wellbet吉祥手机官网

师资队伍
王宁
时间:2020-01-08    浏览量:次

1基本信息

姓 名:王宁

性 别:

职 称: “泓深青年学者”教授(博导,硕导)

职 务:

电 话:

办公地点: 主教1817

E-mailnwang5@wnmb900.com

研究方向: 物理层安全,隐私保护,人工智能,机器学习,无人机安全等研究领域。

招生信息:每年招收有志从事计算机、通信与信息安全等前沿研究的博士和硕士研究生,专业包括数学、通信、计算机、信息安全等专业。本团队与美国乔治梅森大学、美国弗吉尼亚wellbet吉祥手机官网大学、新加坡国立大学等海外一流大学有紧密合作,优秀学生可以推荐至这些一流大学继续深造。此外,团队同时与wellbet吉祥手机官网院、华为、中兴、大唐电信等单位有交流合作,支持工程偏向学生技术实践以及毕业后工作推荐。


2个人简介:

王宁,重庆大学“泓深青年学者”教授、博士生导师,IEEE Member。北京邮电大学博士,美国乔治梅森大学博士后研究员。研究方向包括(但不局限于)物理层安全,信息物理系统安全及隐私保护,射频指纹,以及机器学习和无人机安全等。相关研究成果先后发表于IEEE Networks Magazine, IEEE Transactions on Information Forensics and Security, IEEE Transactions on Wireless Communication, IEEE International Conference on Computer Communications, IEEE Internet of Things Journal等国际主流期刊及会议。受邀为多个国际期刊会议审稿人,包括:IEEE TIFS, IEEE TWC, IEEE TMC, IEEE TCOM, IEEE TVT, IEEE TCCN, IEEE Wireless Communication magazine, IEEE IoT Journal, IEEE INFOCOM, IEEE CNS, IEEE GLOBECOM等。


3学术成果

Book: 

Ning Wang, Long Jiao, Jie Tang, and Kai Zeng. Chapter: "Physical Layer Security for mmWave Massive MIMO Communications in 5G Networks", Book: "Frontiers in Hardware Security and Trust" [B], IET, 2020.


代表性论文:

1、Ning Wang, Long Jiao, Pu Wang, and Kai Zeng. "Exploiting Beam Features for Spoofing Attack Detection in MmWave 60GHz IEEE 802.11ad Networks." [J], IEEE Transactions on Wireless Communication (TWC), In press, 2020.

2、Ning Wang, Weiwei Li, Pu Wang, Amir Alipour-Fanid, Long Jiao and Kai Zeng. "Physical Layer Authentication for 5G Communications: Opportunities and Road Ahead." [J], IEEE Networks Magazine, 2020. (wellbet吉祥手机官网院一区)

3、Ning Wang, Weiwei Li, Amir Alipour-Fanid, Long Jiao, and Kai Zeng. "Pilot Contamination Attack Detection for 5G MmWave Grant-Free IoT Networks." [J], IEEE Transactions on Information Forensics and Security (TIFS),2020. (CCF:A)

4、Ning Wang, Long Jiao, Pu Wang, Weiwei Li, and Kai Zeng. "Machine Learning-based Spoofing Attack Detection in MmWave 60GHz IEEE 802.11ad Networks." [C] In IEEE INFOCOM 2020 International Conference on Computer Communications. (CCF:A)

5、Ning Wang, Weiwei Li, Amir Alipour-Fanid, Monireh Dabaghchian, and Kai Zeng. "Compressed Sensing-Based Pilot Contamination Attack Detection for NOMA-IoT Communications." [J], IEEE Internet of Things Journal, 2020. (wellbet吉祥手机官网院一区)

6、Ning Wang, Long Jiao, and Kai Zeng. "Pilot Contamination Attack Detection for NOMA in 5G Mm-Wave Massive MIMO Networks." [J], IEEE Transactions on Information Forensics and Security (TIFS), 2019. (CCF:A)

7、Ning Wang, Long Jiao, Pu Wang, and Kai Zeng. "Physical Layer Security of 5G Wireless Networks for IoT: Challenges and Opportunities." [J], IEEE Internet of Things Journal, 2019. (wellbet吉祥手机官网院一区)

8、Long Jiao,Ning Wang, Pu Wang, Amir Alipour-Fanid, Jie Tang, Kai Zeng. "Physical Layer Key Generation in 5G Wireless Networks." [J], IEEE Communications Magazine,2019. (wellbet吉祥手机官网院一区)

9、Pu Wang,Ning Wang, Monireh Dabaghchian, Kai Zeng, and Zheng Yan. "Optimal Resource Allocation for Secure Multi-User Wireless Powered Backscatter Communication with Artificial Noise." In IEEE INFOCOM 2019-IEEE Conference on International Conference on Computer Communications, 2019. (CCF:A)

10、Amir Alipour-Fanid, Monireh Dabaghchian,Ning Wang, and Kai Zeng. "Machine Learning-Based Delay-Aware UAV Detection and Operation Mode Identification over Encrypted Wi-Fi Traffic." [J], IEEE Transactions on Information Forensics and Security (TIFS), 2019. (CCF:A)

11、Ning Wang, Shichao Lv, T Jiang, and Liang Xiao. "Physical Layer Authentication Based on Extreme Learning Machine."[J], IEEE Communications Letters, 2017.

12、Ning Wang, and Weiwei Li. "Layer Spoofing Detection Based on Sparse Signal Processing and Fuzzy Recognition." [J], IET Signal Processing, 2017.

13、Ning Wang, Weiwei Li, and Ting Jiang. "A cross-layer approach to message authentication based on sparse representation for wireless body area networks." [J], International Journal of Distributed Sensor Networks, 2017, 13(3): 1550147717692587.

14、Ning Wang, Ting Jiang, Weiwei Li, et al. "Physical Layer Security in IoT based on Compressed Sensing and Frequency selection." [J], IET Communications, 2016.

15Shan Qin, Ting Jiang, Sheng Wu, Ning Wang, and Xinran Zhao. "Graph Convolution Based Deep Clustering for Speech Separation." [J], IEEE Access (2020).

16、Ning Wang, Junqing Le, Weiwei Li, Long Jiao, Zhihao Li and Kai Zeng. "Privacy Protection and Efficient Incumbent Detection in Federated Learning Based Spectrum Sharing." 2020 IEEE Conference on Communications and Network Security (CNS). IEEE, 2020.

17、Long Jiao, Pu Wang, Ning Wang, Junqing Le, Zhihao Li, and Kai Zeng. "Efficient Physical Layer Group Key Generation in 5G Wireless Networks." 2020 IEEE Conference on Communications and Network Security (CNS). IEEE, 2020.

18、Amir Alipour-Fanid, Monireh Dabaghchian, Ning Wang, Pu Wang, Liang Zhao, and Kai Zeng. "Machine learning-based delay-aware UAV detection over encrypted WiFi traffic".IEEE CNS 2019.

19、Ning Wang, Jie Tang, and Kai Zeng. "Spoofing Attack Detection in Mm-Wave and Massive MIMO 5G Communication." in Proc. Of the IEEE CNS Workshop Conference.
IEEE, 2019.

20、Ning Wang, Long Jiao, and Kai Zeng. "Pilot Contamination Attack Detection for NOMA in Mm-Wave and Massive MIMO 5G Communication." 2018 IEEE Conference on Communications and Network Security (CNS). IEEE, 2018

21、Ning Wang, Long Jiao; Pu Wang; Kai Zeng. "Efficient Identity Spoofing Attack Detection for IoT in mm-Wave and Massive MIMO 5G Communication." 2018 IEEE Global Communications Conference (GLOBECOM). IEEE, 2018.

22、Long Jiao, Ning Wang, and Kai Zeng. "Secret Beam: Robust Secret Key Agreement for mmWave Massive MIMO 5G Communication." 2018 IEEE Global Communications Conference (GLOBECOM). IEEE, 2018.

23、Jie Tang, Long Jiao, Ning Wang, Pu Wang, Kai Zeng, and Hong Wen. "Mobility Improves NOMA Physical Layer Security." In 2018 IEEE Global Communications Conference (GLOBECOM), pp. 1-6. IEEE, 2018.

24、Xiaoying Qiu, Ting Jiang, and Ning Wang. "Safeguarding multiuser communication using full-duplex jamming and Q-learning algorithm." IET Communications 12.15
(2018): 1805-1811.

25、Ning Wang, Ting Jiang, and Zheng Zhou. "Channel sparse representation based authentication for reconciliation of key generation." 2016 16th International Symposium on Communications and Information Technologies (ISCIT). IEEE, 2016.

26、Weiwei Li, and Ning Wang. "Transforming the SMV model into MMV model based on the characteristics of wavelet coefficients." IET Signal Processing 11.3 (2016): 275-284.

27、Shichao Lv, Xiang Lu, Zhuo Lu, Xiaoshan Wang, Ning Wang, and Limin Sun. "Zero reconciliation secret key extraction in MIMO backscatter wireless systems." In 2016 IEEE International Conference on Communications (ICC), pp. 1-6. IEEE, 2016.

28、Ning Wang, Shichao Lv, Ting Jiang, et al. "A novel physical layer spoofing detection based on sparse signal processing." 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2015.

29、Weiwei Li, Ning Wang and Ting Jiang. "Image compressed sensing based on similarity of image blocks." IEEE WCNC 2015, USA, New Orleans, 2015, March 09-12.

30、Weiwei Li, Ting Jiang, and Ning Wang. "Compressed sensing based on the characteristic correlation of ECG in hybrid wireless sensor network." International Journal of Distributed Sensor Networks 11.10 (2015): 325103.

31、Weiwei Li, Ning Wang and Ting Jiang. "Compressed sensing-based unequal error protection by linear codes" [J] IET signal processing, 2014, 8 (7): 800-808.

32、Weiwei Li, Ting Jiang, and Ning Wang. "Clustering compressed sensing based on image block similarities." [J], The Journal of China Universities of Posts and Telecommunications, 2014, 21(4), 68-76.

33、Weiwei Li, Ning Wang and Ting Jiang. "Unequal-compressed sensing based on the characteristics of wavelet coefficients" International Conference on Communications signal processing and systems. Hohhot, China, 2014, July 14-15.


3学术服务

电机电子工程师学wellbet吉祥手机官网信协会(IEEE)以及IEEE通信协会成员。

担任多个国际会议如IEEE INFOCOM, IEEE CNS, IEEE GLOBECOM,等评议委员会委员;担任多个国际顶级期刊如IEEE TIFS, IEEE TWC, IEEE TMC, IEEE TCOM, IEEE TVT, IEEE TCCN, IEEE Wireless Communication magazine, IEEE IoT Journal等评审。