Method and device for detecting junk mail

Abstract

The invention provides a method and device for detecting a junk mail. The method includes: generating a sample vector according to a sample library and a feature word lexicon which includes normal mail type feature words and junk mail type feature words which are extracted from sample mails of the sample library; selecting a linear kernel function of a support vector machine, using the sample vector as input and training to obtain a classification function; determining weights of feature words in the feature word lexicon according to a coefficient of the classification function, picking up feature words whose weights are nonzero values to generate a feature word set, and determining a judging threshold value according to an offset of the classification function; and making statistics of a sum of the weights of the feature words contained in a mail to be detected according to the feature word set, and judging the mail to be a junk mail when the sum of the weights exceeds the judging threshold value. The method for detecting a junk mail saves the calculation amount of a detection process, and improves detection efficiency under the condition of guaranteeing detection precision.

Description

technical field [0001] The present application relates to the technical field of communications, in particular to a spam detection method and device. Background technique [0002] With the popularization and rapid development of Internet technology, e-mail has become an important communication method for people's work and life because of its fast, convenient and low-cost characteristics. What followed was the flood of spam. Spam not only occupies limited network data and consumes a lot of processing time for users, but also carries network security issues such as worms, viruses, and phishing attacks. Therefore, fast and effective spam is required. Mail detection to ensure the normal mail communication of users. [0003] Among the many spam detection technologies, the content filtering technology based on statistics is widely used in the process of spam detection because of its good filtering effect, timely capture of changes in spam characteristics, and less manual interven...

AI Technical Summary

Problems solved by technology

What followed was the flood of spam. Spam not only occupies limited network data and consumes a lot of processing time for users, but also carries network security issues such as worms, viruses, and phishing attacks. Therefore, fast and effective spam is required. Email detection to ensure normal email communication for users

[0003] Among the many spam detection technologies, the content filtering technology based on statistics is widely used in the process of spam detection because of its good filtering effect, timely capture of changes in spam characteristics, and less manual intervention. Machine, SVM) has more advantages than other statistics-based filtering techniques due to its small sample size, good generalization performance, complete theory, strong adaptability, global optimality, strong generalization ability, and short training time. In the research of spam detection based on support vector machine, methods such as optimizing feature word selection process, weighting the training process, expanding the constraints of linear discriminant function, optimizing the kernel function of support vector machine and its parameters are used to improve the detection accuracy. These methods improve the detection accuracy by increasing the complexity of the detection process but at the expense of detection efficiency. In gateway security products that require high performance or other spam detection products that require high performance, detection efficiency becomes the main performance bottleneck. In order to ensure high bandwidth, users may even choose to turn off such functions, which seriously affects the user experience of gateway security products

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