Long before the pandemic, K–12 cyberattacks were a serious concern. The shift to remote learning has only increased the danger. “Supporting digital transformation initiatives and a remote work model has led to a dramatic increase in the exposed edges of the network,” says Bob Turner, field CISO of higher education at Fortinet. “At the same time, malware, ransomware and other threats continue to challenge schools by exploiting inconsistently protected endpoint devices.”
The effects of an attack can be significant. IBM’s “2021 Cost of a Data Breach Report” notes that it can take an average of 287 days to identify and contain a data breach — and the longer it takes to identify, the more costly it becomes.
K–12 institutions have discovered an emerging solution: machine learning–enhanced endpoint protection. A type of artificial intelligence, machine learning uses immense computer power and algorithms trained on large amounts of data. It learns comprehensively to apply the knowledge it gains to monitor and render insights at a scale beyond human ability.
Traditional endpoint protection is reactive, responding once something has happened. Endpoint protection with machine learning is proactive, capable of studying an almost limitless amount of network traffic, logging information and app installations for anomalous activity. “Security technologies with artificial intelligence capabilities have the potential to anticipate attacks and counter them in real-time,” says Turner. “Given that cyberattacks occur in seconds, the speed brought by AI-driven security technologies is crucial.”
That’s not the only benefit. Here are three more:
Continue reading: https://edtechmagazine.com/k12/article/2021/10/artificial-intelligence-and-machine-learning-play-role-endpoint-security
The effects of an attack can be significant. IBM’s “2021 Cost of a Data Breach Report” notes that it can take an average of 287 days to identify and contain a data breach — and the longer it takes to identify, the more costly it becomes.
K–12 institutions have discovered an emerging solution: machine learning–enhanced endpoint protection. A type of artificial intelligence, machine learning uses immense computer power and algorithms trained on large amounts of data. It learns comprehensively to apply the knowledge it gains to monitor and render insights at a scale beyond human ability.
Traditional endpoint protection is reactive, responding once something has happened. Endpoint protection with machine learning is proactive, capable of studying an almost limitless amount of network traffic, logging information and app installations for anomalous activity. “Security technologies with artificial intelligence capabilities have the potential to anticipate attacks and counter them in real-time,” says Turner. “Given that cyberattacks occur in seconds, the speed brought by AI-driven security technologies is crucial.”
That’s not the only benefit. Here are three more:
Continue reading: https://edtechmagazine.com/k12/article/2021/10/artificial-intelligence-and-machine-learning-play-role-endpoint-security
