What Could Possibly Go Wrong? Identification of Current Challenges and Prospective Opportunities for Anomaly Detection in Internet of Things

Abstract

The era of the Internet of Things (IoT) is now. Wide-spread adoption of this technology has transformed the way the world, people, and businesses are connected. However, with the adoption of IoT, comes the increased threat of security risks which can negatively impact industry productivity and performance. Companies and organizations, that rely on IoT for operations, are specifically vulnerable to anomalies in their data. Over the years, anomaly detection has evolved, and algorithms have continually taken new forms for better performance. However, there are still challenges that need to be addressed to make IoT anomaly detection more robust in the future. Within this paper, we highlight a high-level description of the current IoT architecture. Following this, we identify some current challenges to anomaly detection in IoT. Finally, we propose prospective opportunities that can be investigated to address these identified modern-day challenges of anomaly detection.