1 research outputs found
Securing the Internet of Things in the Age of Machine Learning and Software-defined Networking
The Internet of Things (IoT) realizes a vision where billions of
interconnected devices are deployed just about everywhere, from inside our
bodies to the most remote areas of the globe. As the IoT will soon pervade
every aspect of our lives and will be accessible from anywhere, addressing
critical IoT security threats is now more important than ever. Traditional
approaches where security is applied as an afterthought and as a "patch"
against known attacks are insufficient. Indeed, next-generation IoT challenges
will require a new secure-by-design vision, where threats are addressed
proactively and IoT devices learn to dynamically adapt to different threats. To
this end, machine learning and software-defined networking will be key to
provide both reconfigurability and intelligence to the IoT devices. In this
paper, we first provide a taxonomy and survey the state of the art in IoT
security research, and offer a roadmap of concrete research challenges related
to the application of machine learning and software-defined networking to
address existing and next-generation IoT security threats.Comment: IEEE Internet of Things Journal, 201