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Your search keyword '"Liu, Qixu"' showing total 124 results
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124 results on '"Liu, Qixu"'

1. TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification

Author

Zhang, Haozhen, Yu, Le, Xiao, Xi, Li, Qing, Mercaldo, Francesco, Luo, Xiapu, and Liu, Qixu

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Encrypted traffic classification is receiving widespread attention from researchers and industrial companies. However, the existing methods only extract flow-level features, failing to handle short flows because of unreliable statistical properties, or treat the header and payload equally, failing to mine the potential correlation between bytes. Therefore, in this paper, we propose a byte-level traffic graph construction approach based on point-wise mutual information (PMI), and a model named Temporal Fusion Encoder using Graph Neural Networks (TFE-GNN) for feature extraction. In particular, we design a dual embedding layer, a GNN-based traffic graph encoder as well as a cross-gated feature fusion mechanism, which can first embed the header and payload bytes separately and then fuses them together to obtain a stronger feature representation. The experimental results on two real datasets demonstrate that TFE-GNN outperforms multiple state-of-the-art methods in fine-grained encrypted traffic classification tasks., Comment: Accepted by The Web Conference 2023 (WWW'23). The code will be available with our incoming future work

Published
2023

3. Survey of industrial Internet traffic analysis technology

Author

LIU Qixu, XIAO Juxin, TAN Yaokang, WANG Chengchun, HUANG Hao, ZHANG Fangjiao, YIN Jie, and LIU Yuling

Subjects
industrial Internet, industrial control system, traffic analysis, machine learning, Telecommunication, TK5101-6720
Abstract

To gain an in-depth awareness of the application of traffic analysis technology in the industrial Internet, the differences between the industrial Internet and the traditional Internet through the five core traffic analysis processes were illustrated. By reviewing a large number of related papers, the application of six popular were summarized in the industrial Internet, such as traffic prediction, protocol identification and reverse engineering, industrial asset fingerprinting, intrusion detection, encrypted traffic identification and vulnerability mining. Depending on the nature of the task, traffic analysis technology was classified into two types of applications, such as service quality enhancement and security capability development, allowing to thoroughly explore the application scenarios of traffic analysis technology in the industrial Internet. Finally, the challenges associated with future traffic analysis applications in the industrial Internet were examined, as well as potential development possibilities.

Published
2024
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5. AAP: Defending Against Website Fingerprinting Through Burst Obfuscation

Author

Yang, Zhenyu, Xiao, Xi, Zhang, Bin, Hu, Guangwu, Li, Qing, Liu, Qixu, 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, Yang, Xiaochun, editor, Suhartanto, Heru, editor, Wang, Guoren, editor, Wang, Bin, editor, Jiang, Jing, editor, Li, Bing, editor, Zhu, Huaijie, editor, and Cui, Ningning, editor

Published
2023
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7. DeepC2: AI-powered Covert Command and Control on OSNs

Author

Wang, Zhi, Liu, Chaoge, Cui, Xiang, Yin, Jie, Liu, Jiaxi, Wu, Di, and Liu, Qixu

Subjects
Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence
Abstract

Command and control (C&C) is important in an attack. It transfers commands from the attacker to the malware in the compromised hosts. Currently, some attackers use online social networks (OSNs) in C&C tasks. There are two main problems in the C&C on OSNs. First, the process for the malware to find the attacker is reversible. If the malware sample is analyzed by the defender, the attacker would be exposed before publishing the commands. Second, the commands in plain or encrypted form are regarded as abnormal contents by OSNs, which would raise anomalies and trigger restrictions on the attacker. The defender can limit the attacker once it is exposed. In this work, we propose DeepC2, an AI-powered C&C on OSNs, to solve these problems. For the reversible hard-coding, the malware finds the attacker using a neural network model. The attacker's avatars are converted into a batch of feature vectors, and the defender cannot recover the avatars in advance using the model and the feature vectors. To solve the abnormal contents on OSNs, hash collision and text data augmentation are used to embed commands into normal contents. The experiment on Twitter shows that command-embedded tweets can be generated efficiently. The malware can find the attacker covertly on OSNs. Security analysis shows it is hard to recover the attacker's identifiers in advance., Comment: A later version of this paper is accepted at the 24th International Conference on Information and Communications Security (ICICS 2022)

Published
2020

10. DeepC2: AI-Powered Covert Command and Control on OSNs

Author

Wang, Zhi, Liu, Chaoge, Cui, Xiang, Yin, Jie, Liu, Jiaxi, Wu, Di, Liu, Qixu, 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, Alcaraz, Cristina, editor, Chen, Liqun, editor, Li, Shujun, editor, and Samarati, Pierangela, editor

Published
2022
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12. Research and Implementation of Hybrid Encryption System Based on SM2 and SM4 Algorithm

Author

Wang, Zhiqiang, Dong, Hongyu, Chi, Yaping, Zhang, Jianyi, Yang, Tao, Liu, Qixu, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Liu, Qi, editor, Liu, Xiaodong, editor, Li, Lang, editor, Zhou, Huiyu, editor, and Zhao, Hui-Huang, editor

Published
2021
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13. GAN-Based Adversarial Patch for Malware C2 Traffic to Bypass DL Detector

Author

Wang, Junnan, Liu, Qixu, Liu, Chaoge, Yin, Jie, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Gao, Debin, editor, Li, Qi, editor, Guan, Xiaohong, editor, and Liao, Xiaofeng, editor

Published
2021
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14. Automated Honey Document Generation Using Genetic Algorithm

Author

Feng, Yun, Liu, Baoxu, Zhang, Yue, Zhang, Jinli, Liu, Chaoge, Liu, Qixu, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Liu, Zhe, editor, Wu, Fan, editor, and Das, Sajal K., editor

Published
2021
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15. DICOM-Fuzzer: Research on DICOM Vulnerability Mining Based on Fuzzing Technology

Author

Wang, Zhiqiang, Li, Quanqi, Liu, Qian, Liu, Biao, Zhang, Jianyi, Yang, Tao, Liu, Qixu, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Honghao, editor, Feng, Zhiyong, editor, Yu, Jun, editor, and Wu, Jun, editor

Published
2020
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16. CoinBot: A Covert Botnet in the Cryptocurrency Network

Author

Yin, Jie, Cui, Xiang, Liu, Chaoge, Liu, Qixu, Cui, Tao, Wang, Zhi, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Meng, Weizhi, editor, Gollmann, Dieter, editor, Jensen, Christian D., editor, and Zhou, Jianying, editor

Published
2020
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17. WSLD: Detecting Unknown Webshell Using Fuzzy Matching and Deep Learning

Author

Zhao, Zihao, Liu, Qixu, Song, Tiantian, Wang, Zhi, Wu, Xianda, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Zhou, Jianying, editor, Luo, Xiapu, editor, Shen, Qingni, editor, and Xu, Zhen, editor

Published
2020
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20. An Empirical Study of OAuth-Based SSO System on Web

Author

Qiu, Kaili, Liu, Qixu, Liu, Jingqiang, Yu, Lei, Wang, Yiwen, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Chellappan, Sriram, editor, Cheng, Wei, editor, and Li, Wei, editor

Published
2018
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21. Practical Metrics for Evaluating Anonymous Networks

Author

Wang, Zhi, Zhang, Jinli, Liu, Qixu, Cui, Xiang, Su, Junwei, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Liu, Feng, editor, Xu, Shouhuai, editor, and Yung, Moti, editor

Published
2018
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30. A Machine Learning Approach for Detecting Third-Party Trackers on the Web

Author

Wu, Qianru, Liu, Qixu, Zhang, Yuqing, Liu, Peng, Wen, Guanxing, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Askoxylakis, Ioannis, editor, Ioannidis, Sotiris, editor, Katsikas, Sokratis, editor, and Meadows, Catherine, editor

Published
2016
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31. Function Escalation Attack

Author

Cao, Chen, Zhang, Yuqing, Liu, Qixu, Wang, Kai, Akan, Ozgur, Series editor, Bellavista, Paolo, Series editor, Cao, Jiannong, Series editor, Coulson, Geoffrey, Series editor, Dressler, Falko, Series editor, Ferrari, Domenico, Series editor, Gerla, Mario, Series editor, Kobayashi, Hisashi, Series editor, Palazzo, Sergio, Series editor, Sahni, Sartaj, Series editor, Shen, Xuemin Sherman, Series editor, Stan, Mircea, Series editor, Xiaohua, Jia, Series editor, Zomaya, Albert Y., Series editor, Tian, Jing, editor, Jing, Jiwu, editor, and Srivatsa, Mudhakar, editor

Published
2015
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32. IVDroid: Static Detection for Input Validation Vulnerability in Android Inter-component Communication

Author

Fang, Zhejun, Liu, Qixu, Zhang, Yuqing, Wang, Kai, Wang, Zhiqiang, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Lopez, Javier, editor, and Wu, Yongdong, editor

Published
2015
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39. P-Verifier

Author

Jin, Ze, primary, Xing, Luyi, additional, Fang, Yiwei, additional, Jia, Yan, additional, Yuan, Bin, additional, and Liu, Qixu, additional

Published
2022
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47. Crafting Adversarial Example to Bypass Flow-&ML- based Botnet Detector via RL

Author

Junnan Wang, Ying Dong, Xiang Cui, Wu Di, and Liu Qixu

Subjects
Source code, Computer science, media_common.quotation_subject, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, Detector, Botnet, Evasion (network security), Adversarial machine learning, Computer security, computer.software_genre, Field (computer science), Adversarial system, Reinforcement learning, computer, media_common
Abstract

Machine learning(ML)-based botnet detection methods have become mainstream in corporate practice. However, researchers have found that ML models are vulnerable to adversarial attacks, which can mislead the models by adding subtle perturbations to the sample. Due to the complexity of traffic samples and the special constraints that to keep malicious functions, no substantial research of adversarial ML has been conducted in the botnet detection field, where the evasion attacks caused by carefully crafted adversarial examples may directly make ML-based detectors unavailable and cause significant property damage. In this paper, we propose a reinforcement learning(RL) method for bypassing ML-based botnet detectors. Specifically, we train an RL agent as a functionality-preserving botnet flow modifier through a series of interactions with the detector in a black-box scenario. This enables the attacker to evade detection without modifying the botnet source code or affecting the botnet utility. Experiments on 14 botnet families prove that our method has considerable evasion performance and time performance.

Published
2021

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