Abstract
The Social Internet of Things (SIoT) now penetrates our daily lives. As a strategy to alleviate the escalation of resource congestion, collaborative edge computing (CEC) has become a new paradigm for solving the needs of the Internet of Things (IoT). CEC can provide computing, storage, and network connection resources for remote devices. Because the edge network is closer to the connected devices, it involves a large amount of users’ privacy. This also makes edge networks face more and more security issues, such as Denial-of-Service (DoS) attacks, unauthorized access, packet sniffing, and man-in-the-middle attacks. To combat these issues and enhance the security of edge networks, we propose a deep learning-based intrusion detection algorithm. Based on the generative adversarial network (GAN), we designed a powerful intrusion detection method. Our intrusion detection method includes three phases. First, we use the feature selection module to process the collaborative edge network traffic. Second, a deep learning architecture based on GAN is designed for intrusion detection aiming at a single attack. Finally, we propose a new intrusion detection model by combining several intrusion detection models that aim at a single attack. Intrusion detection aiming at multiple attacks is realized through the designed GAN-based deep learning architecture. Besides, we provide a comprehensive evaluation to verify the effectiveness of the proposed method.
Highlights
W ITH the continuous development of the Internet, a large number of devices are connected to the Internet and communicated with each other in real time
We designed an intrusion detection algorithm aiming at a single attack based on generative adversarial network (GAN)
By combining several intrusion detection models aiming at a single attack, we design an intrusion detection algorithm aiming at multiple attacks based on GAN
Summary
W ITH the continuous development of the Internet, a large number of devices are connected to the Internet and communicated with each other in real time. CEC is a crucial technique for SIoT based on edge computing, which provides connections for users with low latency, high bandwidth, and high reliability [8], [9]. It can support high-quality communications for vehicles to implement unmanned driving [10], [11] and intelligent transportation system [12], [13]. 2) In CEC-based SIoT, due to the complex network environment (e.g., interactions of human-to-human, human-to-thing, and thing-to-thing), our networks will be threatened by many types of attacks, such as brute force, Denial of Service (DoS), and Distributed Denial of Service (DDoS) It is difficult for existing intrusion detection methods to find various types of attacks from massive data.
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