Data-centric framework for adaptive smart city honeynets

A smart city system will contain diverse heterogeneous smart objects. Their complexity will range from simple reduced function devices (RFD) acting as common nodes, to full function devices (FFD) acting as coordinators and controlling actuators. As part of the Internet of Things, web facing devices can be remotely accessed for monitoring, control and data exchange. This makes them vulnerable to cyber attacks and compromise. To analyse such attacks, honeynets and honeypots are deployed to attract attackers and capture their activity for behavioural analysis. Designing honeynets is difficult due to the broad engineering scope of smart cities as a concept, and consequent diversity of smart object characteristics such as communication channels, interaction, data exchange and embedded security. This paper brings order to this diversity and scope by taking a data-centric view of smart city devices. The data-centric view assesses smart devices for their criticality, security and complexity. It presents a framework using this view, for adaptive honeynet development. It then validates the new framework by categorizing smart objects using the data centric view and applying them to the framework.

[1]  J. Li,et al.  Smart city and the applications , 2011, 2011 International Conference on Electronics, Communications and Control (ICECC).

[2]  Qian Zhu,et al.  IOT Gateway: BridgingWireless Sensor Networks into Internet of Things , 2010, 2010 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing.

[3]  Mohsen Guizani,et al.  Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications , 2015, IEEE Communications Surveys & Tutorials.

[4]  L. Spitzner,et al.  Honeypots: Tracking Hackers , 2002 .

[5]  THE FUTURE OF SMART CITIES: CYBER-PHYSICAL INFRASTRUCTURE RISK , 2015 .

[6]  Qiaoyan Wen,et al.  A Trust-Third-Party Based Key Management Protocol for Secure Mobile RFID Service Based on the Internet of Things , 2012 .

[7]  Jason J. Jung,et al.  Social big data: Recent achievements and new challenges , 2015, Information Fusion.

[8]  Chunxiao Jiang,et al.  Information Security in Big Data: Privacy and Data Mining , 2014, IEEE Access.

[9]  Mianxiong Dong,et al.  A Hierarchical Security Framework for Defending Against Sophisticated Attacks on Wireless Sensor Networks in Smart Cities , 2016, IEEE Access.

[10]  Liesbet van Zoonen,et al.  Privacy concerns in smart cities , 2016, Gov. Inf. Q..

[11]  Antonio F. Gómez-Skarmeta,et al.  SMARTIE project: Secure IoT data management for smart cities , 2015, 2015 International Conference on Recent Advances in Internet of Things (RIoT).

[12]  Bill McCarty.  The Honeynet Arms Race , 2003, IEEE Secur. Priv..

[13]  Ian Welch,et al.  VICTORIA UNIVERSITY OF WELLINGTON , 2006 .

[14]  Antonio Iera,et al.  The Internet of Things: A survey , 2010, Comput. Networks.

[15]  Rudolf Giffinger,et al.  Smart cities ranking: an effective instrument for the positioning of cities? , 2009, 5th International Conference Virtual City and Territory, Barcelona, 2,3 and 4 June 2009.

[16]  Zhiguang Qin,et al.  Honeypot: a supplemented active defense system for network security , 2003, Proceedings of the Fourth International Conference on Parallel and Distributed Computing, Applications and Technologies.

[17]  Niels Provos,et al.  A Virtual Honeypot Framework , 2004, USENIX Security Symposium.