FEATURE : ENDPOINT SECURITY
use predictive analytics and algorithms to improve their suggestions .
The medical fraternity too relies on prediction models to improve diagnostics , identify risk groups and improve patient care .
Why not use the same analytical approach to predict the possibility of a breach rather than detecting cyberattacks after they happen and reacting to them ?
The use of predictive technology and models such as the Bayesian Network to predict cyberbreaches makes this possible .
Saket Modi , Co-Founder and CEO at Safe Security
Enterprise cyber-risk is a product of the probability of a breach happening and its business consequence . This probability is termed the ‘ breach-likelihood ’ of the organization and can be calculated at the most granular level .
Starting from the breach-likelihood of each medical device in every room , department-wise employee threats , to vendors or suppliers of equipment and pharmaceuticals , Electronic Medical Records directory on the cloud and the security posture of each cloud asset – the possibilities are endless .
Each prediction makes the organization that much more prepared to predict and therefore mitigate breaches . Once an organization knows what to expect , it can focus energies on fixing what really matters rather than carrying out ad-hoc activities which only add to a sense of security rather than real cybersecurity .
How does breach-likelihood help the healthcare sector ? in each hospital room , creating a vast digital attack surface . Interestingly , while one aspect is digitizing faster than it can be secured , 83 % of medical imaging devices are still legacy systems too old to receive software updates .
4 . The lack of a designated security team : 87 % of healthcare IT security leaders work without the right personnel , and three in four hospitals are operating without a designated security leader .
Can predictive analytics in cybersecurity help the healthcare sector ?
Financial services organizations predict the likelihood of loans being repaid using the financial history of the applicant , their previous loans , salary / income and credit score . Similarly , OTT platforms
Breach likelihood in the healthcare sector can be a gamechanger in giving the visibility that is missing today . Similar to doctors arriving at a diagnosis after carrying out due diligence , sieving noise from actual symptoms and aggregating all relevant information to a central database , cyber-risk quantification can segregate information from noise .
As healthcare organizations ramp up cybersecurity infrastructure , they need to remember that all cybersecurity services , products and processes implemented in their cyber-risk ecosystem need to communicate with each other .
In a scenario where tens of cybersecurity services and tools are performing well in silos , but together fail to generate a comprehensive and prioritized solution , breach-likelihood can create one score to drive cybersecurity strategy . p
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