App Tamper Detection and Retrospective Program Research
In recent years, the rapid development of mobile Internet, the arrival of 3G, 4G era, the decline in the cost of production of smart mobile terminals, smart phones in people learning, work and life in the penetration rate is higher and higher. But some of the free open source platform features not only give developers a broader space for development, but also to the user to add a lot of security risks, especially the risk of APP to tamper-based. Based on the research of APP tampering detection and retrospective research, this paper elaborates its research background and significance, and introduces the present situation of mainstream protection technology. Then, it introduces the reliable identification of APP tampering, tampering with APP’s retrospective and tampering with APP risk surface Evaluation, probe SDK self-protection technology program design, and the program to test the environment deployment, display functional effects.e sheet.
KeywordsAPP tamper detection Tampering with the retrospective of APP APP tamper with the reliable knowledge Tampering with APP’s risk assessment
This work is supported by the Key Disciplines of Computer Science and Technology of Shanghai Polytechnic University under Grant No. XXKZD1604 and supported by the Shanghai Alliance Program under Grant No. LM201673.
- 1.Becher, M.: Computer Security Art and Science. Addison-Wesley Longman Publishing Co., Inc., Boston (2003)Google Scholar
- 2.Jiang, W., Lin, S.: Exploration and practice of various forms in university-enterprise cooperation model on colleges and universities. In: 2012 International Conference on Education Reform and Management Innovation (ERMI 2012), vol. 2012, no. 12, pp. 403–408. Information Engineering Research Institute, Shenzhen (2012)Google Scholar
- 5.Eswaraiah, R., Reddy, E.S.: A fragile ROI-based medical image watermarking technique with tamper detection and recovery. In: Fourth International Conference on Communication Systems and Network Technologies. IEEE Computer Society (2014)Google Scholar
- 7.Jiang, W., Wang, A., Wu, C., Chen, J., Yan, J.: Approach for name ambiguity problem using a multiple-layer clustering. In: The 2009 IEEE International Conference on Social Computing (SocialCom-09) (2009)Google Scholar
- 8.Bang, J., Cho, H., Ji, M., et al.: Tamper detection scheme using signature segregation on android platform. In: IEEE International Conference on Consumer Electronics (2016)Google Scholar
- 9.Suh, G.E., Fletcher, C., et al.: Author retrospective AEGIS: architecture for tamper-evident and tamper-resistant processing (2014)Google Scholar