职务职称：

讲师、硕士生导师

所属系部：

智能科学与技术系

研究方向：

异常数据检测、异常流量检测、软件安全性测试

联系电话：

18860876992，QQ：562449725

电子邮箱：

caisaih@ujs.edu.cn

个人简介

蔡赛华，男，江苏南通人，博士（后）。2020年6月获工学博士学位，2020年8月进入hg皇冠官方官网工作。社会兼职包括：IEEE、CCF会员、江苏省软件专委会委员、江苏省网络空间安全专委会委员，担任TSUSC、PR、Information Sciences、IET Software、KAIS、KBS、ESWA、EAAI、APIN、NCA、IJIS、COMPAG等期刊的审稿人。

主要从事异常流量检测、离群点检测和软件安全性测试等研究，近年来以一作或通讯作者在：Information Sciences、The Computer Journal、Information and Software Technology、Journal of Software: Evolution and Process、IET Software、Knowledge-Based Systems、Expert Systems with Applications、ASE、ISSRE、QRS、TrustCom、ISC等国内外期刊和国际会议上发表高质量论文30余篇。作为指导教师带领员工获得“中国研究生网络安全创新大赛”国赛二等奖和三等奖。

教研成果

一、 主持和参与的部分科研项目：

[1] 国家自然科学基金，62202206，概念漂移现象下基于关联分析的异常网络流量识别方法研究，主持，2023/01-2025/12。

[2] 江苏省自然科学基金，BK20220515，基于概念漂移检测和适应的异常网络流量识别方法研究，主持，2022/07-2025/06。

[3] 中国博士后基金面上项目，2021M691310，基于特征关联分析的网络流量异常检测和识别方法研究，主持，2021/07-2023/06。

[4] 国家自然科学基金，62172194，面向软件漏洞挖掘的智能化Fuzzing测试方法研究，参与，2022/01-2025/12。

[5] 国家自然科学基金，U1836116，网络流量中基于数据控制流的漏洞利用程序检测方法研究，参与，已结题。（排名第二）

[6] 某部委*****基金，61***16，基于缺陷********方法研究，参与，已结题。（排名第二）

[7] 某部委*****项目，61***02，面向复杂********技术研究，参与，已结题。（排名第三）

二、近年来获得的部分学术成果：

（1）发表的部分学术论文（*代表通讯作者）

[1] Saihua Cai, Jinfu Chen*, Haibo Chen, et al. Minimal rare pattern-based outlier detection approach for uncertain data streams under monotonic constraints. The Computer Journal, 66(1):16-34, 2023.（SCI，CCF-B，中科院四区）

[2] Saihua Cai*, Li Li, Jinfu Chen, et al. MWFP-Outlier: maximal weighted frequent-pattern-based approach for detecting outliers from uncertain weighted data streams. Information Sciences, 591:195-225, 2022.（SCI，CCF-B，中科院一区）

[3] Saihua Cai, Jinfu Chen*, Haibo Chen, et al. An efficient anomaly detection method for uncertain data based on minimal rare patterns with the consideration of anti-monotonic constraints. Information Sciences, 580:620-642, 2021.（SCI，CCF-B，中科院一区）

[4] Saihua Cai, Rubing Huang, Jinfu Chen*, et al. An efficient outlier detection method for data streams based on closed frequent patterns by considering anti-monotonic constraints. Information Sciences, 555:125-146, 2021.（SCI，CCF-B，中科院一区）

[5] Saihua Cai, Sicong Li, Gang Yuan, et al. MiFI-Outlier: Minimal infrequent itemset-based outlier detection approach on uncertain data stream. Knowledge-Based Systems, 191:105268, 2020.（SCI，CCF-C，中科院一区）

[6] Saihua Cai, Li Li, Sicong Li, et al. An efficient approach for outlier detection from uncertain data streams based on maximal frequent patterns. Expert Systems with Applications, 160:113646, 2020.（SCI，CCF-C，中科院一区）

[7] Saihua Cai, Ruizhi Sun*, Shangbo Hao, et al. Minimal weighted infrequent itemset mining-based outlier detection approach on uncertain data stream. Neural Computing & Applications, 32:6619–6639, 2020.（SCI，CCF-C，中科院二区）

[8] Saihua Cai, Li Li, Qian Li, et al. UWFP-Outlier: an efficient frequent-pattern-based outlier detection method for uncertain weighted data streams. Applied Intelligence, 50:3452-3470, 2020.（SCI，CCF-C，中科院二区）

[9] Saihua Cai, Ruizhi Sun*, Shangbo Hao, et al. An Efficient Outlier Detection Approach on Weighted Data Stream Based on Minimal Rare Pattern Mining. China Communications, 16(10):83-99, 2019.（SCI，卓越期刊）

[10] Saihua Cai, Jinfu Chen*, Xinru Li, et al. Minimal rare-pattern-based outlier detection method for data streams by considering anti-monotonic constraints. In: 23^rd International Conference on Information Security (ISC 2020), pp. 274-289, 2020.（EI，CCF-C）

[11] Jinfu Chen, Tianxiang Lv, Saihua Cai*, et al. A novel detection model for abnormal network traffic based on bidirectional temporal convolutional network. Information and Software Technology, 157:107166, 2023.（SCI，CCF-B，中科院二区）

[12] Jinfu Chen, Jingyi Chen, Saihua Cai*, et al. A Novel Combinatorial Testing Approach with Fuzzing Strategy. Journal of Software: Evolution and Process, e2537:1-17, 2023.（SCI，CCF-B，中科院四区）

[13] Jinfu Chen, Yuechao Gu, Saihua Cai*, et al. A Novel Test Case Prioritization Approach for Black-box testing based on K-medoids Clustering. Journal of Software: Evolution and Process, e2565:1-17, 2023.（SCI，CCF-B，中科院四区）

[14] Jinfu Chen, Chi Zhang, Saihua Cai*, et al. A Memory-related Vulnerability Detection Approach based on Vulnerability Model with Petri Net. Journal of Logical and Algebraic Methods in Programming, 100859, 2023.（SCI，CCF-C，中科院四区）

[15] Jinfu Chen, Chi Zhang, Saihua Cai*, et al. Malware recognition approach based on self‐similarity and an improved clustering algorithm. IET Software, 16(5):527-541, 2022.（SCI，CCF-B，中科院四区）

[16] Jinfu Chen, Xiaoli Wang, Saihua Cai*, et al. A software defect prediction method with metric compensation based on feature selection and transfer learning. Frontiers of Information Technology & Electronic Engineering, 2100468, 2022.（SCI，CCF-C，卓越期刊）

[17] Jinfu Chen, Saihua Cai*, Dave Towey, et al. Detecting Implicit Security Exceptions Using an Improved Variable-Length Sequential Pattern Mining Method. International Journal of Software Engineering and Knowledge Engineering, 27(8):1235-1268, 2017.（SCI，CCF-C，中科院四区）

[18] Jinfu Chen*, Shengran Wang, Saihua Cai*, et al. A Novel Coverage-gudied Greybox Fuzzing based on Power Schedule Optimization with Time Complexity. In: 37^th IEEE/ACM International Conference on Automated Software Engineering (ASE 2022), pp.1-5, 2022.（EI，CCF-A）

[19] Jinfu Chen, Jingyi Chen, Saihua Cai*, et al. A Test Case Generation Method of Combinatorial Testing based on t-way Testing with Adaptive Random Testing. In: 32^nd IEEE International Symposium on Software Reliability Engineering (ISSRE 2021), pp.83-90, 2021.（EI，CCF-B）

[20] Jinfu Chen, Jiaping Xu, Saihua Cai*, et al. An efficient dual ensemble software defect prediction method with neural network. In: 32^nd International Symposium on Software Reliability Engineering (ISSRE 2021), pp.91-98, 2021.（EI，CCF-B）

[21] Jinfu Chen, Yuechao Gu, Saihua Cai*, et al. KS-TCP: An Efficient Test Case Prioritization Approach based on K-medoids and Similarity. In: 32^nd International Symposium on Software Reliability Engineering (ISSRE 2021), pp.105-110.（EI，CCF-B）

[22] Jinfu Chen, Yemin Yin, Saihua Cai*, et al. An Improved Test Case Generation Method based on Test Requirements for Testing Software Component. In: 22^nd IEEE International Conference on Software Quality, Reliability, and Security (QRS 2022), pp.209-218, 2022.（EI，CCF-C）

[23] Jinfu Chen, Haodi Xie, Saihua Cai*, et al. A formalization-based vulnerability detection method for cross-subject network components. In: 21^st IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom 2022), pp.1054-1059, 2022.（EI，CCF-C）

[24] Jinfu Chen, Shang Yin, Saihua Cai*, et al. An Efficient Network Intrusion Detection Model Based on Temporal Convolutional Networks. In: 21^st International Conference on Software Quality, Reliability, and Security (QRS 2021), pp.768-775, 2021.（EI，CCF-C）

[25] Ye Geng, Saihua Cai*, Songling Qin, et al. An Efficient Network Traffic Classification Method based on Combined Feature Dimensionality Reduction. In: 21^st IEEE International Conference on Software Quality, Reliability, and Security (QRS 2021), pp.407-414, 2021.（EI，CCF-C）

[26] Dengzhou Shi, Saihua Cai*, Songling Qin, et al. An Identification Algorithm of Attacking Programs based on Quadratic Feature Selection and Fast Decision Tree. In: 21^st IEEE International Conference on Software Quality, Reliability, and Security (QRS 2021), pp.133-140, 2021.（EI，CCF-C）

[27] Jinfu Chen, Bo Liu, Saihua Cai*, et al. AIdetectorX: A Vulnerability Detector Based on TCN and Self-attention Mechanism. In: Symposium on Dependable Software Engineering-Theories, Tools and Applications (SETTA 2021), pp.161-177, 2021.（EI，CCF-C）

[28] Jinfu Chen, Saihua Cai, Lili Zhu, et al. An Improved String-Searching Algorithm and Its Application in Component Security Testing. Tsinghua Science and Technology, 21(3):281-294, 2016.（SCI，卓越期刊）

（2）授权或申请的部分专利

[1] 发明专利：一种基于核主成分分析的二次特征提取及恶意攻击识别方法。发明人：蔡赛华，陈锦富，赵玲玲，等。授权号：ZL 202110659646.0，2021年。（已授权）

[2] 发明专利：一种面向监测日志的构件异常信息查找方法。发明人：陈锦富，蔡赛华，黄如兵，等。授权号：ZL 201610116310.9，2016年。（已授权）

[3] 发明专利：一种基于双向时间卷积神经网络与多头自注意力机制的异常网络流量检测方法。发明人：蔡赛华，刘明杰，徐涵，等。申请号：202211409998.1，2022年。

[4] 发明专利：一种基于双向时间卷积神经网络的异常网络流量检测方法。发明人：蔡赛华，陈锦富，吕天翔，等。申请号：202210650965.X，2022年。

[5] 发明专利：一种基于最大频繁模式非相似性的异常网络流量检测方法。发明人：蔡赛华，陈锦富，徐波，等。申请号：202210226905.5，2022年。

[6] 发明专利：一种基于改进的时间卷积网络的漏洞检测方法。发明人：蔡赛华，陈锦富，林薇，等。申请号：202111257188.4，2021年。

[7] 发明专利：一种基于漏洞攻击数据库及决策树的攻击程序识别方法。发明人：蔡赛华，陈锦富，秦松铃，等。申请号：202110659629.7，2021年。

[8] 发明专利：一种用于确定最佳的神经网络输入向量长度的方法。发明人：蔡赛华，刘博，陈锦富，等。申请号：202110659650.7，2021年。

（3）获批及申请的部分软件著作权

[1] 基于模式距离的异常流量检测平台[简称：Pdbandp]V1.0。完成人：蔡赛华，魏忠旺，林敏，等。登记号：2022SR0626385。

[2] 基于概念漂移检测的异常网络流量识别平台[简称：ANTICD]V1.0。完成人：蔡赛华，唐晗，赵文军，等。登记号：2023SR0414803。

[3] 基于双向时序卷积网络和多头自注意力机制的异常网络流量检测平台[简称：ANTbTCNAte]V1.0。完成人：蔡赛华，陈智霖，刘明杰，等。登记号：2023SR0414802。

更多信息欢迎访问个人主页：https://caisaih1990.github.io/