主讲课程:
数字信号处理
信号与系统
多媒体通信
网络安全攻防技术基础
在研项目:
1.福建省自然科学基金，基于生成对抗网络的小型无人机检测与识别技术研究， 2019/04-2022/12，主持
2.国家自然科学基金重大研究计划项目，面向沉浸式体验的空天地一体化车联网关键技术，2017.01-2020.12 ，子课题负责人
3.国家高技术研究发展计划(863计划)项目，基于物理层增强安全的未来无线通信传输技术研究，2015/01-2016/12 ，子课题负责人
4.国家自然科学基金应急管理项目，无线发射机信号指纹的形成机理及特征识别研究，2015/01-2015/12 ，主持
5.横向课题，宽带无线移动应用技术研究基金， 2014/04-2015/6，主持
6.福建省自然科学基金，宽带无线通信信号指纹的识别研究， 2014/01-2016/12 ，主持
7.横向课题，无线通信信号的个体识别分析系统，主持
代表性论文:
[1] zhao c, huang l, zhao y, et al. secure machine-type communications toward lte heterogeneous networks[j]. ieee wireless communications, 2017, 24(1): 82-87.（jcr1）
[2] c. zhao, m. huang, l. huang, x. du, m. guizani, “a robust authentication scheme based on physical-layer phase noise fingerprint for emerging wireless networks”, computer networks, may 2017,（jcr 3）
[3] zhao, c.; chen, c.; he, z.; wu, z. application of auxiliary classifier wasserstein generative adversarial networks in wireless signal classification of illegal unmanned aerial vehicles. appl. sci. 2018, 8, 2664. （jcr 3）
[4] caidan zhao, mingxian shi, zhibiao cai, and caiyun chen. “research on the open-categorical classification of the internet-of-things based on generative adversarial networks” applied sciences, 2018, 8(12): 2351. （jcr 3）
[5] caidan zhao, caiyun chen, zhibiao cai, mingxian sh, xiaojiang du, and mohsen guizani, “classification of small uavs based on auxiliary classifier wasserstein gans”, ieee globecom’18, abu dhabi, dec.9-13，2018
[6] c. zhao, z. cai, m. huang, m. shi, x. du and m. guizani, the identification of secular variation in iot based on transfer learning, 2018 international conference on computing, networking and communications (icnc), maui, hi, usa, 2018, pp. 878-882.
[7] shi z, huang m, zhao c*, et al. detection of lssuav using hash fingerprint based svdd[c]//communications (icc 2017), 2017 ieee international conference on. ieee, 2017: 1-5.
[8] c. zhao, m. shi, z. cai and c. chen, "detection of unmanned aerial vehicle signal based on gaussian mixture model," 2017 12th international conference on computer science and education (iccse), houston, tx, 2017, pp. 289-293.
[9] c. zhao, z. cai , m huang, and et al. “the identification of secular variation in wireless equipment based on transfer learning," 2018,
[10] zhao c, tai m, huang l, et al. power optimization for secure communications in full-duplex system under residual self-interference，globecom 2016，washington dc
[11] z. shi, x. lin, c. zhao*, m. shi, multifractal slope feature based wireless devices identification, international conference on computer science & education (iccse), cambridge, 2015, 590-595
[12] zhao c d, wu x p, huang l f, et al. compressed sensing based fingerprint identification for wireless transmitters. scientific world journal, 2014:1-9.（sci）
[13] zhao c. d., chi t. y., huang l. f., yao y., kuo s. y. wireless local area network cards identification based on transient fingerprinting. wireless communications and mobile computing, 2013,13(7):711-718.（sci ）
专利：
[1] 无线发射机信号多重分形双对数曲线梯度特征识别方法.（专利号：zl2013 1 0172183.0）
[2] 无线发射机信号载波相位噪声和时钟相位噪声指纹特征联合识别方法.（专利号：zl201310172306.0）