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1,899 results on '"Li, Yahui"'

70. Session-layer Attack Traffic Classification by Program Synthesis

Author

Shi, Lei, Li, Yahui, Alur, Rajeev, and Loo, Boon Thau

Subjects
Computer Science - Programming Languages, Computer Science - Cryptography and Security
Abstract

Writing classification rules to identify malicious network traffic is a time-consuming and error-prone task. Learning-based classification systems automatically extract such rules from positive and negative traffic examples. However, due to limitations in the representation of network traffic and the learning strategy, these systems lack both expressiveness to cover a range of attacks and interpretability in fully describing the attack traffic's structure at the session layer. This paper presents Sharingan system, which uses program synthesis techniques to generate network classification programs at the session layer. Sharingan accepts raw network traces as inputs, and reports potential patterns of the attack traffic in NetQRE, a domain specific language designed for specifying session-layer quantitative properties. Using Sharingan, network operators can better analyze the attack pattern due to the following advantages of Sharingan's learning process: (1) it requires minimal feature engineering, (2) it is amenable to efficient implementation of the learnt classifier, and (3) the synthesized program is easy to decipher and edit. We develop a range of novel optimizations that reduce the synthesis time for large and complex tasks to a matter of minutes. Our experiments show that Sharingan is able to correctly identify attacks from a diverse set of network attack traces and generates explainable outputs, while achieving accuracy comparable to state-of-the-art learning-based intrusion detection systems., Comment: 13 pages

Published
2020

75. Construction and validation of prognostic risk model for hepatocellular carcinoma based on biological analysis of palmitoyl-associated enzyme long-chain non-coding RNA

Author

YU Li, SU Xiandu, ZHANG Min, LI Yahui, and WANG Le

Subjects
hepatocellular carcinoma (hcc), long non-coding rna (lncrna), palmitoylation, risk model, immune therapy, Medicine
Abstract

Objective·To explore the effect of screening the expression of long non-coding RNA (lncRNA) related to palmitoylation on prognosis of liver cancer based on The Cancer Genome Atlas (TCGA) database and construct a risk prediction model in liver cancer.Methods·The sequencing data and the corresponding clinical information of 374 liver cancer tissues and 50 normal tissue samples were downloaded from TCGA database. The differential zinc finger aspartate-histidine-histidine-cysteine domain (ZDHHC) between liver cancer tissues and normal tissues was used to construct the expression profile of lncRNA related to ZDHHC. Furthermore, the prediction model was constructed by LASSO regression algorithm and the validity of the model prediction was verified to analyze the relationship between high-risk and low-risk groups and immune function and to predict the response to immunotherapy.Results·There were 20 differentially expressed ZDHHCs in hepatocellular carcinoma, among which 656 lncRNAs were correlated with differential ZDHHCs (all P

Published
2023
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86. Security-Constrained Multi-Objective Optimal Power Flow for a Hybrid AC/VSC-MTDC System with Lasso-based Contingency Filtering

Author

Li, Yahui and Li, Yang

Subjects
Electrical Engineering and Systems Science - Signal Processing, Electrical Engineering and Systems Science - Systems and Control, Mathematics - Optimization and Control
Abstract

In order to coordinate the economy and voltage quality of a meshed AC/VSC-MTDC system, a new corrective security-constrained multi-objective optimal power flow (SC-MOPF) method is presented in this paper. A parallel SC-MOPF model with N-1 security constraints is proposed for corrective control actions of the meshed AC/DC system, in which the minimization of the generation cost and voltage deviation are used as objective functions. To solve this model, a novel parallel bi-criterion evolution indicator based evolutionary algorithm (BCE-IBEA) algorithm is developed to seek multiple well-spread Pareto-optimal solutions through the introduction of parallel computation. In this process, a least absolute shrinkage and selection operator (Lasso)-based N-1 contingency filtering scheme with a composite security index is developed to efficiently screen out the most severe cases from all contingencies. And thereby, the best compromise solutions reflecting the preferences of different decision makers are automatically determined via an integrated decision making technique. Case studies in the modified IEEE 14- and 300- bus systems demonstrate that the presented approach manages to address this SC-MOPF problem with significantly improved computational efficiency., Comment: Accepted by IEEE Access

Published
2019
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89. Driving Driven Lattice Gases to Identify Their Universality Classes

Author

Li, Yahui, Zeng, Zhongda, and Zhong, Fan

Subjects
Condensed Matter - Statistical Mechanics
Abstract

The critical behavior of driven lattice gas models has been studied for decades as a paradigm to explore nonequilibrium phase transitions and critical phenomena. However, there exists a long-standing controversy in the universality classes to which they belong. This is of paramount importance as it implies the question of whether or not a microscopic model and its mesoscopic field theory may possess different symmetries in nonequilibrium critical phenomena in contrast to their equilibrium counterparts. Here, we heat with finite rates two generic models of driven lattice gases across their respective nonequilibrium critical points into further nonequilibrium conditions. Employing the theory of finite-time scaling, we are able to unambiguously discriminate the universality classes between the two models. In particular, the infinitely driven lattice gas and the randomly driven lattice gas models belong to different universality classes. These results show that finite-time scaling is effective even in nonequilibrium phase transitions., Comment: 6 pages, 3 figures

Published
2019
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90. A rare gain of function mutation in a wheat tandem kinase confers resistance to powdery mildew.

Author

Lu, Ping, Guo, Li, Wang, Zhenzhong, Li, Beibei, Li, Jing, Li, Yahui, Qiu, Dan, Shi, Wenqi, Yang, Lijun, Wang, Ning, Guo, Guanghao, Xie, Jingzhong, Wu, Qiuhong, Chen, Yongxing, Li, Miaomiao, Zhang, Huaizhi, Dong, Lingli, Zhang, Panpan, Zhu, Keyu, Yu, Dazhao, Zhang, Yan, Deal, Karin, Huo, Naxin, Liu, Cuimin, Luo, Ming-Cheng, Dvorak, Jan, Gu, Yong, Li, Hongjie, and Liu, Zhiyong

Subjects
Ascomycota, China, Disease Resistance, Gain of Function Mutation, Genes, Plant, Hydrogen Peroxide, Mutagenesis, Plant Diseases, Plant Immunity, Plant Proteins, Plants, Genetically Modified, Protein Domains, Protein Kinases, Transformation, Genetic, Triticum
Abstract

Powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is one of the most destructive diseases that pose a great threat to wheat production. Wheat landraces represent a rich source of powdery mildew resistance. Here, we report the map-based cloning of powdery mildew resistance gene Pm24 from Chinese wheat landrace Hulutou. It encodes a tandem kinase protein (TKP) with putative kinase-pseudokinase domains, designated WHEAT TANDEM KINASE 3 (WTK3). The resistance function of Pm24 was validated by transgenic assay, independent mutants, and allelic association analyses. Haplotype analysis revealed that a rare 6-bp natural deletion of lysine-glycine codons, endemic to wheat landraces of Shaanxi Province, China, in the kinase I domain (Kin I) of WTK3 is critical for the resistance function. Transgenic assay of WTK3 chimeric variants revealed that only the specific two amino acid deletion, rather than any of the single or more amino acid deletions, in the Kin I of WTK3 is responsible for gaining the resistance function of WTK3 against the Bgt fungus.

Published
2020

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