Biblio

Filters: Author is Cheng, Guozhen  [Clear All Filters]
2023-02-17
Liu, Xuanyu, Cheng, Guozhen, Wang, Yawen, Zhang, Shuai.  2022.  Overview of Scientific Workflow Security Scheduling in Clouds. 2021 International Conference on Advanced Computing and Endogenous Security. :1–6.
With the development of cloud computing technology, more and more scientific researchers choose to deliver scientific workflow tasks to public cloud platforms for execution. This mode effectively reduces scientific research costs while also bringing serious security risks. In response to this problem, this article summarizes the current security issues facing cloud scientific workflows, and analyzes the importance of studying cloud scientific workflow security issues. Then this article analyzes, summarizes and compares the current cloud scientific workflow security methods from three perspectives: system architecture, security model, and security strategy. Finally made a prospect for the future development direction.
2023-09-01
Xie, Genlin, Cheng, Guozhen, Liang, Hao, Wang, Qingfeng, He, Benwei.  2022.  Evaluating Software Diversity Based on Gadget Feature Analysis. 2022 IEEE 8th International Conference on Computer and Communications (ICCC). :1656—1660.
Evaluating the security gains brought by software diversity is one key issue of software diversity research, but the existing software diversity evaluation methods are generally based on conventional code features and are relatively single, which are difficult to accurately reflect the security gains brought by software diversity. To solve these problems, from the perspective of return-oriented programming (ROP) attack, we present a software diversity evaluation method which integrates metrics for the quality and distribution of gadgets. Based on the proposed evaluation method and SpiderMonkey JavaScript engine, we implement a software diversity evaluation system for compiled languages and script languages. Diversity techniques with different granularities are used to test. The evaluation results show that the proposed evaluation method can accurately and comprehensively reflect the security gains brought by software diversity.
2020-02-26
Ai, Jianjian, Chen, Hongchang, Guo, Zehua, Cheng, Guozhen, Baker, Thar.  2019.  Improving Resiliency of Software-Defined Networks with Network Coding-Based Multipath Routing. 2019 IEEE Symposium on Computers and Communications (ISCC). :1–6.

Traditional network routing protocol exhibits high statics and singleness, which provide significant advantages for the attacker. There are two kinds of attacks on the network: active attacks and passive attacks. Existing solutions for those attacks are based on replication or detection, which can deal with active attacks; but are helpless to passive attacks. In this paper, we adopt the theory of network coding to fragment the data in the Software-Defined Networks and propose a network coding-based resilient multipath routing scheme. First, we present a new metric named expected eavesdropping ratio to measure the resilience in the presence of passive attacks. Then, we formulate the network coding-based resilient multipath routing problem as an integer-programming optimization problem by using expected eavesdropping ratio. Since the problem is NP-hard, we design a Simulated Annealing-based algorithm to efficiently solve the problem. The simulation results demonstrate that the proposed algorithms improve the defense performance against passive attacks by about 20% when compared with baseline algorithms.