“In the case of malware detection, for example, cyberdefenses have traditionally focused on signature recognition of code that has been detected in precious malware attacks or on heuristics that define a set of rules based on past malware behavior”
Cybersecurity Protection Increasingly Depends on Machine Learning
Using machine learning to protect the proliferating landscape of IoT and edge devices will ultimately rely on a distributed network model that applies intelligence at different tiers, based on cost, bandwidth and availability.
In this report, explore the capabilities of machine learning for cybersecurity tasks. Find out more about:
How machine learning algorithms can infer relationships and patterns of previously unseen activity to recognize network activity that indicates pending attacks.
Is it possible to secure IoT devices without spending on additional infrastructure or upsetting the already established IT status quo?
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