Biblio
A conversational agent to detect anomalous traffic in consumer IoT networks is presented. The agent accepts two inputs in the form of user speech received by Amazon Alexa enabled devices, and classified IDS logs stored in a DynamoDB Table. Aural analysis is used to query the database of network traffic, and respond accordingly. In doing so, this paper presents a solution to the problem of making consumers situationally aware when their IoT devices are infected, and anomalous traffic has been detected. The proposed conversational agent addresses the issue of how to present network information to non-technical users, for better comprehension, and improves awareness of threats derived from the mirai botnet malware.
Ever-driven by technological innovation, the Internet of Things (IoT) is continuing its exceptional evolution and growth into the common consumer space. In the wake of these developments, this paper proposes a framework for an IoT home security system that is secure, expandable, and accessible. Congruent with the ideals of the IoT, we are proposing a system utilizing an ultra-low-power wireless sensor network which would interface with a central hub via Bluetooth 4, commonly referred to as Bluetooth Low Energy (BLE), to monitor the home. Additionally, the system would interface with an Amazon Echo to accept user voice commands. The aforementioned central hub would also act as a web server and host an internet accessible configuration page from which users could monitor and customize their system. An internet-connected system would carry the capability to notify the users of system alarms via SMS or email. Finally, this proof of concept is intended to demonstrate expandability into other areas of home automation or building monitoring functions in general.