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Zheng, Yaowen, Song, Zhanwei, Sun, Yuyan, Cheng, Kai, Zhu, Hongsong, Sun, Limin.  2019.  An Efficient Greybox Fuzzing Scheme for Linux-based IoT Programs Through Binary Static Analysis. 2019 IEEE 38th International Performance Computing and Communications Conference (IPCCC). :1–8.
With the rapid growth of Linux-based IoT devices such as network cameras and routers, the security becomes a concern and many attacks utilize vulnerabilities to compromise the devices. It is crucial for researchers to find vulnerabilities in IoT systems before attackers. Fuzzing is an effective vulnerability discovery technique for traditional desktop programs, but could not be directly applied to Linux-based IoT programs due to the special execution environment requirement. In our paper, we propose an efficient greybox fuzzing scheme for Linux-based IoT programs which consist of two phases: binary static analysis and IoT program greybox fuzzing. The binary static analysis is to help generate useful inputs for efficient fuzzing. The IoT program greybox fuzzing is to reinforce the IoT firmware kernel greybox fuzzer to support IoT programs. We implement a prototype system and the evaluation results indicate that our system could automatically find vulnerabilities in real-world Linux-based IoT programs efficiently.
Mi, Xianghang, Feng, Xuan, Liao, Xiaojing, Liu, Baojun, Wang, XiaoFeng, Qian, Feng, Li, Zhou, Alrwais, Sumayah, Sun, Limin, Liu, Ying.  2019.  Resident Evil: Understanding Residential IP Proxy as a Dark Service. 2019 IEEE Symposium on Security and Privacy (SP). :1185—1201.

An emerging Internet business is residential proxy (RESIP) as a service, in which a provider utilizes the hosts within residential networks (in contrast to those running in a datacenter) to relay their customers' traffic, in an attempt to avoid server- side blocking and detection. With the prominent roles the services could play in the underground business world, little has been done to understand whether they are indeed involved in Cybercrimes and how they operate, due to the challenges in identifying their RESIPs, not to mention any in-depth analysis on them. In this paper, we report the first study on RESIPs, which sheds light on the behaviors and the ecosystem of these elusive gray services. Our research employed an infiltration framework, including our clients for RESIP services and the servers they visited, to detect 6 million RESIP IPs across 230+ countries and 52K+ ISPs. The observed addresses were analyzed and the hosts behind them were further fingerprinted using a new profiling system. Our effort led to several surprising findings about the RESIP services unknown before. Surprisingly, despite the providers' claim that the proxy hosts are willingly joined, many proxies run on likely compromised hosts including IoT devices. Through cross-matching the hosts we discovered and labeled PUP (potentially unwanted programs) logs provided by a leading IT company, we uncovered various illicit operations RESIP hosts performed, including illegal promotion, Fast fluxing, phishing, malware hosting, and others. We also reverse engi- neered RESIP services' internal infrastructures, uncovered their potential rebranding and reselling behaviors. Our research takes the first step toward understanding this new Internet service, contributing to the effective control of their security risks.

Yang, Shouguo, Shi, Zhiqiang, Zhang, Guodong, Li, Mingxuan, Ma, Yuan, Sun, Limin.  2019.  Understand Code Style: Efficient CNN-Based Compiler Optimization Recognition System. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). :1–6.
Compiler optimization level recognition can be applied to vulnerability discovery and binary analysis. Due to the exists of many different compilation optimization options, the difference in the contents of the binary file is very complicated. There are thousands of compiler optimization algorithms and multiple different processor architectures, so it is very difficult to manually analyze binary files and recognize its compiler optimization level with rules. This paper first proposes a CNN-based compiler optimization level recognition model: BinEye. The system extracts semantic and structural differences and automatically recognize the compiler optimization levels. The model is designed to be very suitable for binary file processing and is easy to understand. We built a dataset containing 80028 binary files for the model training and testing. Our proposed model achieves an accuracy of over 97%. At the same time, BinEye is a fully CNN-based system and it has a faster forward calculation speed, at least 8 times faster than the normal RNN-based model. Through our analysis of the model output, we successfully found the difference in assembly codes caused by the different compiler optimization level. This means that the model we proposed is interpretable. Based on our model, we propose a method to analyze the code differences caused by different compiler optimization levels, which has great guiding significance for analyzing closed source compilers and binary security analysis.
Wang, Jiye, Sun, Yuyan, Miao, Siwei, Shi, Zhiqiang, Sun, Limin.  2018.  Vulnerability and Protocol Association of Device Firmware in Power Grid. 2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS). :259-263.

The intelligent power grid is composed of a large number of industrial control equipment, and most of the industrial control equipment has security holes, which are vulnerable to malicious attacks and affect the normal operation of the power grid. By analyzing the security vulnerability of the firmware of industrial control equipment, the vulnerability can be detected in advance and the power grid's ability to resist attack can be improved. In this paper, a kind of industrial control device firmware protocol vulnerabilities associated technology, through the technology of information extraction from the mass grid device firmware device attributes and extract the industrial control system, the characteristics of the construction of industrial control system device firmware and published vulnerability information correlation, faster in the industrial control equipment safety inspection found vulnerabilities.