Search

Your search keyword '"Liu, YuLing"' showing total 2,032 results
Start Over Author "Liu, YuLing"
2,032 results on '"Liu, YuLing"'

1. Are Watermarks Bugs for Deepfake Detectors? Rethinking Proactive Forensics

Author

Wu, Xiaoshuai, Liao, Xin, Ou, Bo, Liu, Yuling, and Qin, Zheng

Subjects
Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

AI-generated content has accelerated the topic of media synthesis, particularly Deepfake, which can manipulate our portraits for positive or malicious purposes. Before releasing these threatening face images, one promising forensics solution is the injection of robust watermarks to track their own provenance. However, we argue that current watermarking models, originally devised for genuine images, may harm the deployed Deepfake detectors when directly applied to forged images, since the watermarks are prone to overlap with the forgery signals used for detection. To bridge this gap, we thus propose AdvMark, on behalf of proactive forensics, to exploit the adversarial vulnerability of passive detectors for good. Specifically, AdvMark serves as a plug-and-play procedure for fine-tuning any robust watermarking into adversarial watermarking, to enhance the forensic detectability of watermarked images; meanwhile, the watermarks can still be extracted for provenance tracking. Extensive experiments demonstrate the effectiveness of the proposed AdvMark, leveraging robust watermarking to fool Deepfake detectors, which can help improve the accuracy of downstream Deepfake detection without tuning the in-the-wild detectors. We believe this work will shed some light on the harmless proactive forensics against Deepfake., Comment: Accepted by IJCAI 2024

Published
2024

2. E-DoH: Elegantly Detecting the Depths of Open DoH Service on the Internet

Author

Dong, Cong, Yang, Jiahai, Li, Yun, Wu, Yue, Chen, Yufan, Li, Chenglong, Jiao, Haoran, Yin, Xia, and Liu, Yuling

Subjects
Computer Science - Cryptography and Security, Computer Science - Networking and Internet Architecture
Abstract

In recent years, DNS over Encrypted (DoE) methods have been regarded as a novel trend within the realm of the DNS ecosystem. In these DoE methods, DNS over HTTPS (DoH) provides encryption to protect data confidentiality while providing better obfuscation to avoid censorship by multiplexing port 443 with web services. This development introduced certain inconveniences in discovering publicly available DoH services. In this paper, we propose the E-DoH method for elegant and efficient DoH service detection. First, we optimized the probing mechanism to enable a single DoH connection to accomplish multiple tasks including service discovery, correctness validation and dependency construction. Second, we propose an efficient DoH detection tool. This tool can enhance probing efficiency while significantly reduce the required traffic volume. Third, based on the above optimization methods, we conducted an exploration of the IPv4 space and performed an in-depth analysis of DoH based on the collected information. Through experiments, our approach demonstrates a remarkable 80% improvement in time efficiency, and only requires 4%-20% traffic volume to complete the detection task. In wild detection, our approach discovered 46k DoH services, which nearly doubles the number discovered by the state-of-the-art. Based on the collected data, we present several intriguing conclusions about the current DoH service ecosystem.

Published
2024

5. Mettl3 induced miR‐338‐3p expression in dendritic cells promotes antigen‐specific Th17 cell response via regulation of Dusp16

Author

Wei, Yankai, Yang, Chao, Liu, Yuling, Sun, Deming, Li, Xiaorong, Wei, Ruihua, and Nian, Hong

Subjects
Biomedical and Clinical Sciences, Immunology, Autoimmune Disease, Biotechnology, Prevention, Biodefense, Eye Disease and Disorders of Vision, Vaccine Related, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Animals, Th17 Cells, Autoimmune Diseases, Methyltransferases, p38 Mitogen-Activated Protein Kinases, Uveitis, Dendritic Cells, MicroRNAs, Dusp16, Mettl3, Th17 cell, dendritic cells, miR-338-3p, p38 signaling, Biochemistry and Cell Biology, Physiology, Medical Physiology, Biochemistry & Molecular Biology, Biochemistry and cell biology, Medical physiology
Abstract

Pathogenic Th17 cells are critical drivers of multiple autoimmune diseases, including uveitis and its animal model, experimental autoimmune uveitis (EAU). However, how innate immune signals modulate pathogenic Th17 responses remains largely unknown. Here, we showed that miR-338-3p endowed dendritic cells (DCs) with an increased ability to activate interphotoreceptor retinoid-binding protein (IRBP)1-20 -specific Th17 cells by promoting the production of IL-6, IL-1β, and IL-23. In vivo administration of LV-miR-338-infected DCs promoted pathogenic Th17 responses and exacerbated EAU development. Mechanistically, dual-specificity phosphatase 16 (Dusp16) was a molecular target of miR-338-3p. miR-338-3p repressed Dusp16 and therefore strengthened the mitogen-activated protein kinase (MAPK) p38 signaling, resulting in increased production of Th17-polarizing cytokines and subsequent pathogenic Th17 responses. In addition, methyltransferase like 3 (Mettl3), a key m6A methyltransferase, mediated the upregulation of miR-338-3p in activated DCs. Together, our findings identify a vital role for Mettl3/miR-338-3p/Dusp16/p38 signaling in DCs-driven pathogenic Th17 responses and suggest a potential therapeutic avenue for uveitis and other Th17 cell-related autoimmune disorders.

Published
2023

6. CBSeq: A Channel-level Behavior Sequence For Encrypted Malware Traffic Detection

Author

Cui, Susu, Dong, Cong, Shen, Meng, Liu, Yuling, Jiang, Bo, and Lu, Zhigang

Subjects
Computer Science - Cryptography and Security
Abstract

Machine learning and neural networks have become increasingly popular solutions for encrypted malware traffic detection. They mine and learn complex traffic patterns, enabling detection by fitting boundaries between malware traffic and benign traffic. Compared with signature-based methods, they have higher scalability and flexibility. However, affected by the frequent variants and updates of malware, current methods suffer from a high false positive rate and do not work well for unknown malware traffic detection. It remains a critical task to achieve effective malware traffic detection. In this paper, we introduce CBSeq to address the above problems. CBSeq is a method that constructs a stable traffic representation, behavior sequence, to characterize attacking intent and achieve malware traffic detection. We novelly propose the channels with similar behavior as the detection object and extract side-channel content to construct behavior sequence. Unlike benign activities, the behavior sequences of malware and its variant's traffic exhibit solid internal correlations. Moreover, we design the MSFormer, a powerful Transformer-based multi-sequence fusion classifier. It captures the internal similarity of behavior sequence, thereby distinguishing malware traffic from benign traffic. Our evaluations demonstrate that CBSeq performs effectively in various known malware traffic detection and exhibits superior performance in unknown malware traffic detection, outperforming state-of-the-art methods., Comment: Submitted to IEEE TIFS

Published
2023

13. Study on the Prevention and Control Mechanism for Minors’ Involvement in Telecom and Online Fraud : --Based on the Law of the People’s Republic of China on Combating Telecom and Online Fraud

Author

Ma, Yanan, Liu, Yuling, Wang, Hejiao, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Zhan, Zehui, editor, Liu, Jian, editor, Elshenawi, Dina M., editor, and Duester, Emma, editor

Published
2024
Full Text
View/download PDF

14. DFT-3DLaneNet: Dual-Frequency Domain Enhanced Transformer for 3D Lane Detection

Author

Li, Kaijiang, Liu, Yuling, Wang, Peisen, Liu, XiangQian, Liu, Xichen, Guo, ChunYi, Zhou, Bing, Goos, Gerhard, Series 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, Huang, De-Shuang, editor, Si, Zhanjun, editor, and Pan, Yijie, editor

Published
2024
Full Text
View/download PDF

15. TAElog: A Novel Transformer AutoEncoder-Based Log Anomaly Detection Method

Author

Zhao, Changzhi, Huang, Kezhen, Wu, Di, Han, Xueying, Du, Dan, Zhou, Yutian, Lu, Zhigang, Liu, Yuling, 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, and Ge, Chunpeng, editor

Published
2024
Full Text
View/download PDF

16. Research on Camouflage Target Detection Method Based on Dual Band Optics and SAR Image Fusion

Author

Zhang, Tong, Zhang, Dongfang, Liu, Yuling, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, You, Peng, editor, Liu, Shuaiqi, editor, and Wang, Jun, editor

Published
2024
Full Text
View/download PDF

46. Genome-wide chromatin accessibility landscape and dynamics of transcription factor networks during ovule and fiber development in cotton

Author

Bao, Yu, Wei, Yangyang, Liu, Yuling, Gao, Jingjing, Cheng, Shuang, Liu, Guanqing, You, Qi, Liu, Peng, Lu, Quanwei, Li, Pengtao, Zhang, Shulin, Hu, Nan, Han, Yangshuo, Liu, Shuo, Wu, Yuechao, Yang, Qingqing, Li, Zhaoguo, Ao, Guowei, Liu, Fang, Wang, Kunbo, Jiang, Jiming, Zhang, Tao, Zhang, Wenli, and Peng, Renhai

Published
2023
Full Text
View/download PDF

48. Chinese Children's Heterogeneous Friendship Quality Trajectories: Relations with School Adjustment

Author

Liu, Yuling, Huebner, E. Scott, and Tian, Lili

Abstract

Friendships affect children's development and adjustment. This longitudinal study examined the possible heterogeneity and gender differences in the trajectories of children's friendship quality, as well as the relations between distinct friendship quality trajectories and school adjustment. A total of 3,779 Chinese elementary school students (45.5% girls, M[subscript age] = 9.94 years, SD = 0.72 at Time 1) completed measures of relevant constructs on five occasions at 6-month intervals. Latent class growth modeling revealed four heterogeneous developmental trajectory classes of friendship quality: high-increasing (49.6%), moderate-decreasing (5.1%), moderate-increasing (31.9%), and low-stable (13.4%). Girls were more likely than boys to fall into the higher friendship quality trajectory classes in reference to the low-stable class. Children in the high-increasing class and low-stable class showed the best and the worst school adjustment, respectively. The identification of four heterogeneous developmental trajectories of friendship quality with differential school adjustment outcomes highlights the importance of intervention programs tailored to specific groups for promoting children's friendship quality and school adjustment.

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results