| Predicting defect-prone software modules using support vector machines KO Elish, MO Elish Journal of Systems and Software, Elsevier 81 (5), 649-660, 2008 | 689 | 2008 |
| Profiling user-trigger dependence for Android malware detection KO Elish, X Shu, DD Yao, BG Ryder, X Jiang Computers & Security, Elsevier Journal 49, 255-273, 2015 | 152 | 2015 |
| Application of treenet in predicting object-oriented software maintainability: A comparative study MO Elish, KO Elish IEEE European Conference on Software Maintenance and Reengineering, 69-78, 2009 | 121 | 2009 |
| On the need of precise inter-app ICC classification for detecting Android malware collusions KO Elish, D Yao, BG Ryder IEEE Mobile Security Technologies (MoST), in conjunction with IEEE S&P, 2015 | 77 | 2015 |
| A Literature Review on Medicine Recommender Systems B Stark, C Knahl, M Aydin, K Elish International Journal of Advanced Computer Science and Applications (IJACSA …, 2019 | 60 | 2019 |
| A classification of refactoring methods based on software quality attributes KO Elish, M Alshayeb Arabian Journal for Science and Engineering, Springer 36 (7), 1253-1267, 2011 | 58 | 2011 |
| User-centric dependence analysis for identifying malicious mobile apps KO Elish, D Yao, BG Ryder IEEE Mobile Security Technologies (MoST), in conjunction with IEEE S&P, 2012 | 57 | 2012 |
| Identifying Mobile Inter-App Communication Risks K Elish, H Cai, D Barton, D Yao, B Ryder IEEE Transactions on Mobile Computing, 2020 | 44 | 2020 |
| MR-Droid: A scalable and prioritized analysis of inter-app communication risks F Liu, H Cai, G Wang, DD Yao, KO Elish, BG Ryder IEEE Mobile Security Technologies (MoST), in conjunction with IEEE S&P, 2017 | 38 | 2017 |
| Using Software Quality Attributes to Classify Refactoring to Patterns. KO Elish, M Alshayeb Journal of Software 7 (2), 408-419, 2012 | 37 | 2012 |
| Machine Learning-based Prediction of Prolonged Length of Stay in Newborns B Thompson, KO Elish, R Steele IEEE International Conference on Machine Learning and Applications (ICMLA), 2018 | 34 | 2018 |
| Comprehensive Behavior Profiling for Proactive Android Malware Detection B Wolfe, KO Elish, DD Yao 17th International Information Security Conference, Springer, 2014 | 34 | 2014 |
| Investigating the Effect of Refactoring on Software Testing Effort KO Elish, M Alshayeb IEEE Asia-Pacific Software Engineering Conference, APSEC, 29-34, 2009 | 30 | 2009 |
| A Static Assurance Analysis of Android Applications KO Elish, DD Yao, BG Ryder, X Jiang Technical Report TR-13-03, Computer Science, Virginia Tech, 2013 | 29 | 2013 |
| High Precision Screening for Android Malware with Dimensionality Reduction B Wolfe, K Elish, D Yao IEEE International Conference on Machine Learning and Applications (ICMLA), 2014 | 24 | 2014 |
| BetterChoice: A Migraine Drug Recommendation System Based on Neo4J B Stark, C Knahl, M Aydin, M Samarah, K Elish IEEE International Conference on Computational Intelligence and Applications …, 2017 | 23 | 2017 |
| A Survey on Connected Vehicles Vulnerabilities and Countermeasures C Riggs, CE Rigaud, R Beard, T Douglas, K Elish Journal of Traffic and Logistics Engineering 6 (1), 2018 | 17 | 2018 |
| Identifying Android Malware Families Using Android-Oriented Metrics W Blanc, L Hashem, K Elish, H Almohri IEEE International Conference on Big Data, 2019 | 15 | 2019 |
| Lightweight, effective detection and characterization of mobile malware families KO Elish, MO Elish, HMJ Almohri IEEE Transactions on Computers 71 (11), 2982-2995, 2022 | 7 | 2022 |
| An Empirical Comparison of Resampling Ensemble Methods of Deep Learning Neural Networks for Cross-Project Software Defect Prediction MO Elish, K Elish International Journal of Intelligent Engineering and Systems 14 (3), 2021 | 6 | 2021 |
Danfeng (Daphne) Yao, IEEE FellowVirginia TechVerified email at vt.edu
