Data Security in Machine Learning
The Fourth Industrial Revolution is commencing. The fourth installment of the revolution is marked by technology that blurs the line between human and machine and its most sought-after commodity is data. Therefore, data security and privacy are of the utmost concern in the digital economy.
The developments in Machine Learning (ML) are rapid, and the opportunities that this technology creates are wonderous. The rapidity of recent breakthroughs has no precedent, historically and is impacting almost every industry and encounter. Smart technologies are operating in our homes (Alexa, Amazon Echo, etc) and in our cars (think Tesla), they are customizing our online shopping experiences (Amazon), and soon in store (with facial recognition technology), they are supporting our military and our infrastructure, our agriculture and our financial services. Technology is shaping almost every aspect of human experience. Technology is interacting with, and learning from, the people with which it is intermingling.
But our love of technology also comes at a price. The more of it we adopt, the more we are vulnerable to cyber-attacks. ML utilizes data to teach its systems, and the better the learning data is, the more accurate the results are. Clean and reliable data is a valuable commodity, but the sheer amount of it makes it also an easy target, but while it must be remembered that cyberattack agents are a constant and real threat, this doesn’t mean that AI technologies are unsafe. They just require a heightened level of data security.
The best way to protect data privacy and an organization’s network is by utilizing the power of ML. In other words, matching the technology that the opponent is using.