies increasingly rely on digital technologies and internet-connected devices, a cybersecurity solution that can detect and defend against malicious activity is crucial. Healthcare companies are increasingly turning to AI to reduce their attack surface and enhance security measures.
Sensitive data and patient care are at risk
Attacks on healthcare companies are on the rise. Most recently, the Atlantic General Hospital in Baltimore, MD, was down after a January 29 ransomware attack that created network outage issues and impacted patient care. Hospital personnel implemented "downtime procedures" where they manually checked patients in and out, and patient information was recorded by hand rather than online. Hospital operations that were not available due to the attack and through remediation included the outpatient walk-in lab, pulmonary function testing, outpatient imaging, and RediScripts.
In December of last year, the Office for Civil Rights (OCR) at the U.S. Department of Health and Human Services (HHS) issued a bulletin warning against using browser cookies that could violate Health Insurance Portability and Accountability Act of 1996 (HIPAA) policies by tracking users. For instance, some healthcare companies may share patient information with online tracking technology vendors, and such disclosures could be used for marketing purposes. Not only does this violate HIPPA regulations, but it also could result in patient identity theft. As a result, healthcare companies need to be mindful and are even facing legal consequences.
For instance, two of the largest hospital networks in Louisiana, LCMC Health Systems and Willis-Knighton Health, are being sued for using a tracking code on their websites and sharing patient data. The hospitals deployed the Meta Pixel code, which shared information with Facebook so that patients could be targeted for advertising. Private and protected patient data exposed include medical conditions, prescriptions, doctors' names, and appointment history.
Using AI to reduce the attack surface
With the power of AI-enabled technologies, healthcare companies can reduce their attack surfaces and improve their security measures. For instance, companies can use automated crawlers to regularly track attack surfaces and gain an understanding of any differences, either up or down. Additionally, with URL clustering and analysis, they can scan for vulnerabilities and exposure to ensure that the proper code base does not violate HIPPA regulations.
Additional examples of how AI can reduce attack surfaces include:
Threat Detection: Analyze data for signs of malicious activity, enabling healthcare companies to respond to potential threats by identifying unusual patterns or anomalies that could indicate an attack.
Authentication and Access Control: Strengthen authentication and access control measures through biometric authentication, such as facial recognition or fingerprint scanning, to ensure that only authorized personnel are granted access.
Automated Patch Management: Monitor software and systems for vulnerabilities that may have been discovered and addressed through security patches and automatically deploy patches to all relevant systems, reducing the attack surface by mitigating known vulnerabilities.
Fraud Detection: Analyze vast amounts of data, such as payment transactions and insurance claims, to detect patterns that indicate fraudulent activity and help healthcare companies identify and prevent fraud, such as false insurance claims or duplicate payments.
Intrusion Prevention: Detect and prevent malicious activities on networks and systems through techniques such as behavioral analysis and signature recognition to identify attacks and trigger preventative measures, like shutting down certain network connections or isolating infected systems, for example, to minimize the impact of an attack.
Data Encryption: Encrypt and protect sensitive data using public key cryptography, such as patient records and financial information.
Vulnerability Assessment: Monitor systems continuously for vulnerabilities, such as outdated software or misconfigured systems, so that healthcare companies can identify and fix vulnerabilities before attackers can exploit them.
Read: Reshaping the Threat Landscape in 2023: Cybersixgill Announces Top Trends in Cybersecurity
As threat actors increasingly utilize more systematic and sophisticated attack methods, healthcare companies need to do more than updating and patching systems and hiring more security professionals. Instead, healthcare companies need to respond at lightning speed. They are enabled to do so through AI to identify vulnerabilities and stop the spread of an attack that can cause great harm to patients and the company's reputation.
Cybersixgill can help you assess, measure, prioritize, and address emerging threats.
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