In recent years, with the rapid development of mobile Internet and 5G technology, great changes have been brought to our lives, and human beings have stepped into the era of big data. These new features and techniques in 5G support many different types of mobile applications for users, which makes network security extremely challenging. Among them, more and more applications involve users’ private data, such as location information, financial information, and biological information. In order to prevent users’ privacy disclosure, most applications choose to use private protocols. However, such private protocols also provide a means for malware and malicious applications to steal users’ privacy and confidential data. From a more secure point of view, we need to provide a way for users to know how many private protocols are running on their mobile phones and distinguish which are authorized applications and which are not. Therefore, the analysis and identification of private protocols have become a hot topic in current research. How to extract the characteristics of network protocol effectively and identify the private protocol accurately becomes the most important part of this research. In this paper, we combine genetic algorithm and association rule algorithm and then propose a set of feature extraction algorithm and protocol recognition algorithm for unknown protocols. The experimental analysis based on the actual data shows that these methods can effectively solve the problems of feature extraction and recognition for unknown protocols and can greatly improve the accuracy of private protocol recognition.

Background: The Hepatocyte Growth Factor Receptor (HGFR) c-Met is over-expressed and/or mutated in various human tumor types. Dysregulation of c-Met/HGF signaling pathway affects cell proliferation, survival and motility, leading to tumor growth, angiogenesis, and metastasis. Therefore, c-Met has become an attractive target for cancer therapy. Objective: This study is aimed to evaluate a new series of 4-phenoxypyridine derivatives containing semicarbazones moiety for its cytotoxicity. Methods: A series of novel 4-phenoxypyridines containing semicarbazone moieties were synthesized and evaluated for their in vitro cytotoxic activities against MKN45 and A549 cancer cell lines and some selected compounds were further examined for their inhibitory activity against c-Met kinase. In order to evaluate the mechanism of cytotoxic activity of compound 24, cell cycle analysis, Annexin V/PI staining assay, AO/EB assay, wound-healing assay and docking analysis with c-Met were performed. Results: The results indicated that most of the compounds showed moderate to good antitumor activity. The compound 28 showed well cytotoxic activity against MKN45 and A549 cell lines with IC50 values of 0.25μM and 0.67μM, respectively. Compound 24 showed good activity on c-Met and its IC50 value was 0.093μM. Conclusion: Their preliminary Structure-Activity Relationships (SARs) studies indicated that electronwithdrawing groups on the terminal phenyl rings are beneficial for improving the antitumor activity. Treatments of MKN45 cells with compound 24 resulted in cell cycle arrest in G2/M phase and induced apoptosis in a dose-dependent manner. In addition, AO/EB assays indicated 24 induced dose-dependent apoptosis of A549 and MKN45 cells. Wound-healing assay results indicated that compound 24 strongly inhibited A549 cell motility.