[1] |
POTTER B , DAY G . The effectiveness of anti-malware tools[J]. Computer Fraud & Security, 2009(3): 12-13.
|
[2] |
KIM J Y , BU S J , CHO S B . Zero-day malware detection using transferred generative adversarial networks based on deep autoencoders[J]. Information Sciences, 2018(460): 83-102.
|
[3] |
PENG W , LI F , ZOU X ,et al. Behavioral malware detection in delay tolerant networks[J]. IEEE Transactions on Parallel and Distributed systems, 2014,25(1): 53-63.
|
[4] |
PEKTA? A , ACARMAN T . Malware classification based on API calls and behaviour analysis[J]. IET Information Security, 2017,12(2): 107-117.
|
[5] |
HAN L , ZHOU M , HAN S ,et al. Targeting malware discrimination based on reversed association task[J]. Concurrency and Computation:Practice and Experience, 2018:e4922.
|
[6] |
KOLOSNJAJI B , ZARRAS A , WEBSTER G ,et al. Deep learning for classification of malware system call sequences[C]// Australasian Joint Conference on Artificial Intelligence. Springer, 2016: 137-149.
|
[7] |
CHO I K , KIM T G , SHIM Y J ,et al. Malware similarity analysis using API sequence alignments[J]. Journal of Internet Services and Information Security., 2014,4(4): 103-114.
|
[8] |
SANTOS I , BREZO F , UGARTE-PEDRERO X ,et al. Opcode sequences as representation of executables for data-mining-based unknown malware detection[J]. Information Sciences, 2013(231): 64-82.
|
[9] |
ARP D , SPREITZENBARTH M , HUBNER M ,et al. DREBIN:effective and explainable detection of Android malware in your pocket[C]// NDSS. 2014: 23-26.
|
[10] |
XU K S , KLIGER M , HERO III A O . Adaptive evolutionary clustering[J]. Data Mining and Knowledge Discovery, 2014,28(2): 304-336.
|
[11] |
WAN Y , LIU X , WU Y ,et al. ICGT:a novel incremental clustering approach based on GMM tree[J]. Data & Knowledge Engineering, 2018(117): 71-86.
|
[12] |
PFEFFER A , CALL C , CHAMBERLAIN J . Malware analysis and attribution using genetic information[C]// 2012 7th International Conference on Malicious and Unwanted Software (MALWARE). IEEE, 2012: 39-45.
|
[13] |
WU S , WANG P , LI X ,et al. Effective detection of android malware based on the usage of data flow APIs and machine learning[J]. Information and Software Technology, 2016,75: 17-25.
|
[14] |
DAS S , LIU Y , ZHANG W . Semantics-based online malware detection:towards efficient real-time protection against malware[J]. IEEE transactions on information forensics and security, 2016,11(2): 289-302.
|
[15] |
ZHAO H , XU M , ZHENG N ,et al. Malicious executables classification based on behavioral factor analysis[C]// International Conference on e-Education,e-Business,e-Management,and e-Learning. IEEE, 2010: 502-506.
|
[16] |
DENG Z , LLOYD H , XIA C ,et al. Components of variation in female common cuckoo calls[J]. Behavioural Processes, 2018(158): 106-112.
|
[17] |
SARACINO A , SGANDURRA D , DINI G . Madam:effective and efficient behavior-based Android malware detection and prevention[J]. IEEE Transactions on Dependable and Secure Computing, 2018,15(1): 83-97.
|
[18] |
BOULEMNADJEL A , HACHOUF F , KHARFOUCHI S . GMM estimation of 2D-RCA models with applications to texture image classification[J]. IEEE Transactions on Image Processing, 2016,25(2): 528-539.
|
[19] |
ENGEL P M , HEINEN M R . Incremental learning of multivariate gaussian mixture models[C]// Brazilian Symposium on Artificial Intelligence. Springer, 2010: 82-91.
|
[20] |
SONG M Z , WANG H B . Highly efficient incremental estimation of Gaussian mixture models for online data stream clustering[J]. Proceedings of SPIE-International Society for Optics and Photonics, 2005(5803): 174-184.
|
[21] |
TANG Z , SHEN F , ZHAO J . Speaker recognition based on SOINN and incremental learning Gaussian mixture model[C]// The 2013 International Joint Conference on Neural Networks. IEEE, 2013: 1-6.
|
[22] |
LIU Y , PERRONNIN F . A similarity measure between unordered vector sets with application to image categorization[C]// 2008 IEEE Conference on Computer Vision and Pattern Recognition. 2008: 24-26.
|
[23] |
RONEN R , RADU M , FEUERSTEIN C ,et al. Microsoft malware classification challenge[J]. arXiv Preprint,arXiv:1802.10135, 2018.
|
[24] |
LIPTON Z C , BERKOWITZ J , ELKAN C . A critical review of recurrent neural networks for sequence learning[J]. arXiv Preprint,arXiv:1506.00019, 2015.
|
[25] |
LU X F , XIAO Z , JIANG F S ,et al. ASSCA:API based sequence and statistics features combined malware detection architecture[J]. Procedia Computer Science, 2018,129: 248-256.
|
[26] |
AHMED F , HAMEED H , SHAFIQ M Z ,et al. Using spatio-temporal information in API calls with machine learning algorithms for malware detection[C]// The 2nd ACM Workshop on Security and Artificial Intelligence. ACM, 2009: 55-62.
|