An Intrusion Detection System for Fog Computing and IoT based Logistic Systems using a Smart Data Approach
*1, 3 and 5 Department of Information Technology, University of Turku, Finland.
2 and 4Faculty of Information Technology, University of Jyväskylä, 40100, Jyväskylä, Finland.
JDCTA (International Journal of Digital Content Technology and its Applications)
Volume 10 Issue 5, December, 2016
ISSN 1975-9339 (Print) 2233-9310 (Online)
GlobalCIS (Convergence Information Society, Republic of Korea)
The Internet of Things (IoT) is widely used in advanced logistic systems. Safety and security of such
systems are utmost important to guarantee the quality of their services. However, such systems are
vulnerable to cyber-attacks. Development of lightweight anomaly based intrusion detection systems
(IDS) is one of the key measures to tackle this problem. In this paper, we present a new distributed and
lightweight IDS based on an Artificial Immune System (AIS). The IDS is distributed in a three-layered
IoT structure including the cloud, fog and edge layers. In the cloud layer, the IDS clusters primary
network traffic and trains its detectors. In the fog layer, we take advantage of a smart data concept to
analyze the intrusion alerts. In the edge layer, we deploy our detectors in edge devices. Smart data is a
very promising approach for enabling lightweight and efficient intrusion detection, providing a path
for detection of silent attacks such as botnet attacks in IoT-based systems.
Intrusion Detection Systems, Smart Data, Fog Computing, Internet of Things