Browsing by Author "Yang, Jie"

Now showing 1 - 7 of 7
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    Authenticating Users Through Fine-Grained Channel Information
    (IEEE, 2018-02) Liu, Hongbo; Wang, Yan; Liu, Jian; Yang, Jie; Chen, Yingying; Poor, H. Vincent; Engineering Technology, School of Engineering and Technology
    User authentication is the critical first step in detecting identity-based attacks and preventing subsequent malicious attacks. However, the increasingly dynamic mobile environments make it harder to always apply cryptographic-based methods for user authentication due to their infrastructural and key management overhead. Exploiting non-cryptographic based techniques grounded on physical layer properties to perform user authentication appears promising. In this work, the use of channel state information (CSI), which is available from off-the-shelf WiFi devices, to perform fine-grained user authentication is explored. Particularly, a user-authentication framework that can work with both stationary and mobile users is proposed. When the user is stationary, the proposed framework builds a user profile for user authentication that is resilient to the presence of a spoofer. The proposed machine learning based user-authentication techniques can distinguish between two users even when they possess similar signal fingerprints and detect the existence of a spoofer. When the user is mobile, it is proposed to detect the presence of a spoofer by examining the temporal correlation of CSI measurements. Both office building and apartment environments show that the proposed framework can filter out signal outliers and achieve higher authentication accuracy compared with existing approaches using received signal strength (RSS).
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    Determining Driver Phone Use by Exploiting Smartphone Integrated Sensors
    (IEEE, 2016-08) Wang, Yan; Chen, Yingying (Jennifer); Yang, Jie; Gruteser, Marco; Martin, Richard P.; Liu, Hongbo; Liu, Luyang; Karatas, Cagdas; Department of Engineering Technology, School of Engineering and Technology
    This paper utilizes smartphone sensing of vehicle dynamics to determine driver phone use, which can facilitate many traffic safety applications. Our system uses embedded sensors in smartphones, i.e., accelerometers and gyroscopes, to capture differences in centripetal acceleration due to vehicle dynamics. These differences combined with angular speed can determine whether the phone is on the left or right side of the vehicle. Our low infrastructure approach is flexible with different turn sizes and driving speeds. Extensive experiments conducted with two vehicles in two different cities demonstrate that our system is robust to real driving environments. Despite noisy sensor readings from smartphones, our approach can achieve a classification accuracy of over 90 percent with a false positive rate of a few percent. We also find that by combining sensing results in a few turns, we can achieve better accuracy (e.g., 95 percent) with a lower false positive rate. In addition, we seek to exploit the electromagnetic field measurement inside a vehicle to complement vehicle dynamics for driver phone sensing under the scenarios when little vehicle dynamics is present, for example, driving straight on highways or standing at roadsides.
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    Enabling Self-healing Smart Grid Through Jamming Resilient Local Controller Switching
    (IEEE, 2015-09) Liu, Hongbo; Chen, Yingying; Chuah, Mooi Choo; Yang, Jie; Poor, H. Vincent; Department of Computer and Information Science, School of Science
    A key component of a smart grid is its ability to collect useful information from a power grid for enabling control centers to estimate the current states of the power grid. Such information can be delivered to the control centers via wireless or wired networks. It is envisioned that wireless technology will be widely used for local-area communication subsystems in the smart grid (e.g., in distribution networks). However, various attacks with serious impact can be launched in wireless networks such as channel jamming attacks and denial-of-service attacks. In particular, jamming attacks can cause significant damages to power grids, e.g., delayed delivery of time-critical messages can prevent control centers from properly controlling the outputs of generators to match load demands. In this paper, a communication subsystem with enhanced self-healing capability in the presence of jamming is designed via intelligent local controller switching while integrating a retransmission mechanism. The proposed framework allows sufficient readings from smart meters to be continuously collected by various local controllers to estimate the states of a power grid under various attack scenarios. The jamming probability is also analyzed considering the impact of jammer power and shadowing effects. In addition, guidelines on optimal placement of local controllers to ensure effective switching of smart meters under jamming are provided. Via theoretical, experimental and simulation studies, it is demonstrated that our proposed system is effective in maintaining communications between smart meters and local controllers even when multiple jammers are present in the network.
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    Implications of smartphone user privacy leakage from the advertiser’s perspective
    (Elsevier, 2019-02) Wang, Yan; Chen, Yingying; Ye, Fan; Liu, Hongbo; Yang, Jie; Computer Information and Graphics Technology, School of Engineering and Technology
    Many smartphone apps routinely gather various private user data and send them to advertisers. Despite recent study on protection mechanisms and analysis on apps’ behavior, the understanding of the consequences of such privacy losses remains limited. In this paper, we investigate how much an advertiser can infer about users’ social and community relationships. After one month’s user study involving about 190 most popular Android apps, we find that an advertiser can infer 90% of the social relationships. We further propose a privacy leakage inference framework and use real mobility traces and Foursquare data to quantify the consequences of privacy leakage. We find that achieving 90% inference accuracy of the social and community relationships requires merely 3 weeks’ user data. Finally, we present a real-time privacy leakage visualization tool that captures and displays the spatial–temporal characteristics of the leakages. The discoveries underscore the importance of early adoption of privacy protection mechanisms.
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    Targeting Protein Arginine Methyltransferase 5 Suppresses Radiation-induced Neuroendocrine Differentiation and Sensitizes Prostate Cancer Cells to Radiation
    (American Association for Cancer Research, 2022) Owens, Jake L.; Beketova, Elena; Liu, Sheng; Shen, Qi; Pawar, Jogendra Singh; Asberry, Andrew M.; Yang, Jie; Deng, Xuehong; Elzey, Bennett D.; Ratliff, Timothy L.; Cheng, Liang; Choo, Richard; Citrin, Deborah E.; Polascik, Thomas J.; Wang, Bangchen; Huang, Jiaoti; Li, Chenglong; Wan, Jun; Hu, Chang-Deng; Medical and Molecular Genetics, School of Medicine
    Prostate cancer remains the second leading cause of cancer death among American men. Radiotherapy is a potentially curative treatment for localized prostate cancer, and failure to control localized disease contributes to the majority of prostate cancer deaths. Neuroendocrine differentiation (NED) in prostate cancer, a process by which prostate adenocarcinoma cells transdifferentiate into neuroendocrine-like (NE-like) cells, is an emerging mechanism of resistance to cancer therapies and contributes to disease progression. NED also occurs in response to treatment to promote the development of treatment-induced neuroendocrine prostate cancer (NEPC), a highly aggressive and terminal stage disease. We previously demonstrated that by mimicking clinical radiotherapy protocol, fractionated ionizing radiation (FIR) induces prostate cancer cells to undergo NED in vitro and in vivo. Here, we performed transcriptomic analysis and confirmed that FIR-induced NE-like cells share some features of clinical NEPC, suggesting that FIR-induced NED represents a clinically relevant model. Furthermore, we demonstrated that protein arginine methyltransferase 5 (PRMT5), a master epigenetic regulator of the DNA damage response and a putative oncogene in prostate cancer, along with its cofactors pICln and MEP50, mediate FIR-induced NED. Knockdown of PRMT5, pICln, or MEP50 during FIR-induced NED and sensitized prostate cancer cells to radiation. Significantly, PRMT5 knockdown in prostate cancer xenograft tumors in mice during FIR prevented NED, enhanced tumor killing, significantly reduced and delayed tumor recurrence, and prolonged overall survival. Collectively, our results demonstrate that PRMT5 promotes FIR-induced NED and suggests that targeting PRMT5 may be a novel and effective radiosensitization approach for prostate cancer radiotherapy.
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    Towards Understanding the Advertiser’s Perspective of Smartphone User Privacy
    (IEEE, 2015-06) Wang, Yan; Chen, Yingying; Ye, Fan; Yang, Jie; Liu, Hongbo; Department of Computer & Information Science, School of Science
    Many smartphone apps routinely gather various private user data and send them to advertisers. Despite recent study on protection mechanisms and analysis on apps' behavior, the understanding about the consequences of such privacy losses remains limited. In this paper we investigate how much an advertiser can infer about users' social and community relationships by combining data from multiple applications and across many users. After one month's user study involving about 200 most popular Android apps, we find that an advertiser can infer 90% of the social relationships. We further propose a privacy leakage inference framework and use real mobility traces and Foursquare data to quantify the consequences of privacy leakage. We find that achieving 90% inference accuracy of the social and community relationships requires merely 3 weeks' user data. The discoveries underscore the importance of early adoption of privacy protection mechanisms.