Chinese Journal of Network and Information Security ›› 2023, Vol. 9 ›› Issue (3): 102-112.doi: 10.11959/j.issn.2096-109x.2023042
• Papers • Previous Articles Next Articles
Guanyun FENG, Cai FU, Jianqiang LYU, Lansheng HAN
Revised:
2023-03-15
Online:
2023-06-25
Published:
2023-06-01
Supported by:
CLC Number:
Guanyun FENG, Cai FU, Jianqiang LYU, Lansheng HAN. Insider threat detection based on operational attention and data augmentation[J]. Chinese Journal of Network and Information Security, 2023, 9(3): 102-112.
[1] | HOMOLIAK I , TOFFALINI F , GUARNIZO J ,et al. Insight into insiders and IT:a survey of insider threat taxonomies,analysis,modeling,and countermeasures[J]. ACM Computing Surveys, 2020,52(2): 1-40. |
[2] | Insider threat 2022 report[EB]. |
[3] | Gurucul - insider threat survey report[EB]. |
[4] | Insider threat report 2023[EB]. |
[5] | YUAN S H , WU X T . Deep learning for insider threat detection:review,challenges and opportunities[J]. Computers & Security, 2021,104:102221. |
[6] | LIU L , DE VEL O , HAN Q L ,et al. Detecting and preventing cyber insider threats:a survey[J]. IEEE Communications Surveys & Tutorials, 2018,20(2): 1397-1417. |
[7] | MONTANO I H , ARANDA J J G , DIAZ J R ,et al. Survey of techniques on data leakage protection and methods to address the insider threat[J]. Cluster Computing, 2022,25(6): 4289-4302. |
[8] | XU J H , WU H X , WANG J M ,et al. Anomaly transformer:time series anomaly detection with association discrepancy[EB/OL]. 2021:arXiv:2110.02642. |
[9] | Cmu-cert insider threat test dataset[EB]. |
[10] | TUOR A , KAPLAN S , HUTCHINSON B ,et al. Deep learning for unsupervised insider threat detection in structured cybersecurity data streams[C]// Proceeding of Workshops of the Thirty-First AAAI Conference on Artificial Intelligence. 2017. |
[11] | LIU L , DE VEL O , CHEN C ,et al. Anomaly-based insider threat detection using deep autoencoders[C]// Proceedings of 2018 IEEE International Conference on Data Mining Workshops (ICDMW). 2019: 39-48. |
[12] | SHARMA B , POKHAREL P , JOSHI B . User behavior analytics for anomaly detection using LSTM autoencoder-insider threat detection[C]// Proceedings of the 11th International Conference on Advances in Information Technology. 2020: 1-9. |
[13] | LIU L , CHEN C , ZHANG J ,et al. Insider threat identification using the simultaneous neural learning of multi-source logs[J]. IEEE Access, 2019,7: 183162-183176. |
[14] | SINGH M , MEHTRE B , SANGEETHA S . User behavior based insider threat detection using a multi fuzzy classifier[J]. Multimedia Tools and Applications, 2022,81(16): 22953-22983. |
[15] | JIANG J G , CHEN J M , GU T B ,et al. Warder:online insider threat detection system using multi-feature modeling and graph-based correlation[C]// Proceedings of MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM). 2020: 1-6. |
[16] | LIU C C , ZHONG Y , WANG Y L . Improved detection of user malicious behavior through log mining based on IHMM[C]// Proceedings of 2018 5th International Conference on Systems and Informatics (ICSAI). 2019: 1193-1198. |
[17] | LYU B , WANG D , WANG Y ,et al. A hybrid model based on multi-dimensional features for insider threat detection[C]// Proceedings of International Conference on Wireless Algorithms,Systems,and Applications. 2018: 333-344. |
[18] | NASSER M , AL-MHIQANI . A new intelligent multilayer framework for insider threat detection[J]. Computers & Electrical Engineering, 2022,97:107597. |
[19] | GAYATHRI R G , SAJJANHAR A , XIANG Y . Image-based feature representation for insider threat classification[J]. Applied Sciences, 2020,10(14): 4945. |
[20] | CHATTOPADHYAY P , WANG L P , TAN Y P . Scenario-based insider threat detection from cyber activities[J]. IEEE Transactions on Computational Social Systems, 2018,5(3): 660-675. |
[21] | NASIR R , AFZAL M , LATIF R ,et al. Behavioral based insider threat detection using deep learning[J]. IEEE Access, 2021,9: 143266-143274. |
[22] | MENG F Z , LOU F , FU Y S ,et al. Deep learning based attribute classification insider threat detection for data security[C]// Proceedings of 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC). 2018: 576-581. |
[23] | JIANG W , TIAN Y , LIU W X ,et al. An insider threat detection method based on user behavior analysis[C]// International Conference on Intelligent Information Processing. 2018: 421-429. |
[24] | LI D Y , YANG L , ZHANG H G ,et al. Image-based insider threat detection via geometric transformation[J]. Security and Communication Networks, 2021: 1-18. |
[25] | HUANG W Q , ZHU H , LI C ,et al. ITDBERT:temporal-semantic representation for insider threat detection[C]// Proceedings of 2021 IEEE Symposium on Computers and Communications (ISCC). 2021: 1-7. |
[26] | LEGG P A , BUCKLEY O , GOLDSMITH M ,et al. Automated insider threat detection system using user and role-based profile assessment[J]. IEEE Systems Journal, 2017,11(2): 503-512. |
[27] | JIANG J G , CHEN J M , GU T B ,et al. Anomaly detection with graph convolutional networks for insider threat and fraud detection[C]// Proceedings of MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM). 2020: 109-114. |
[28] | ABEDINIA O , AMJADY N , ZAREIPOUR H . A new feature selection technique for load and price forecast of electrical power systems[J]. IEEE Transactions on Power Systems, 2017,32(1): 62-74. |
[29] | XU K , BA J L , KIROS R ,et al. Show,attend and tell:neural image caption generation with visual attention[C]// Proceedings of the 32nd International Conference on International Conference on Machine Learning. 2015: 2048-2057. |
[30] | JADERBERG M , SIMONYAN K , ZISSERMAN A ,et al. Spatial transformer networks[J]. arXiv Preprint arXiv:1506.02025, 2015. |
[31] | CHENG X , LI X , YANG J ,et al. SESR:single image super resolution with recursive squeeze and excitation networks[C]// Proceedings of 2018 24th International Conference on Pattern Recognition (ICPR). 2018: 147-152. |
[32] | DOSOVITSKIY A , BEYER L , KOLESNIKOV A ,et al. An image is worth 16x16 words:transformers for image recognition at scale[K]. arXiv Preprint arXiv:2010.11929, 2020. |
[33] | LIU Z , LIN Y T , CAO Y ,et al. Swin transformer:hierarchical vision transformer using shifted windows[C]// Proceedings of 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 2022: 9992-10002. |
[34] | VASWANI A , SHAZEER N , PARMAR N ,et al. Attention is all you need[C]// Proceedings of the 31st International Conference on Neural Information Processing Systems. 2017: 6000-6010. |
[35] | SUN F , LIU J , WU J ,et al. BERT4Rec:sequential recommendation with bidirectional encoder representations from transformer[C]// Proceedings of the 28th ACM International Conference on Information and Knowledge Management. 2019: 1441-1450. |
[36] | MNIH V , HEESS N , GRAVES A ,et al. Recurrent models of visual attention[J]. arXiv Preprint arXiv:1406.6247, 2014. |
[37] | ZHAO B , WU X , FENG J S ,et al. Diversified visual attention networks for fine-grained object classification[J]. IEEE Transactions on Multimedia, 2017,19(6): 1245-1256. |
[38] | STOLLENGA M F , MASCI J , GOMEZ F ,et al. Deep networks with internal selective attention through feedback connections[C]// Proceedings of the 27th International Conference on Neural Information Processing Systems. 2014: 3545-3553. |
[39] | ELSAYED G F , KORNBLITH S , LE Q V . Saccader:improving accuracy of hard attention models for vision[J]. arXiv Preprint arXiv:1908.07644, 2019. |
[40] | ANDERSON P , HE X D , BUEHLER C ,et al. Bottom-up and top-down attention for image captioning and visual question answering[C]// Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2018: 6077-6086. |
[1] | Liquan CHEN, Yuhang ZHU, Yu WANG, Zhongyuan QIN, Yang MA. New hash function based on C-MD structure and chaotic neural network [J]. Chinese Journal of Network and Information Security, 2023, 9(3): 1-15. |
[2] | Zhao CAI, Tao JING, Shuang REN. Survey on Ethereum phishing detection technology [J]. Chinese Journal of Network and Information Security, 2023, 9(2): 21-32. |
[3] | Zezhou HOU, Jiongjiong REN, Shaozhen CHEN. Security evaluation for parameters of SIMON-like cipher based on neural network distinguisher [J]. Chinese Journal of Network and Information Security, 2023, 9(2): 154-163. |
[4] | Rongna XIE, Zhuhong MA, Zongyu LI, Ye TIAN. Encrypted traffic classification method based on convolutional neural network [J]. Chinese Journal of Network and Information Security, 2022, 8(6): 84-91. |
[5] | Dibin SHAN, Xuehui DU, Wenjuan WANG, Aodi LIU, Na WANG. Access control relationship prediction method based on GNN dual source learning [J]. Chinese Journal of Network and Information Security, 2022, 8(5): 40-55. |
[6] | Hao CHEN, Feng WANG, Weiming ZHANG, Nenghai YU. Carrier-independent deep optical watermarking algorithm [J]. Chinese Journal of Network and Information Security, 2022, 8(4): 110-118. |
[7] | Dian LIN, Li PAN, Ping YI. Research on the robustness of convolutional neural networks in image recognition [J]. Chinese Journal of Network and Information Security, 2022, 8(3): 111-122. |
[8] | Xinya WANG, Guang HUA, Hao JIANG, Haijian ZHANG. Survey on intellectual property protection for deep learning model [J]. Chinese Journal of Network and Information Security, 2022, 8(2): 1-14. |
[9] | Tong QIAO, Hongwei YAO, Binmin PAN, Ming XU, Yanli CHEN. Research progress of digital image forensic techniques based on deep learning [J]. Chinese Journal of Network and Information Security, 2021, 7(5): 13-28. |
[10] | Zhenglong WANG, Baowen ZHANG. Survey of generative adversarial network [J]. Chinese Journal of Network and Information Security, 2021, 7(4): 68-85. |
[11] | Jinyin CHEN, Dunjie ZHANG, Guohan HUANG, Xiang LIN, Liang BAO. Adversarial attack and defense on graph neural networks: a survey [J]. Chinese Journal of Network and Information Security, 2021, 7(3): 1-28. |
[12] | Peijie LI, Li ZHANG, Yunfei XIA, Liming XU. Architecture design of re-configurable convolutional neural network on software definition [J]. Chinese Journal of Network and Information Security, 2021, 7(3): 29-36. |
[13] | Hao CHEN, Ping YI. Code vulnerability detection method based on graph neural network [J]. Chinese Journal of Network and Information Security, 2021, 7(3): 37-45. |
[14] | Qingyin TAN, Yingming ZENG, Ye HAN, Yijing LIU, Zheli LIU. Survey on backdoor attacks targeted on neural network [J]. Chinese Journal of Network and Information Security, 2021, 7(3): 46-58. |
[15] | Xin ZHANG,Weizhong QIANG,Yueming WU,Deqing ZOU,Hai JIN. Mining behavior pattern of mobile malware with convolutional neural network [J]. Chinese Journal of Network and Information Security, 2020, 6(6): 35-44. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||
|