The Major Reasons for Endpoint Security Failure
Endpoint computing is changing like never before, with smartphones, tablets, IoT devices and many other devices and appliances becoming part of the endpoint computing ecosystem for most organizations today.
However, as the endpoint computing ecosystem expands, cybersecurity vulnerabilities affecting endpoints too are increasing rapidly. Consequently. organizations have begun to invest heavily in endpoint security products. In fact, research data shows that endpoint security is the single largest segment of security software worldwide. Studies say, based on emerging trends, that in the near future, spending on endpoint security would definitely spike.
Cybercriminals target endpoints with ransomware, mobile malware, APTs (Advanced Persistent Threats), zero-day attacks, DDoS attacks, spear phishing, spoofing etc and organizations are reeling under the pressure of the tremendously increasing volume of endpoint-based threats and attacks. Endpoint security is becoming a big challenge and for many organizations, especially the small and midsize ones that do not have sufficient financial resources and experience to deal with the ever-increasing volume of threats and attacks, endpoint security even tends to fail very often.
Today, let’s examine the main reasons for endpoint security failure at the organizational network level…
Endpoints expanding, and becoming increasingly diverse & complex
This is one of the basic reasons for the failure of endpoint security. As we have already mentioned, the endpoint computing ecosystem goes on expanding for all organizations today. From a stage where we had only desktops, the notebook computers and the like as part of the endpoint computing ecosystem, we have evolved to a stage when we have tablets, smartphones, IoT devices, ATMs, checkout terminals, copiers, refrigerators and much more as part of the endpoint landscape. It’s all becoming more and more diverse, and consequently turning more complex as well. The fact remains that a vast majority of connected things remain unprotected or under-protected when it comes to cybersecurity. On the global level, there would be billions and billions of such unprotected or under-protected endpoint devices/appliances and that itself is a pointer to the enormity of the challenges lurking at endpoints for organizations big and small. Moreover, small and midsize organizations, owing to financial constraints, might not be able to ensure the support of security experts and engineers in an effective manner to ensure proper endpoint security. They wouldn’t have the resources to buy endpoint security products and that makes it all a big issue. Today, as we move towards a situation in which we have personal network connections, desktops, personal applications, personal cloud services etc turning part of the endpoint landscape for many organizations, endpoint security becomes a real tough game for most of them.
Organizations relying on a default-allow security posture
By continually relying on a default-allow security posture, organizations are putting themselves at risk. Unknown threats are let into their networks because of the default-allow security posture and eventually, there’s the likelihood of extensive damages happening as a result of such threats which are not recognized by their existing endpoint solutions. This is indeed a big issue as regards endpoint security.
Machine learning could also increase endpoint security risk
That machine learning has revolutionized and redefined everything associated with digital businesses is a well-acknowledged fact. But, at the same time, machine learning could also increase endpoint security risk if companies don’t understand the security challenges associated with it, especially because of the enormous amount of data involved. Examples of risks associated with machine learning are the increasing incidences of false positives and misplaced alerts because of a dramatic increase in data that machine learning brings, the inefficiency caused by algorithmic-based automation etc. Hence, though modern-day enterprises should definitely try to reap the benefits of machine learning, there should also be a continued effort to understand the security challenges associated with it as regards endpoint security and do the needful to protect endpoints and the data therein.
With endpoint security getting totally redefined with lots of new endpoint devices and appliances, plus virtual and cloud-based segments becoming part of the endpoint landscape for all organizations today, it’s important that organizations rethink on how endpoint security has to be worked out. They need to invest heavily in endpoint security and install the most advanced of endpoint security products, which would help them prevent cybercriminals from penetrating their networks through unprotected or under-protected endpoints.
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