Paper Info
Title
SAGA: Secure Auto-Configurable Gateway Architecture for Smart Home
Abstract
Advances in the Internet of Things (IoT) have changed Smart Home technology from a local control system to one where many devices with high computational ability are network-enabled. These devices exhibit known and unknown attack surfaces by attackers either compromising the Smart Home itself or exploiting these devices to launch DDoS attacks. However, average home users often lack the technical skills to properly protect their networks and devices from those attacks. And manufacturers tend to design their systems for ease of use rather than ensuring security. Even for skilled home users, secure manual configuration and connection are time-consuming and error-prone. Therefore, it is important to develop a technique which is both simple to manage and secure against cyber-attacks. We present a secure auto-configurable gateway architecture (SAGA) that allows IoT devices to be automatically discovered, registered and configured when they connect to a Smart Home network. SAGA can (1) automatically register IoT devices securely, (2) reject malicious attempts by rogue devices to connect to the network, (3) identify attempts to capture devices by a rogue gateway and (4) provide services such as firewalls, address translation, device software updates, and host home control applications. Security analysis for the proposed architecture and details was performed. A prototype for SAGA was implemented and performance was evaluated in terms of execution/processing time.
Year
DOI
Venue
2019
10.1109/PRDC47002.2019.00013
2019 IEEE 24th Pacific Rim International Symposium on Dependable Computing (PRDC)
Keywords
Field
DocType
Auto configuration, Gateway, Smart Home, Internet of Things, mDNS, DNS SD
Architecture,Denial-of-service attack,Computer security,Computer science,Usability,Home automation,Security analysis,Default gateway,Software,Auto-configuration,Distributed computing
Conference
ISSN
ISBN
Citations 
1555-094X
978-1-7281-4962-2
0
PageRank 
References 
Authors
0.34
2
3
Name
Order
Citations
PageRank
Huichen Lin1271.69
Dong Seong Kim286693.34
Neil W. Bergmann300.34