Cyber SecurityHealth Tech

How Predictive Cybersecurity Diagnosis is Helping Healthcare

Predictive Cybersecurity

An increase in digital access to healthcare is increasing the risk of cyberattacks

The number of cyberattacks on networked medical devices has increased in the past few years. The health care sector has been taking proactive steps to defend patient data. Predictive cyber security is the usage of AI and advanced technology to proactively monitor cyber threats. The average rate of cyber security has increased from US$7.13 million in 2020 to $9.23 million in 2021 resulting in a 29% increase just in a year. Cyber-attacks in the healthcare sector not only cause problems financially, regulatorily, reputationally but also put patients’ safety at risk. The medical records are being largely edited and manipulated. If hackers can CT’s and MRIs, it can also lead to misdiagnosis, cyberterrorism, insurance fraud, ransomware, and incorrect procedure or surgeries.

Though healthcare is taking strict actions against cybersecurity it still fails to control medical device security, accidental or malicious insider threats, and lack of a designated security team. According to a recent report, 89% of the cyber-attacks take place through emails and 57% of cyberattacks begin with trusted insiders. The medical sector does not have the right personnel to secure its system and work for cyberattacks. The healthcare sector has now started using prediction to improve diagnosis and patient care.

Cyber risks in the healthcare sector can be brought down by predictive cybersecurity. The risks within the organization can be calculated at the most basic level. The probability of cyber risks is termed as ‘breach likelihood’. Medical personnel has to predict risk which can be from medical devices, through personnel, medical equipment, and suppliers. The possibilities are endless. Each prediction makes the organization to be prepared to alleviate breaches. Breach likelihood can be useful for cybersecurity conversations to form a complete picture. It provides a realistic view of cyber risk and transfers cybersecurity into a shared responsibility.

This is how predictive cybersecurity is helpful:

Cybersecurity threat prediction for medical devices 

Using artificial intelligence and big data predictive analysis can prove to help detect cybersecurity threats. This technique is used to gather data from the network combined with previous information and then analyzed by an algorithm to calculate future threats like attempted breaches. If an attempted threat is detected, security personnel find out where it came from and potential measures to restrict it in the future. Predictive analysis helps to scan the network for vulnerabilities and online attacks before the hackers can target them. This predictive analysis allows medical device manufacturers to keep a check on hacker behavior. The medical device manufacturer is told to manufacture devices that have inbuilt AI facilities that can record, store, and analyze data during a crisis. This approach can detect cyberattacks with an accuracy of 97.16%. Security technologies allow companies to stay one step ahead of attackers from accessing medical data and information.

Threat prediction to defend patient’s data

Increased cyber-attacks mean increased danger. Growing cyber-attacks mean difficulty in protecting patients’ data and carrying out treatments effectively. If cyberthreat keeps on growing it may be very difficult to protect important data and documents in the next coming years. Any misuse of the patient’s reports might lead to wrong treatment. As cybersecurity strategies and practices are becoming effective, automated and proactive methods need to be taken. Approaches like threat prediction cybersecurity help them prepare for attacks from beforehand reducing the risk of breaches and unauthorized access of patient data.

Threat prediction to restore and backup application

Cybersecurity tactics like the use of backups and restore help in saving important data. Once the attempted threat has been detected, these proactive measures allow us to get data back in case it is deleted or tamper with data. Data is very crucial for providing effective medical facilities to patients. The previous data can be restored and cross-checked with the original file before deciding on a treatment plan for the patients. The health care sector should invest in AI-enabled tools and equipment to detect duplicate files and access the original ones.

Training and awareness

Not only professionals, but medical cybersecurity also need to raise awareness among the patients and other healthcare workers. From end-users to clinicians, scheduling staff, caregivers who connect with medical aid through devices should know about cyberattacks and predictive analysis techniques to restrict the hackers from tampering with patient’s files. The patient and other medical staff need to know that it is not safe to store their documents randomly on mobile phones or computers. This might lead to piracy and data integrity risks. People need to be more cautious of malware execution. Healthcare needs to come up with software where patients and store their data and doctors can also go through them without any external interventions. Though many healthcare institutions are coming up with their apps and website to communicate with their patients, they first need to ensure data protection with strong cybersecurity facilities.

What's your reaction?

In Love
Not Sure

You may also like

Leave a reply

Your email address will not be published. Required fields are marked *