关键词: 移动互联网, 恶意代码, 人工免疫系统, 检测, 阴性选择, 克隆选择

Abstract: The mobile Internet has brought great convenience to us, however, we have to face many threats such as malcode. In face of unknown malcode emerging in large numbers, traditional detection methods show many limitations, such as decline of detection speed, rise of false positive rate and false negative rate, the sharp increase of cost and so on. In recent years, some malcode detection methods based on intelligent algorithm are proposed. Among them, the artificial immune system has become the research hotpot of information security area because of its organization, adaption, memory and distributed advantages. According to the basic theory of nature immune system, a mobile malcode detection model for android platform was proposed. Extract the behavior features of malcode using the android emulator, such as starting service, telephoning, sending message, file read or write operations and accessing the Internet. The behavior features were encoded as one of the source of immature detectors. The immature detectors become mature through negative selection algorithm. Clone and mutate the mature detectors with higher affinity. Experiment results show that the proposed detection model has high detection rate and can also accurately detect the packed malcode samples.

Key words: mobile Internet, malcode, artificial immune system, detection, negative selection, clonal selection