How Bad Data Alters Machine Learning Results

The effectiveness of machine learning models may vary between the test phase and their use "in the wild" on actual consumer data. Many research papers claim high rates of malware detection and false positives with machine learning, and often deep learning, models. However, nearly all of these rates are within the context of a single source of data, which authors use to train and test their models. Machine learning has become more advanced but isn't used enough yet in security, says Hillary Sanders, data scientist for Sophos' data science research group. She anticipates usage will increase in coming years to address the rise of different forms of malware.