{'fraction_non_alphanumeric': 0.0195712954333644, 'fraction_numerical': 0.0, 'mean_word_length': 5.392857142857143, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A new Anomaly Traffic Detection Based on Fuzzy Logic Approach in Wireless Sensor Networks

In the Internet of Things era, Wireless Sensor Network (WSN) acts as a key infrastructure, provides a large number of outstanding applications nowadays. WSN is a distributed and self-organizing wireless network with lots of constraint issues such as communication capacity, energy limitation, and distributed fashion. This type of wireless network is usually vulnerable by many attack strategies including jamming attacks, DDOS attacks, and malicious nodes. Anomaly detection is one of the typical intrusion defense approaches, in which the entropy-based anomaly detection approach has been extensively studied which brings some good results. However, it has faced several challenges such as complexity and accuracy. Hence, in this paper, a new anomaly detection method based on a fuzzy inference system is proposed to detect anomaly network traffic in wireless sensor networks. This fuzzy inference system model based on the fuzzy estimator which is validated by numerical results.