Machine learning is growing along with its ability to provide deep insights using big data. Information Week brought this interesting topic to our attention in their article, “4 Machine Learning Challenges for Threat Detection.”
Many organizations are developing deliberate machine learning to see how their companies can benefit, and a popular focus is on cybersecurity.
Machine learning solutions for cybersecurity can and will provide a significant return on investment, but they do face some challenges. It is important that organizations are aware of potential setbacks and set realistic goals to realize machine learning’s full potential going in.
Machine learning algorithms work by learning the environment and establishing baselines before they monitor for events that can indicate a compromise. However, if the IT enterprise is constantly reinventing itself to meet business agility needs and the dynamic environment doesn’t have a steady baseline, the algorithm cannot effectively determine what is normal and will issue alerts on completely benign events.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
