Abstract
Fog computing, as the supplement of cloud computing, can provide low‐latency services between mobile users and the cloud. However, fog devices may encounter security challenges as a result of the fog nodes being close to the end users and having limited computing ability. Traditional network attacks may destroy the system of fog nodes. Intrusion detection system (IDS) is a proactive security protection technology and can be used in the fog environment. Although IDS in tradition network has been well investigated, unfortunately directly using them in the fog environment may be inappropriate. Fog nodes produce massive amounts of data at all times, and, thus, enabling an IDS system over big data in the fog environment is of paramount importance. In this study, we propose an IDS system based on decision tree. Firstly, we propose a preprocessing algorithm to digitize the strings in the given dataset and then normalize the whole data, to ensure the quality of the input data so as to improve the efficiency of detection. Secondly, we use decision tree method for our IDS system, and then we compare this method with Naïve Bayesian method as well as KNN method. Both the 10% dataset and the full dataset are tested. Our proposed method not only completely detects four kinds of attacks but also enables the detection of twenty‐two kinds of attacks. The experimental results show that our IDS system is effective and precise. Above all, our IDS system can be used in fog computing environment over big data.
Highlights
Fog computing [1, 2] was defined as a highly virtualized computing platform for migrating cloud computing center tasks to network edge devices
The nodes in fog environment are close to the mobile users, and fog computing nodes are usually composed of devices with weak computing ability
In order to address the above issue, we propose an Intrusion Detection Systems (IDS) system based on decision tree over Anaconda [28]
Summary
Fog computing [1, 2] was defined as a highly virtualized computing platform for migrating cloud computing center tasks to network edge devices. Storage, and networking service between mobile users and traditional Cloud platform, which is complementary to Cloud. The fog computing reduces unnecessary multiple communication between the cloud computing center and the mobile users. When the number of users has increased dramatically, these users can obtain the service by visiting the contents of the cache in the fog servers so as to reduce network delay [8]. It significantly reduces the bandwidth of the backbone link load [9, 10]. Intrusion Detection Systems (IDS) can be used for fog environment [11]
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