Browsing by Author "Liu, Fang"

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    Enterprise data breach: causes, challenges, prevention, and future directions
    Cheng, Long; Liu, Fang; Yao, Danfeng (Daphne) (Wiley, 2017)
    A data breach is the intentional or inadvertent exposure of confidential information to unauthorized parties. In the digital era, data has become one of the most critical components of an enterprise. Data leakage poses serious threats to organizations, including significant reputational damage and financial losses. As the volume of data is growing exponentially and data breaches are happening more frequently than ever before, detecting and preventing data loss has become one of the most pressing security concerns for enterprises. Despite a plethora of research efforts on safeguarding sensitive information from being leaked, it remains an active research problem. This review helps interested readers to learn about enterprise data leak threats, recent data leak incidents, various state-of-the-art prevention and detection techniques, new challenges, and promising solutions and exciting opportunities.
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    Forbidden City: An Immersive Virtual Reality World Using the HTC VIVE to explore the real imperial palace of China
    Liu, Fang (Virginia Tech, 2017-06-07)
    Forbidden City is a 3D virtual tour of an ancient Chinese architectural masterpiece, first of the world's top five palaces -The Imperial Palace in Beijing, China. This travel guide is designed to give you useful information that will greatly enhance your experience, and it will bring you into an immersive virtual world by using the device of the HTC VIVE rather than static texts and images. This 3D guide integrates cultural and historical information, which is practical and informative. You can get a comprehensive understanding of the palace history, architectural characteristics and Chinese culture through interaction within the immersive experience. Forbidden City travel guide 3D virtual tour provides all the necessary functions and information for planning a visit to the Forbidden Cty palace in the capital of Beijing, China. With the tour guide character "Doctor Guider" within this experience/game, your tour to this Forbidden City will be purposeful and fun.
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    Measurement of the B0 lifetime and flavor-oscillation frequency using hadronic decays reconstructed in 2019-2021 Belle II data
    Ablikim, M.; Achasov, M. N.; Adlarson, P.; Ahmed, S.; Albrecht, M.; Amoroso, A.; An, Q.; Bai, X. H.; Bai, Y.; Bakina, O.; Ferroli, R. Baldini; Balossino, I.; Ban, Y.; Begzsuren, K.; Bennett, J.; Berger, N.; Bertani, M.; Bettoni, D.; Bianchi, F.; Biernat, J.; Bloms, J.; Bortone, A.; Boyko, I.; Briere, R. A.; Cai, H.; Cai, X.; Calcaterra, A.; Cao, G. F.; Cao, N.; Cetin, S. A.; Chang, J. F.; Chang, W. L.; Chelkov, G.; Chen, D. Y.; Chen, G.; Chen, H. S.; Chen, M. L.; Chen, S. J.; Chen, X. R.; Chen, Y. B.; Cheng, W.; Cibinetto, G.; Cossio, F.; Cui, X. F.; Dai, H. L.; Dai, J. P.; Dai, X. C.; Dbeyssi, A.; de Boer, R. B.; Dedovich, D.; Deng, Z. Y.; Denig, A.; Denysenko, I.; Destefanis, M.; De Mori, F.; Ding, Y.; Dong, C.; Dong, J.; Dong, L. Y.; Dong, M. Y.; Du, S. X.; Fang, J.; Fang, S. S.; Fang, Y.; Farinelli, R.; Fava, L.; Feldbauer, F.; Felici, G.; Feng, C. Q.; Fritsch, M.; Fu, C. D.; Fu, Y.; Gao, X. L.; Gao, Y.; Gao, Y.; Gao, Y. G.; Garzia, I.; Gersabeck, E. M.; Gilman, A.; Goetzen, K.; Gong, L.; Gong, W. X.; Gradl, W.; Greco, M.; Gu, L. M.; Gu, M. H.; Gu, S.; Gu, Y. T.; Guan, C. Y.; Guo, A. Q.; Guo, L. B.; Guo, R. P.; Guo, Y. P.; Guskov, A.; Han, S.; Han, T. T.; Han, T. Z.; Hao, X. Q.; Harris, F. A.; He, K. L.; Heinsius, F. H.; Held, T.; Heng, Y. K.; Himmelreich, M.; Holtmann, T.; Hou, Y. R.; Hou, Z. L.; Hu, H. M.; Hu, J. F.; Hu, T.; Hu, Y.; Huang, G. S.; Huang, L. Q.; Huang, X. T.; Huesken, N.; Hussain, T.; Andersson, W. Ikegami; Imoehl, W.; Irshad, M.; Jaeger, S.; Ji, Q.; Ji, Q. P.; Ji, X. B.; Ji, X. L.; Jiang, H. B.; Jiang, X. S.; Jiang, X. Y.; Jiao, J. B.; Jiao, Z.; Jin, S.; Jin, Y.; Johansson, T.; Kalantar-Nayestanaki, N.; Kang, X. S.; Kappert, R.; Kavatsyuk, M.; Ke, B. C.; Keshk, I. K.; Khoukaz, A.; Kiese, P.; Kiuchi, R.; Kliemt, R.; Koch, L.; Kolcu, O. B.; Kopf, B.; Kuemmel, M.; Kuessner, M.; Kupsc, A.; Kurth, M. G.; Kuehn, W.; Lane, J. J.; Lange, J. S.; Larin, P.; Lavezzi, L.; Leithoff, H.; Lellmann, M.; Lenz, T.; Li, C.; Li, C. H.; Li, Cheng; Li, D. M.; Li, F.; Li, G.; Li, H. B.; Li, H. J.; Li, J. L.; Li, J. Q.; Li, Ke; Li, L. K.; Li, Lei; Li, P. L.; Li, P. R.; Li, W. D.; Li, W. G.; Li, X. H.; Li, X. L.; Li, Z. B.; Li, Z. Y.; Liang, H.; Liang, H.; Liang, Y. F.; Liang, Y. T.; Liao, L. Z.; Libby, J.; Lin, C. X.; Liu, B.; Liu, B. J.; Liu, C. X.; Liu, D.; Liu, D. Y.; Liu, F. H.; Liu, Fang; Liu, Feng; Liu, H. B.; Liu, H. M.; Liu, Huanhuan; Liu, Huihui; Liu, J. B.; Liu, J. Y.; Liu, K.; Liu, K. Y.; Liu, Ke; Liu, L.; Liu, L. Y.; Liu, Q.; Liu, S. B.; Liu, T.; Liu, X.; Liu, Y. B.; Liu, Z. A.; Liu, Zhiqing; Long, Y. F.; Lou, X. C.; Lu, H. J.; Lu, J. D.; Lu, J. G.; Lu, X. L.; Lu, Y.; Lu, Y. P.; Luo, C. L.; Luo, M. X.; Luo, P. W.; Luo, T.; Luo, X. L.; Lusso, S.; Lyu, X. R.; Ma, F. C.; Ma, H. L.; Ma, L. L.; Ma, M. M.; Ma, Q. M.; Ma, R. Q.; Ma, R. T.; Ma, X. N.; Ma, X. X.; Ma, X. Y.; Ma, Y. M.; Maas, F. E.; Maggiora, M.; Maldaner, S.; Malde, S.; Malik, Q. A.; Mangoni, A.; Mao, Y. J.; Mao, Z. P.; Marcello, S.; Meng, Z. X.; Messchendorp, J. G.; Mezzadri, G.; Min, T. J.; Mitchell, R. E.; Mo, X. H.; Mo, Y. J.; Muchnoi, N. Yu; Muramatsu, H.; Nakhoul, S.; Nefedov, Y.; Nerling, F.; Nikolaev, I. B.; Ning, Z.; Nisar, S.; Olsen, S. L.; Ouyang, Q.; Pacetti, S.; Pan, Y.; Pan, Y.; Papenbrock, M.; Pathak, A.; Patteri, P.; Pelizaeus, M.; Peng, H. P.; Peters, K.; Pettersson, J.; Ping, J. L.; Ping, R. G.; Pitka, A.; Poling, R.; Prasad, V.; Qi, H.; Qi, M.; Qi, T. Y.; Qian, S.; Qiao, C. F.; Qin, L. Q.; Qin, X. P.; Qin, X. S.; Qin, Z. H.; Qiu, J. F.; Qu, S. Q.; Rashid, K. H.; Ravindran, K.; Redmer, C. F.; Rivetti, A.; Rodin, V.; Rolo, M.; Rong, G.; Rosner, Ch; Rump, M.; Sarantsev, A.; Savrie, M.; Schelhaas, Y.; Schnier, C.; Schoenning, K.; Shan, W.; Shan, X. Y.; Shao, M.; Shen, C. P.; Shen, P. X.; Shen, X. Y.; Shi, H. C.; Shi, R. S.; Shi, X.; Shi, X. D.; Song, J. J.; Song, Q. Q.; Song, Y. X.; Sosio, S.; Spataro, S.; Sui, F. F.; Sun, G. X.; Sun, J. F.; Sun, L.; Sun, S. S.; Sun, T.; Sun, W. Y.; Sun, Y. J.; Sun, Y. K.; Sun, Y. Z.; Sun, Z. T.; Tan, Y. X.; Tang, C. J.; Tang, G. Y.; Thoren, V.; Tsednee, B.; Uman, I.; Wang, B.; Wang, B. L.; Wang, C. W.; Wang, D. Y.; Wang, H. P.; Wang, K.; Wang, L. L.; Wang, M.; Wang, M. Z.; Wang, Meng; Wang, W. P.; Wang, X.; Wang, X. F.; Wang, X. L.; Wang, Y.; Wang, Y.; Wang, Y. D.; Wang, Y. F.; Wang, Y. Q.; Wang, Z.; Wang, Z. Y.; Wang, Ziyi; Wang, Zongyuan; Weber, T.; Wei, D. H.; Weidenkaff, P.; Weidner, F.; Wen, H. W.; Wen, S. P.; White, D. J.; Wiedner, U.; Wilkinson, G.; Wolke, M.; Wollenberg, L.; Wu, J. F.; Wu, L. H.; Wu, L. J.; Wu, Z.; Xia, L.; Xiao, S. Y.; Xiao, Y. J.; Xiao, Z. J.; Xie, Y. G.; Xie, Y. H.; Xing, T. Y.; Xiong, X. A.; Xu, G. F.; Xu, J. J.; Xu, Q. J.; Xu, W.; Xu, X. P.; Yan, L.; Yan, W. B.; Yan, W. C.; Yang, H. J.; Yang, H. X.; Yang, L.; Yang, R. X.; Yang, S. L.; Yang, Y. H.; Yang, Y. X.; Yang, Yifan; Yang, Zhi; Ye, M.; Ye, M. H.; Yin, J. H.; You, Z. Y.; Yu, B. X.; Yu, C. X.; Yu, G.; Yu, J. S.; Yu, T.; Yuan, C. Z.; Yuan, W.; Yuan, X. Q.; Yuan, Y.; Yue, C. X.; Yuncu, A.; Zafar, A. A.; Zeng, Y.; Zhang, B. X.; Zhang, Guangyi; Zhang, H. H.; Zhang, H. Y.; Zhang, J. L.; Zhang, J. Q.; Zhang, J. W.; Zhang, J. Y.; Zhang, J. Z.; Zhang, Jianyu; Zhang, Jiawei; Zhang, L.; Zhang, Lei; Zhang, S.; Zhang, S. F.; Zhang, T. J.; Zhang, X. Y.; Zhang, Y.; Zhang, Y. H.; Zhang, Y. T.; Zhang, Yan; Zhang, Yao; Zhang, Yi; Zhang, Z. H.; Zhang, Z. Y.; Zhao, G.; Zhao, J.; Zhao, J. Y.; Zhao, J. Z.; Zhao, Lei; Zhao, Ling; Zhao, M. G.; Zhao, Q.; Zhao, S. J.; Zhao, Y. B.; Zhao, Z. G.; Zhemchugov, A.; Zheng, B.; Zheng, J. P.; Zheng, Y.; Zheng, Y. H.; Zhong, B.; Zhong, C.; Zhou, L. P.; Zhou, Q.; Zhou, X.; Zhou, X. K.; Zhou, X. R.; Zhu, A. N.; Zhu, J.; Zhu, K.; Zhu, K. J.; Zhu, S. H.; Zhu, W. J.; Zhu, X. L.; Zhu, Y. C.; Zhu, Z. A.; Zou, B. S.; Zou, J. H. (American Physical Society, 2023-05-15)
    We measure the B0 lifetime and flavor-oscillation frequency using B0→D(∗)-π+ decays collected by the Belle II experiment in asymmetric-energy e+e- collisions produced by the SuperKEKB collider operating at the ϒ(4S) resonance. We fit the decay-time distribution of signal decays, where the initial flavor is determined by identifying the flavor of the other B meson in the event. The results, based on 33000 signal decays reconstructed in a data sample corresponding to 190 fb-1, are τB0=(1.499±0.013±0.008) ps, Δmd=(0.516±0.008±0.005) ps-1, where the first uncertainties are statistical and the second are systematic. These results are consistent with the world-average values.
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    Mining Security Risks from Massive Datasets
    Liu, Fang (Virginia Tech, 2017-08-09)
    Cyber security risk has been a problem ever since the appearance of telecommunication and electronic computers. In the recent 30 years, researchers have developed various tools to protect the confidentiality, integrity, and availability of data and programs. However, new challenges are emerging as the amount of data grows rapidly in the big data era. On one hand, attacks are becoming stealthier by concealing their behaviors in massive datasets. One the other hand, it is becoming more and more difficult for existing tools to handle massive datasets with various data types. This thesis presents the attempts to address the challenges and solve different security problems by mining security risks from massive datasets. The attempts are in three aspects: detecting security risks in the enterprise environment, prioritizing security risks of mobile apps and measuring the impact of security risks between websites and mobile apps. First, the thesis presents a framework to detect data leakage in very large content. The framework can be deployed on cloud for enterprise and preserve the privacy of sensitive data. Second, the thesis prioritizes the inter-app communication risks in large-scale Android apps by designing new distributed inter-app communication linking algorithm and performing nearest-neighbor risk analysis. Third, the thesis measures the impact of deep link hijacking risk, which is one type of inter-app communication risks, on 1 million websites and 160 thousand mobile apps. The measurement reveals the failure of Google's attempts to improve the security of deep links.
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    Privacy-Preserving Scanning of Big Content for Sensitive Data Exposure with MapReduce
    Liu, Fang; Shu, Xiaokui; Yao, Danfeng (Daphne); Butt, Ali R. (2015-02-06)
    The exposure of sensitive data in storage and transmission poses a serious threat to organizational and personal security. Data leak detection aims at scanning content (in storage or transmission) for exposed sensitive data. Because of the large content and data volume, such a screening algorithm needs to be scalable for a timely detection. Our solution uses the MapReduce framework for detecting exposed sensitive content, because it has the ability to arbitrarily scale and utilize public resources for the task, such as Amazon EC2. We design new MapReduce algorithms for computing collection intersection for data leak detection. Our prototype implemented with the Hadoop system achieves 225 Mbps analysis throughput with 24 nodes. Our algorithms support a useful privacy-preserving data transformation. This transformation enables the privacy-preserving technique to minimize the exposure of sensitive data during the detection. This transformation supports the secure outsourcing of the data leak detection to untrusted MapReduce and cloud providers.