一、 主持和參與的部分科研項目: [1] 國家自然科學基金青年項目,62202206,概念漂移現象下基于關聯分析的異常網絡流量識别方法研究,主持,2023/01-2025/12。 [2] 江蘇省自然科學基金青年項目,BK20220515,基于概念漂移檢測和适應的異常網絡流量識别方法研究,主持,2022/07-2025/06。 [3] 中國博士後科學基金特别資助(站中)項目,2023T160275,基于數據增強的惡意網絡流量檢測及攻擊溯源方法研究,主持,2023/07-2024/12。 [4] 中國博士後科學基金面上項目,2021M691310,基于特征關聯分析的網絡流量異常檢測和識别方法研究,主持,已結題。 [5] 國家自然科學基金面上項目,62172194,面向軟件漏洞挖掘的智能化Fuzzing測試方法研究,2022/01-2025/12。(排名第三) [6] 國家自然科學基金,U1836116,網絡流量中基于數據控制流的漏洞利用程序檢測方法研究,已結題。(排名第二) [7] 某部委預研領域基金,61***16,基于缺陷********方法研究,已結題。(排名第二) [8] “十三五”部委預研基金,61***502,物聯網軟件鍊漏洞********技術研究,已結題。(排名第三)
二、近年來獲得的部分學術成果: (1)部分學術論文(*代表通訊作者) [1] Saihua Cai*, Han Xu, Mingjie Liu, et al. A Malicious Network Traffic Detection Model Based on Bidirectional Temporal Convolutional Network with Multi-Head Self-Attention Mechanism. Computers & Security, 136:103580, 2024.(SCI,CCF-B) [2] 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) [3] 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) [4] 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) [5] 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) [6] 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) [7] 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) [8] 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) [9] 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) [10] 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) [11] Saihu Cai, Wenjun Zhao, Han Tang, et al. CGSA-RNN: Abnormal Network Traffic Detection Model Based on CycleGAN and Self-Attention Mechanism. In: 23rd IEEE International Conference on Software Quality, Reliability, and Security (QRS 2023), pp. 541-549, 2023.(EI,,CCF-C) [12] Saihua Cai, Jinfu Chen*, Xinru Li, et al. Minimal rare-pattern-based outlier detection method for data streams by considering anti-monotonic constraints. In: 23rd International Conference on Information Security (ISC 2020), pp. 274-289, 2020.(EI,CCF-C) [13] Jinfu Chen, Jiaping Xu, Saihua Cai*, et al. Software Defect Prediction Approach based on A Diversity Ensemble Combined with Neural Network. IEEE Transactions on Reliability, accept, 2024.(SCI,CCF-C) [14] Jinfu Chen, Luo Song, Saihua Cai*, et al. TLS-MHSA: An efficient detection model for Encrypted Malicious Traffic based on Multi-head Self-Attention Mechanism. ACM Transactions on Privacy and Security, 26(4):44:1-21, 2023.(SCI,CCF-B) [15] 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) [16] Jinfu Chen, Yuhao Chen, Saihua Cai*, et al. An optimized feature extraction algorithm for abnormal network traffic detection. Future Generation Computer Systems, 149:330-342, 2023.(SCI,CCF-C) [17] Jinfu Chen, Wei Lin, Saihua Cai*, et al. BiTCN_DRSN: An Effective Software Vulnerability Detection Model based on an Improved Temporal Convolutional Network. Journal of Systems & Software, 204:111772, 2023.(SCI,CCF-B) [18] 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) [19] 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, 2024.(SCI,CCF-B) [20] 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) [21] 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) [22] 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) [23] 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) [24] Jinfu Chen, Shengran Wang, Saihua Cai*, et al. A Novel Coverage-gudied Greybox Fuzzing based on Power Schedule Optimization with Time Complexity. In: 37th IEEE/ACM International Conference on Automated Software Engineering (ASE 2022), pp.1-5, 2022.(EI,CCF-A) [25] 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: 32nd IEEE International Symposium on Software Reliability Engineering (ISSRE 2021), pp.83-90, 2021.(EI,CCF-B) [26] Jinfu Chen, Jiaping Xu, Saihua Cai*, et al. An efficient dual ensemble software defect prediction method with neural network. In: 32nd International Symposium on Software Reliability Engineering (ISSRE 2021), pp.91-98, 2021.(EI,CCF-B) [27] Jinfu Chen, Yuechao Gu, Saihua Cai*, et al. KS-TCP: An Efficient Test Case Prioritization Approach based on K-medoids and Similarity. In: 32nd International Symposium on Software Reliability Engineering (ISSRE 2021), pp.105-110.(EI,CCF-B) [28] Jinfu Chen, Qiaowei Feng, Saihua Cai*, et al. VDABSys: A novel security-testing framework for blockchain systems based on vulnerability detection. In: 19th EAI International Conference on Security and Privacy in Communication Networks (SecureComm 2023), pp. 15-32, 2023.(EI,CCF-C) [29] Jinfu Chen, Yemin Yin, Saihua Cai*, et al. An Improved Test Case Generation Method based on Test Requirements for Testing Software Component. In: 22nd IEEE International Conference on Software Quality, Reliability, and Security (QRS 2022), pp.209-218, 2022.(EI,CCF-C) [30] Jinfu Chen, Haodi Xie, Saihua Cai*, et al. A formalization-based vulnerability detection method for cross-subject network components. In: 21st IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom 2022), pp.1054-1059, 2022.(EI,CCF-C) [31] Jinfu Chen, Shang Yin, Saihua Cai*, et al. An Efficient Network Intrusion Detection Model Based on Temporal Convolutional Networks. In: 21st International Conference on Software Quality, Reliability, and Security (QRS 2021), pp.768-775, 2021.(EI,CCF-C) [32] Ye Geng, Saihua Cai*, Songling Qin, et al. An Efficient Network Traffic Classification Method based on Combined Feature Dimensionality Reduction. In: 21st IEEE International Conference on Software Quality, Reliability, and Security (QRS 2021), pp.407-414, 2021.(EI,CCF-C) [33] Dengzhou Shi, Saihua Cai*, Songling Qin, et al. An Identification Algorithm of Attacking Programs based on Quadratic Feature Selection and Fast Decision Tree. In: 21st IEEE International Conference on Software Quality, Reliability, and Security (QRS 2021), pp.133-140, 2021.(EI,CCF-C) [34] 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) [35] 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,學生一作,卓越期刊) [36] 陳錦富, 馮喬偉, 蔡賽華*, 等. 基于形式化方法的區塊鍊系統漏洞檢測模型. 軟件學報, 35(9):2204-2230, 2024.(EI,卓越期刊) [37] 陳錦富, 王震鑫, 蔡賽華*, 等. 基于蛻變測試的區塊鍊智能合約漏洞檢測方法. 通信學報, 44(10):164-176, 2023.(EI,卓越期刊)
(2)授權或申請的部分發明專利 [1] 發明專利:一種基于核主成分分析的二次特征提取及惡意攻擊識别方法。發明人:蔡賽華,陳錦富,趙玲玲,等。授權号:ZL 202110659646.0,2021年。(已授權) [2] 發明專利:一種基于雙向時間卷積神經網絡的異常網絡流量檢測方法。發明人:蔡賽華,陳錦富,呂天翔,等。專利号:ZL 202210650965.X,2022年。(已授權) [3] 發明專利:一種面向監測日志的構件異常信息查找方法。發明人:陳錦富,蔡賽華,黃如兵,等。授權号:ZL 201610116310.9,2016年。(已授權) [4] 發明專利:一種基于漏洞攻擊數據庫及決策樹的攻擊程序識别方法。發明人:蔡賽華,陳錦富,秦松鈴,等。申請号:202110659629.7,2021年。 [5] 發明專利:一種用于确定最佳的神經網絡輸入向量長度的方法。發明人:蔡賽華,劉博,陳錦富,等。申請号:202110659650.7,2021年。 [6] 發明專利:一種基于改進的時間卷積網絡的漏洞檢測方法。發明人:蔡賽華,陳錦富,林薇,等。申請号:202111257188.4,2021年。 [7] 發明專利:一種基于雙向時間卷積神經網絡與多頭自注意力機制的異常網絡流量檢測方法。發明人:蔡賽華,劉明傑,徐涵,等。申請号:202211409998.1,2022年。 [8] 發明專利:一種基于最大頻繁模式非相似性的異常網絡流量檢測方法。發明人:蔡賽華,陳錦富,徐波,等。申請号:202210226905.5,2022年。 [9] 發明專利:一種基于圖注意力網絡的惡意網絡流量檢測方法。發明人:蔡賽華,趙文軍,陳錦富,等。申請号:202310950685.5,2023年。 [10] 發明專利:一種基于循環生成對抗網絡和多頭自注意力機制的異常流量檢測方法。發明人:蔡賽華,趙文軍,陳錦富,等。申請号:202311283486.X,2023年。 [11] 發明專利:一種基于雙向時序卷積網絡和多堆疊集成學習的概念漂移檢測方法。發明人:蔡賽華,胡佚恺,趙英偉,等。申請号:202311702201.1,2023年。 [12] 發明專利:一種基于概念漂移檢測和自适應的惡意流量檢測方法。發明人:蔡賽華,唐晗,胡佚恺,等。申請号:202410009003.5,2024年。
(3)獲批的部分軟件著作權 [1] 基于模式距離的異常流量檢測平台[簡稱:Pdbandp]V1.0。完成人:蔡賽華,魏忠旺,林敏,等。登記号:2022SR0626385。 [2] 基于概念漂移檢測的異常網絡流量識别平台[簡稱:ANTICD]V1.0。完成人:蔡賽華,唐晗,趙文軍,等。登記号:2023SR0414803。 [3] 基于雙向時序卷積網絡和多頭自注意力機制的異常網絡流量檢測平台[簡稱:ANTbTCNAte]V1.0。完成人:蔡賽華,陳智霖,劉明傑,等。登記号:2023SR0414802。 [4] 基于特征差異的異常數據檢測平台[簡稱:KCROD]V1.0。完成人:蔡賽華,趙光瀚,孫瑜,等。登記号:2023SR0598372。 [5] 基于圖注意力網絡和決策樹的惡意流量檢測平台[簡稱:MTDPGSADT]V1.0。完成人:蔡賽華,趙星宇,趙文軍,等。登記号:2023SR1630233。 [6] 基于時序卷積網絡和多堆疊集成學習的網絡流量概念漂移檢測平台[簡稱:CDTCNML]V1.0。完成人:蔡賽華,吳佳旭,趙英偉,等。登記号:2023SR1633973。
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