Internet of Things is one of the fastest growing fields in the tech industry. New devices are constantly being invented and introduced into the market. According to Statista, there are expected to be “30.73 billion connected IoT devices in the world by 2020.” With so many new devices being introduced, it is inevitable that some of these devices will be released with vulnerabilities somewhere in the course of their product lifecycle. Many of these devices pose a risk to users and the networks to which they are connected. As many of Viasat’s customers will be adopting these IoT devices, Viasat had two intern teams working together on different aspects of IoT security. My intern team identifies devices in order to associate and offer better protection visibility to our customers. Our partner team is focused on detecting anomalies in network traffic behavior from these devices. This article summarizes both our teams’ efforts and results. (more)
In the last few years, we’ve witnessed explosive growth in the role machine learning (ML) plays in technology. Making good predictions from data has always been important in our industry, but modern machine learning techniques allow us to be much more systematic. However, this wealth of new ML algorithms and services present new challenges for software developers. (more)
I’m an intern in the Commercial Mobility group at ViaSat. Our group is responsible for all of the company’s commercial aviation clients, providing internet services to aircraft. While providing the world’s best in-flight internet service to airplanes traveling over 500 miles per hour 30,000 feet above the ground is no small feat, it is also a challenge to analyze and predict user demand of our network. There are typically several hundred planes connected to ViaSat’s network at any given time amounting to 15,000-40,000 flights a week depending on the season. With this much range and traffic, and flights leaving all times of day, all over the world, modeling anything about them becomes very difficult.