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24 results on '"Yan, Huaiyu"'

1. On Manually Reverse Engineering Communication Protocols of Linux Based IoT Systems

Author

Liu, Kaizheng, Yang, Ming, Ling, Zhen, Yan, Huaiyu, Zhang, Yue, Fu, Xinwen, and Zhao, Wei

Subjects
Computer Science - Cryptography and Security
Abstract

IoT security and privacy has raised grave concerns. Efforts have been made to design tools to identify and understand vulnerabilities of IoT systems. Most of the existing protocol security analysis techniques rely on a well understanding of the underlying communication protocols. In this paper, we systematically present the first manual reverse engineering framework for discovering communication protocols of embedded Linux based IoT systems. We have successfully applied our framework to reverse engineer a number of IoT systems. As an example, we present a detailed use of the framework reverse-engineering the WeMo smart plug communication protocol by extracting the firmware from the flash, performing static and dynamic analysis of the firmware and analyzing network traffic. The discovered protocol exposes severe design flaws that allow attackers to control or deny the service of victim plugs. Our manual reverse engineering framework is generic and can be applied to both read-only and writable Embedded Linux filesystems.

Published
2020

2. fASLR: Function-Based ASLR for Resource-Constrained IoT Systems

Author

Shao, Xinhui, Luo, Lan, Ling, Zhen, Yan, Huaiyu, Wei, Yumeng, Fu, Xinwen, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Atluri, Vijayalakshmi, editor, Di Pietro, Roberto, editor, Jensen, Christian D., editor, and Meng, Weizhi, editor

Published
2022
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10. Transverse distribution of cyanobacteria in a regulated urban river

Author

Yan, Huaiyu, Wang, Hua, He, Xinchen, Liu, Yulin, Tang, Quanyin, Yang, Yeye, Yuan, Weihao, Yan, Huaiyu, Wang, Hua, He, Xinchen, Liu, Yulin, Tang, Quanyin, Yang, Yeye, and Yuan, Weihao

Abstract

River eutrophication and CyanoHABs are severe problems that are often ignored because of high current speed and strong self-purification. In this paper, Liangxi River, Taihu Basin, was selected as the research area. Combined with field investigation, a 2D water environment mathematical model was developed to simulate the chl-a distribution in Liangxi River. An indicator (Transverse Distribution Center, TDC) and its normalized form (NTDC) to quantitatively represent material transverse distribution in rivers is proposed and coupled in the model. The calculation showed that TDC and NTDC had the property of random fluctuation, seasonal consistency, and water transfer dependence. The multiple regression equation with normalized data indicated that the maximum offset, average variation rate, and average reverting rate of Liangxi River chl-a NTDC were most affected by the chl-a dry matter flux ratio between tributaries and the mainstream, followed by flow and chl-a concentration ratio. From the perspective of river morphology, for different river width change modes and river bending directions, when water flows into and out of these river sections, the chl-a transverse distribution is subject to different specific effects. In addition, the position of nutrients and dissolved oxygen significantly affected the position of chl-a growth when the N/P ratio was not very high. Conversely, a high N/P ratio may contribute to decrease of the chl-a concentration. Proliferation with abundant nutrients may cause the settlement of chl-a resulting in a decrease of chl-a in the water column. © 2020 John Wiley & Sons, Ltd.

Published
2020

18. Dynamics of nutrient export from the Yangtze River to the East China sea

Author

Yan Huaiyu, Wang Hua, Zhou Feng-nian, Zhuang Wei, Yang Yeye, and Li Bao

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, 010604 marine biology & hydrobiology, Nutrient flux, Aquatic Science, Oceanography, 01 natural sciences, Nutrient, Animal science, Flux (metallurgy), Water transfer, Yangtze river, Environmental science, Annual variation, 0105 earth and related environmental sciences, China sea, Three gorges
Abstract

River-sea transition plays a key role in global geochemical cycles. This study proposed a Section-Segmented Method (SSM) to determine the nutrient discharge from the Yangtze River to the East China Sea (ECS), against the high-density data of water flux and nutrient by the combination of artificial and tele-control monitoring. During 2012–2016, the nutrient delivery exhibited a pronounced inter annual variation, and the mean fluxes of TN and TP were respectively 1.69 Tg/yr and 0.11 Tg/yr. The year of 2016 was characterized by the highest level, with the loads of 2.00 Tg and 0.115 Tg for TN and TP, respectively. The river transported the maximum monthly flux in July, yielding 270.97 Gg and 15.62 Gg for TN and TP, respectively. The 5-year mean daily TN and TP flux were respectively 4.62 Gg and 0.27 Gg. The daily nutrient flux showed a pronounced and positive relationship with net water flux, but due to the different input modes of N and P, TP flux displayed a higher dispersion than TN. The degrees influenced by the South-to-North Water Transfer Project (SNWTP) in the nutrient delivery were stably maintained at the level of 2.50% and 2.36% for TN and TP, respectively, whereas the Three Gorges Dam (TGD) just harnessed 0.60% and 0.26%.

Published
2019

24. Numerical simulation of microcystin distribution in Liangxi River, downstream of Taihu Lake.

Author

He X, Wang H, Yan H, and Ao Y

Subjects
China, Environmental Monitoring, Rivers, Lakes, Microcystins analysis
Abstract

Microcystins (MCs), the algal toxins produced by cyanobacteria, raised a worldwide concern in recent decades. Limited monitoring stations for MCs make it hard to map the MC spatial distribution in certain areas. To tackle such problems, we selected Liangxi River as our research area and developed an integrated model to get spatial continuous MC data without too many sampling sites, which integrates a hydro-environment model and an artificial neural network algorithm (ANN). The ANN algorithm can estimate concentration MCs via environmental factors. In this paper, we selected chl-a, TN, TP, NO 2 - , NO 3 - , NH 3 -N, and PO 4 3 - as stressors. The ANN model we established showed good performances both in train (R 2  = 0.8407) and test set (R 2  = 0.7543). In the hydro-environment model, by inputting river geometry and model boundary data, the spatial continuous water quality data could be simulated. The water quality data returned from the hydro-environmental model were used as input variables of the well-trained ANN model; the continuous MC data were derived. To evaluate this model on geo-mapping the MC distribution in Liangxi River, we compared the performance of this model and spatial interpolation on the test set, it turns out the integrated model showed a better performance. © 2020 Water Environment Federation PRACTITIONER POINTS: The cost of microcystin (MC) detection is too high for routine monitoring. We integrated regression method and hydro-environment model to predict MCs. Results derived from spatial interpolation are not robust in unmonitored area. The new integration model can minimize the drawback of spatial interpolation., (© 2020 Water Environment Federation.)

Published
2021
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