Watchful eyes of Artificial Intelligence – Healthcare Data Security using AI
Cybercrime is an inevitable consequence of digitalization. It is a growing threat to all sectors, including health care. Contamination and loss of healthcare data is a prime concern, and in fact, data security in healthcare is considered as valuable as one’s bank details or even more. There is not enough staff in many organizations to ensure data security by monitoring it around the clock and protecting valuable data against hackers.
In this scenario, artificial intelligence (AI) offers a defense mechanism to medical IT by recognizing vulnerabilities, unfamiliar patterns, suspicious activity, and data breaches more efficiently. It can also respond to these attacks with greater precision quickly by identifying abnormal network behaviors and fraud threats.
Furthermore, cybercrimes involving social engineering techniques such as Phishing outsmart traditional anti-virus and other similar security systems are continually increasing. These attacks are becoming a more significant threat to the healthcare industry than any other type of attack. These breaches happen either to obtain access to protected health information (PHI) or to introduce malware. Thus, health care and info are used by hackers to create false identities, access free healthcare facilities and fraud insurance companies. Once these hackers succeed in installing ransomware into the hospital’s IT system, they can demand considerable ransoms to unlock encrypted documents and details.
Despite the online security offered by most healthcare organizations, there is an increase in these frauds. One main reason being the fact that is the BYOD policy where the employees bring their devices and operate their mobile phones at work while they fail to install online security onto their mobile phones.
Medical devices ranging from CT scanning machines to surveillance cameras need to be protected for data- and patient privacy. Startups like Cynerio identify possible cyberthreat and malicious activity by assessing the medical device’s behavior/pattern. CyberMDX leverages AI for adding extra layers of protection for medical devices to identify and combat cyberattacks automatically.
MedCrypt offers cybersecurity exclusively for medical devices. With importance to clinical functionality, this US-based startup protects a range of medical devices from surgical robots to ventilators, all in compliance with US Food and Drug Administration (FDA) regulations.
US-based Zingbox offers AI-powered data security and automated solutions integrating every device in a company’s IoT network. This avoids the need to install the program individually for each medical device. It analyses the standard activity pattern of several pieces of equipment in its repository and forms a baseline of regular activity and behavior. This helps in identifying the abnormal pattern of activity indicative of cyber-attack. Zingbox uses machine learning to offer secure and safe patient care to those in the hospitals.
Similarly, Cybeats, a Canadian startup, uses the device’s existing profile to chart the expected behavior of a medical device, thereby makes it possible to detect data fraud and cyber theft. It has the advantage of identifying the breach in few seconds, whereas existing traditional security systems would take more time to detects and quarantine infected devices and stop it from operating.
US startup Armis offers ML- and AI-based “agentless” cybersecurity for medical devices and eliminates the need to scan devices for threats and security breaches. This is an attractive feature as scanning could disrupt or interrupt the medical device’s working and undesirable while working on patients. It only takes a few minutes to install its SaaS platform, and it offers protects a wide range of it.
Darktrace is another startup that uses machine learning to detect cybersecurity threats to hospitals and healthcare organizations. Their solution, Enterprise Immune System, detects the breach and has a solution to respond to these fraudsters at lightning speed. The UK based Deep learning is yet another startup inspired by the human brain’s ability to learn. Once its artificial neural network trains to detect any cyber threat, it develops instinctive abilities to identify cybercrime and unauthorized entry in no-time.
Every healthcare organization wants uncompromised data security. The threat from malware is on the rise and continues to terrorize the government and other healthcare organizations. All the advancements in the digitalization of healthcare will require more prudent actions to protect data security.
However, AI is redefining cybersecurity. With this technological advancement, companies need to concentrate more on defending their security system against threats such as internet-related holes in cybersecurity. It also needs to enhance protection against cybercrimes attempting to infiltrate the healthcare organization, such as spearfishing emails or ones containing malware. These cybersecurity systems should also capture the details of the network intruder. Moreover, its diagnostic algorithms pose the threat of cyberattacks and giving out wrong interpretations.
After all, AI is a double edged sword. Solutions such as layered security controls, robust email filtering solutions, data control, and network visibility also play a vital role in keeping health systems safe.