关键词: 入侵检测, Wi-Fi技术, 异常序列检测, 隐马尔科夫模型

Abstract: Faced with indoor security problem brought by illegal intrusion and the prevalent Wi-Fi technique, this paper firstly designs a novel algorithm based on abnormal sequences detection to learn users’ behavior habits to identify illegal intruder. The algorithm takes collected CSI （Channel State Information） as input signal. After denoising and segmentation, the algorithm leverages HMM （Hidden Markov Model） to learn users’ behavior habits, and then adjusts detection threshold according to the output probability value. As time passed by, the model will be more close to users’ behavior feature. Finally tailored models will be built for different users, and distinguish the intruder. Experiments have demonstrated that detection accuracy can achieve 93.4%, thus the algorithm has realized real-time correct identification purpose.

Key words: intrusion detection, Wi-Fi technique, abnormal sequences detection, hidden Markov model