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| VirusShare is proud to have played a part in assisting the tireless efforts of the global research community and is thankful to the researchers who have contributed to the project. Below is an incomplete but growing list of publications that have cited VirusShare as a data source for their research. |
| • 2020 • |
| Abbasi, Muhammad Shabbir; Al-Sahaf, Harith; Welch, Ian; (2020). Particle Swarm Optimization: A Wrapper-Based Feature Selection Method for Ransomware Detection and Classification. International Conference on the Applications of Evolutionary Computation (Part of EvoStar), 181-196. Springer. |
| Ahmed, Yahye Abukar; Koçer, Barış; Al-rimy, Bander Ali Saleh; (2020). Automated Analysis Approach for the Detection of High Survivable Ransomware. KSII Transactions on Internet and Information Systems (TIIS), 14(5), 2236-2257. 한국인터넷정보학회. |
| Ahmed, Yahye Abukar; Koçer, Barış; Huda, Shamsul; Al-rimy, Bander Ali Saleh; Hassan, Mohammad Mehedi; (2020). A system call refinement-based enhanced Minimum Redundancy Maximum Relevance method for ransomware early detection. Journal of Network and Computer Applications, 102753. Elsevier. |
| Alaeiyan, Mohammadhadi; Dehghantanha, Ali; Dargahi, Tooska; Conti, Mauro; Parsa, Saeed; (2020). A multilabel fuzzy relevance clustering system for malware attack attribution in the edge layer of cyber-physical networks. ACM Transactions on Cyber-Physical Systems, 4(3), 1-22. ACM New York, NY, USA. |
| Alam, Manaar; Mukhopadhyay, Debdeep; Kadiyala, Sai Praveen; Lam, Siew-Kei; Srikanthan, Thambipillai; (2020). Improving accuracy of HPC-based malware classification for embedded platforms using gradient descent optimization. Journal of Cryptographic Engineering, 1-15. Springer. |
| Alazab, Moutaz; (2020). Automated Malware Detection in Mobile App Stores Based on Robust Feature Generation. Electronics, 9(3), 435. Multidisciplinary Digital Publishing Institute. |
| Alazab, Moutaz; Alazab, Mamoun; Shalaginov, Andrii; Mesleh, Abdelwadood; Awajan, Albara; (2020). Intelligent mobile malware detection using permission requests and api calls. Future Generation Computer Systems, 107, 509-521. Elsevier. |
| Alhanahnah, Mohannad; Yan, Qiben; Bagheri, Hamid; Zhou, Hao; Tsutano, Yutaka; Srisa-An, Witawas; Luo, Xiapu; (2020). DINA: Detecting Hidden Android Inter-App Communication in Dynamic Loaded Code. IEEE Transactions on Information Forensics and Security, 15, 2782-2797. IEEE. |
| Ali, Abdullah; Eshete, Birhanu; (2020). Best-Effort Adversarial Approximation of Black-Box Malware Classifiers. arXiv preprint arXiv:2006.15725 |
| Allgood, Nicholas R; Nicholas, Charles K; (2020). A quantum algorithm to locate unknown hashes for known n-grams within a large malware corpus. arXiv preprint arXiv:2005.02911 |
| Alrabaee, Saed; Debbabi, Mourad; Shirani, Paria; Wang, Lingyu; Youssef, Amr; Rahimian, Ashkan; Nouh, Lina; Mouheb, Djedjiga; Huang, He; Hanna, Aiman; (2020). Free Open-Source Software Fingerprinting. Binary Code Fingerprinting for Cybersecurity, 157-186. Springer. |
| Alswaina, Fahad; Elleithy, Khaled; (2020). Android Malware Family Classification and Analysis: Current Status and Future Directions. Electronics, 9(6), 942. Multidisciplinary Digital Publishing Institute. |
| Amin, Muhammad; Tanveer, Tamleek Ali; Tehseen, Mohammad; Khan, Murad; Khan, Fakhri Alam; Anwar, Sajid; (2020). Static malware detection and attribution in android byte-code through an end-to-end deep system. Future Generation Computer Systems, 102, 112-126. Elsevier. |
| Babu, Pasupuleti Nagendra; Ramakrishna, S; (2020). Critical Review on Privacy and Security Issues in Data Mining. Emerging Research in Data Engineering Systems and Computer Communications, 217-230. Springer. |
| Bajpai, Pranshu; Enbody, Richard; (2020). An empirical study of key generation in cryptographic ransomware. 2020 International Conference on Cyber Security and Protection of Digital Services (Cyber Security), 1-8. IEEE. |
| Basole, Samanvitha; Di Troia, Fabio; Stamp, Mark; (2020). Multifamily malware models. Journal of Computer Virology and Hacking Techniques, 1-14. Springer. |
| BehradFar, Mohammad Mehdi; HaddadPajouh, Hamed; Dehghantanha, Ali; Azmoodeh, Amin; Karimipour, Hadis; Parizi, Reza M; Srivastava, Gautam; (2020). RAT Hunter: Building Robust Models for Detecting Remote Access Trojans Based on Optimum Hybrid Features. Handbook of Big Data Privacy, 371-383. Springer. |
| Benthin, Marius; (2020). Conception and Implementation of an Open-Source Threat Intelligence System. |
| Botacin, Marcus; Ceschin, Fabricio; de Geus, Paulo; Grégio, André; (2020). We Need to Talk About AntiViruses: Challenges & Pitfalls of AV Evaluations. Computers & Security, 101859. Elsevier. |
| Cai, Haipeng; (2020). Embracing Mobile App Evolution via Continuous Ecosystem Mining and Characterization. |
| Cai, Haipeng; (2020). Assessing and improving malware detection sustainability through app evolution studies. ACM Transactions on Software Engineering and Methodology (TOSEM), 29(2), 1-28. ACM New York, NY, USA. |
| Cai, Haipeng; Fu, Xiaoqin; Hamou-Lhadj, Abdelwahab; (2020). A study of run-time behavioral evolution of benign versus malicious apps in android. Information and Software Technology, 122, 106291. Elsevier. |
| Chatterjee, Moitrayee; Datta, Prerit; Abri, Faranak; Namin, Akbar Siami; Jones, Keith S; (2020). Launching Stealth Attacks using Cloud. arXiv preprint arXiv:2006.07908 |
| Christian, Brian P; (2020). Data Surveillance for Privileged Assets based on Threat Streams. . Google Patents. |
| Chu, Qianfeng; Liu, Gongshen; Zhu, Xinyu; (2020). Visualization Feature and CNN Based Homology Classification of Malicious Code. Chinese Journal of Electronics, 29(1), 154-160. IET. |
| Darshan, SL Shiva; Jaidhar, CD; (2020). An empirical study to estimate the stability of random forest classifier on the hybrid features recommended by filter based feature selection technique. International Journal of Machine Learning and Cybernetics, 11(2), 339-358. Springer. |
| Devi, R Aiyshwariya; Arunachalam, AR; Rajakumar, PS; (2020). Development of Advanced IoT Devices using ECC-LSTM for an Enhanced Device Security. Development, 29(9s), 5074-5087 |
| D’Angelo, Gianni; Ficco, Massimo; Palmieri, Francesco; (2020). Malware detection in mobile environments based on Autoencoders and API-images. Journal of Parallel and Distributed Computing, 137, 26-33. Elsevier. |
| Egitmen, Alper; Bulut, Irfan; Aygun, R; Gunduz, A Bilge; Seyrekbasan, Omer; Yavuz, A Gokhan; (2020). Combat Mobile Evasive Malware via Skip-Gram-Based Malware Detection. Security and Communication Networks, 2020. Hindawi. |
| Fang, Yong; Zeng, Yuetian; Li, Beibei; Liu, Liang; Zhang, Lei; (2020). DeepDetectNet vs RLAttackNet: An adversarial method to improve deep learning-based static malware detection model. Plos one, 15(4), e0231626. Public Library of Science San Francisco, CA USA. |
| Feng, Ruitao; Chen, Sen; Xie, Xiaofei; Meng, Guozhu; Lin, Shang-Wei; Liu, Yang; (2020). A Performance-Sensitive Malware Detection System Using Deep Learning on Mobile Devices. arXiv preprint arXiv:2005.04970 |
| Fu, Hao; Hu, Pengfei; Zheng, Zizhan; Das, Aveek; Pathak, Parth; Gu, Tianbo; Zhu, Sencun; Mohapatra, Prasant; (2020). Towards Automatic Detection of Nonfunctional Sensitive Transmissions in Mobile Applications. IEEE Transactions on Mobile Computing. IEEE. |
| Gajrani, Jyoti; Agarwal, Umang; Laxmi, Vijay; Bezawada, Bruhadeshwar; Gaur, Manoj Singh; Tripathi, Meenakshi; Zemmari, Akka; (2020). EspyDroid+: Precise reflection analysis of android apps. Computers & Security, 90, 101688. Elsevier. |
| Gibert Llauradó, Daniel; Mateu Piñol, Carles; Planes Cid, Jordi; (2020). The rise of machine learning for detection and classification of malware: Research developments, trends and challenge. Journal of Network and Computer Applications, 2020, vol. 153, 102526. Elsevier. |
| Gibert, Daniel; Mateu, Carles; Planes, Jordi; (2020). HYDRA: A Multimodal Deep Learning Framework for Malware Classification. Computers & Security, 101873. Elsevier. |
| Gibert, Daniel; Mateu, Carles; Planes, Jordi; (2020). The rise of machine learning for detection and classification of malware: Research developments, trends and challenges. Journal of Network and Computer Applications, 153, 102526. Elsevier. |
| Gopalakrishnan, Prakash; Narayanan, R Sankara; Kamath, Rahul; Ramani, Anirud; (2020). Analyzing Diverse Data Mining Techniques to Detect the Malware based on Signature. |
| Goyal, Parth S; Kakkar, Akshat; Vinod, Gopika; Joseph, Gigi; (2020). Crypto-Ransomware Detection Using Behavioural Analysis. Reliability, Safety and Hazard Assessment for Risk-Based Technologies, 239-251. Springer. |
| Gupta, Deepak; Rani, Rinkle; (2020). Improving malware detection using big data and ensemble learning. Computers & Electrical Engineering, 86, 106729. Elsevier. |
| Hatada, Mitsuhiro; Mori, Tatsuya; (2020). CLAP: Classification of Android PUAs by Similarity of DNS Queries. IEICE TRANSACTIONS on Information and Systems, 103(2), 265-275. The Institute of Electronics, Information and Communication Engineers. |
| Hua, Yakang; Du, Yuanzheng; He, Dongzhi; (2020). Classifying Packed Malware Represented as Control Flow Graphs using Deep Graph Convolutional Neural Network. 2020 International Conference on Computer Engineering and Application (ICCEA), 254-258. IEEE. |
| Hussain, Ahamed KH; Kakavand, Mohsen; Silval, Mira; Arulsamy, Lingges; (2020). A Novel Android Security Framework to Prevent Privilege Escalation Attacks.. International Journal of Computer Network & Information Security, 12(1) |
| Hwang, Chanwoong; Hwang, Junho; Kwak, Jin; Lee, Taejin; (2020). Platform-Independent Malware Analysis Applicable to Windows and Linux Environments. Electronics, 9(5), 793. Multidisciplinary Digital Publishing Institute. |
| Hwang, Jinsoo; Kim, Jeankyung; Lee, Seunghwan; Kim, Kichang; (2020). Two-Stage Ransomware Detection Using Dynamic Analysis and Machine Learning Techniques. Wireless Personal Communications, 112(4), 2597-2609. Springer. |
| Imamverdiyev, Yadigar N; Abdullayeva, Fargana J; (2020). Deep Learning in Cybersecurity: Challenges and Approaches. International Journal of Cyber Warfare and Terrorism (IJCWT), 10(2), 82-105. IGI Global. |
| Irshad, Areeba; Dutta, Malay Kishore; (2020). Identification of Windows-Based Malware by Dynamic Analysis Using Machine Learning Algorithm. Advances in Computational Intelligence and Communication Technology, 207-218. Springer. |
| Jeon, Seungho; Moon, Jongsub; (2020). Malware-Detection Method with a Convolutional Recurrent Neural Network Using Opcode Sequences. Information Sciences. Elsevier. |
| Joseph, D Paul; Norman, Jasmine; (2020). A Review and Analysis of Ransomware Using Memory Forensics and Its Tools. Smart Intelligent Computing and Applications, 505-514. Springer. |
| Joseph, Paul; Norman, Jasmine; (2020). Systematic Memory Forensic Analysis of Ransomware using Digital Forensic Tools. International Journal of Natural Computing Research (IJNCR), 9(2), 61-81. IGI Global. |
| KP, Soman; Alazab, Mamoun; (2020). A Comprehensive Tutorial and Survey of Applications of Deep Learning for Cyber Security. . TechRxiv. |
| Kadiyala, Sai Praveen; Alam, Manaar; Shrivastava, Yash; Patranabis, Sikhar; Abbas, Muhamed Fauzi Bin; Biswas, Arnab Kumar; Mukhopadhyay, Debdeep; Srikanthan, Thambipillai; (2020). LAMBDA: Lightweight Assessment of Malware for emBeddeD Architectures. ACM Transactions on Embedded Computing Systems (TECS), 19(4), 1-31. ACM New York, NY, USA. |
| Kato, Hiroya; Haruta, Shuichiro; Sasase, Iwao; (2020). Android malware detection scheme based on level of SSL server certificate. IEICE Transactions on Information and Systems, 103(2), 379-389. The Institute of Electronics, Information and Communication Engineers. |
| Kim, Kichang; Kim, Jinsung; Ko, Eunbyeol; Yi, Jeong Hyun; (2020). Risk Assessment Scheme for Mobile Applications Based on Tree Boosting. IEEE Access, 8, 48503-48514. IEEE. |
| Kok, SH; Abdullah, Azween; Jhanjhi, NZ; (2020). Early Detection of Crypto-Ransomware Using Pre-Encryption Detection Algorithm. Journal of King Saud University-Computer and Information Sciences. Elsevier. |
| Kouliaridis, Vasileios; Kambourakis, Georgios; Geneiatakis, Dimitris; Potha, Nektaria; (2020). Two Anatomists Are Better than One—Dual-Level Android Malware Detection. Symmetry, 12(7), 1128. Multidisciplinary Digital Publishing Institute. |
| Kucuk, Yunus; Yan, Guanhua; (2020). Deceiving Portable Executable Malware Classifiers into Targeted Misclassification with Practical Adversarial Examples. Proceedings of the Tenth ACM Conference on Data and Application Security and Privacy, 341-352 |
| Kumar, Amit; Gupta, Mugdha; Kumar, Gaurav; Handa, Anand; Kumar, Nitesh; Shukla, Sandeep Kumar; (2020). A Review: Malware Analysis Work at IIT Kanpur. Cyber Security in India, 39-48. Springer. |
| Kuruvila, Abraham Peedikayil; Kundu, Shamik; Basu, Kanad; (2020). Defending Hardware-based Malware Detectors against Adversarial Attacks. arXiv preprint arXiv:2005.03644 |
| Laurenza, Giuseppe; (2020). Critical Infrastructures Security: Improving Defense Against Novel Malware and Advanced Persistent Threats. . Sapienza–University of Rome. |
| Li, Jingmei; Xue, Di; Wu, Weifei; Wang, Jiaxiang; (2020). Incremental Learning for Malware Classification in Small Datasets. Security and Communication Networks, 2020. Hindawi. |
| Li, Zeng; Huang, Wenchao; Xiong, Yan; Ren, Siqi; Zhu, Tuanfei; (2020). Incremental learning imbalanced data streams with concept drift: The dynamic updated ensemble algorithm. Knowledge-Based Systems, 105694. Elsevier. |
| Li, Zhiqiang; (2020). Advanced Techniques to Detect Complex Android Malware. |
| Libri, Antonio; Bartolini, Andrea; Benini, Luca; (2020). pAElla: Edge-AI based Real-Time Malware Detection in Data Centers. IEEE Internet of Things Journal. IEEE. |
| Liu, Xiaojian; Lei, Qian; Liu, Kehong; (2020). A Graph-Based Feature Generation Approach in Android Malware Detection with Machine Learning Techniques. Mathematical Problems in Engineering, 2020. Hindawi. |
| Lysenko, Sergii; Bobrovnikova, Kira; Popov, Peter; Kharchenko, Viacheslav; Medzatyi, Dmytro; (2020). Spyware Detection Technique Based on Reinforcement Learning. |
| Martins, Nuno; Cruz, José Magalhães; Cruz, Tiago; Abreu, Pedro Henriques; (2020). Adversarial Machine Learning applied to Intrusion and Malware Scenarios: a systematic review. IEEE Access, 8, 35403-35419. IEEE. |
| Mateless, Roni; Rejabek, Daniel; Margalit, Oded; Moskovitch, Robert; (2020). Decompiled APK based malicious code classification. Future Generation Computer Systems. Elsevier. |
| Mehtab, Anam; Shahid, Waleed Bin; Yaqoob, Tahreem; Amjad, Muhammad Faisal; Abbas, Haider; Afzal, Hammad; Saqib, Malik Najmus; (2020). AdDroid: rule-based machine learning framework for android malware analysis. Mobile Networks and Applications, 25(1), 180-192. Springer. |
| Mosli, Rayan; (2020). Crafting Adversarial Examples using Particle Swarm Optimization. |
| Nassiri, Mohammad; HaddadPajouh, Hamed; Dehghantanha, Ali; Karimipour, Hadis; Parizi, Reza M; Srivastava, Gautam; (2020). Malware Elimination Impact on Dynamic Analysis: An Experimental Machine Learning Approach. Handbook of Big Data Privacy, 359-370. Springer. |
| Ngo, Quoc-Dung; Nguyen, Huy-Trung; Nguyen, Le-Cuong; Nguyen, Doan-Hieu; (2020). A survey of IoT malware and detection methods based on static features. ICT Express. Elsevier. |
| Nguyen, Huy-Trung; Ngo, Quoc-Dung; Nguyen, Doan-Hieu; Le, Van-Hoang; (2020). PSI-rooted subgraph: A novel feature for IoT botnet detection using classifier algorithms. ICT Express. Elsevier. |
| Nisha, OS Jannath; Bhanu, S Mary Saira; (2020). Detection of malware applications using social spider algorithm in mobile cloud computing environment. International Journal of Ad Hoc and Ubiquitous Computing, 34(3), 154-169. Inderscience Publishers (IEL). |
| Niu, Weina; Cao, Rong; Zhang, Xiaosong; Ding, Kangyi; Zhang, Kaimeng; Li, Ting; (2020). OpCode-Level Function Call Graph Based Android Malware Classification Using Deep Learning. Sensors, 20(13), 3645. Multidisciplinary Digital Publishing Institute. |
| Niveditha, VR; Ananthan, TV; Amudha, S; Sam, Dahlia; Srinidhi, S; (2020). Detect and classify zero day Malware efficiently in big data platform. International Journal of Advanced Science and Technology, 29(4s), 1947-1954 |
| Olukoya, Oluwafemi; Mackenzie, Lewis; Omoronyia, Inah; (2020). Towards using unstructured user input request for malware detection. Computers & Security, 101783. Elsevier. |
| Olukoya, Oluwafemi; Mackenzie, Lewis; Omoronyia, Inah; (2020). Security-oriented view of app behaviour using textual descriptions and user-granted permission requests. Computers & Security, 89, 101685. Elsevier. |
| PEYNİRCİ, Gökçer; EMİNAĞAOĞLU, Mete; (2020). Android Platformunda Kötücül Yazılım Tespiti: Literatür İncelemesi.. International Journal of InformaticsTechnologies, 13(1) |
| Pan, Ya; Ge, Xiuting; Fang, Chunrong; Fan, Yong; (2020). A Systematic Literature Review of Android Malware Detection Using Static Analysis. IEEE Access, 8, 116363-116379. IEEE. |
| Patil, Rajendra; Dudeja, Harsha; Modi, Chirag; (2020). Designing in-VM-assisted lightweight agent-based malware detection framework for securing virtual machines in cloud computing. International Journal of Information Security, 19(2), 147-162. Springer. |
| Raff, Edward; Nicholas, Charles; (2020). A Survey of Machine Learning Methods and Challenges for Windows Malware Classification. arXiv preprint arXiv:2006.09271 |
| Raff, Edward; Nicholas, Charles; McLean, Mark; (2020). A New Burrows Wheeler Transform Markov Distance.. AAAI, 5444-5453 |
| Rahul; Kedia, Priyansh; Sarangi, Subrat; Monika; (2020). Analysis of machine learning models for malware detection. Journal of Discrete Mathematical Sciences and Cryptography, 23(2), 395-407. Taylor & Francis. |
| Rauf, Mohammad Afiq Amirul Abdul; Asraf, Syed Muhammad Hazry; Idrus, Syed Zulkarnain Syed; (2020). Malware Behaviour Analysis and Classification via Windows DLL and System Call. Journal of Physics: Conference Series, 1529(2), 022097. IOP Publishing. |
| Ren, Zhongru; Wu, Haomin; Ning, Qian; Hussain, Iftikhar; Chen, Bingcai; (2020). End-to-end malware detection for android IoT devices using deep learning. Ad Hoc Networks, 101, 102098. Elsevier. |
| Sajid, Md Sajidul Islam; Wei, Jinpeng; Alam, Md Rabbi; Aghaei, Ehsan; Al-Shaer, Ehab; (2020). DodgeTron: Towards Autonomous Cyber Deception Using Dynamic Hybrid Analysis of Malware. |
| Sarker, Iqbal H; Kayes, ASM; Badsha, Shahriar; Alqahtani, Hamed; Watters, Paul; Ng, Alex; (2020). Cybersecurity data science: an overview from machine learning perspective. Journal of Big Data, 7(1), 1-29. Springer. |
| Sayadi, Hossein; Gao, Yifeng; Makrani, Hosein; Sasan, Avesta; Lin, Jessica; Rafatirad, Setareh; Homayoun, Houman; (2020). Towards Run-Time Hardware-Assisted Stealthy Malware Detection. |
| Shalabi, Eman; Moustafa, Ahmed; Khedr, Walid; (2020). On Malware Detection on Android Smartphones. |
| Sharma, Shweta; Kumar, Naveen; Kumar, Rakesh; Krishna, C Rama; (2020). The Paradox of Choice: Investigating Selection Strategies for Android Malware Datasets Using a Machine-learning Approach. Communications of the Association for Information Systems, 46(1), 26 |
| Sharmeen, Shaila; Huda, Shamsul; Abawajy, Jemal; Hassan, Mohammad Mehedi; (2020). An adaptive framework against android privilege escalation threats using deep learning and semi-supervised approaches. Applied Soft Computing, 89, 106089. Elsevier. |
| Shaukat, Kamran; Luo, Suhuai; Varadharajan, Vijay; Hameed, Ibrahim A; Chen, Shan; Liu, Dongxi; Li, Jiaming; (2020). Performance Comparison and Current Challenges of Using Machine Learning Techniques in Cybersecurity. Energies, 13(10), 2509. Multidisciplinary Digital Publishing Institute. |
| Shobana, M; Poonkuzhali, S; (2020). A novel approach to detect IoT malware by system calls using Deep learning techniques. 2020 International Conference on Innovative Trends in Information Technology (ICITIIT), 1-5. IEEE. |
| Singh, Jagsir; Singh, Jaswinder; (2020). Assessment of supervised machine learning algorithms using dynamic API calls for malware detection. International Journal of Computers and Applications, 1-8. Taylor & Francis. |
| Singh, Jagsir; Singh, Jaswinder; (2020). Detection of malicious software by analyzing the behavioral artifacts using machine learning algorithms. Information and Software Technology, 121, 106273. Elsevier. |
| Smith, Michael R; Johnson, Nicholas T; Ingram, Joe B; Carbajal, Armida J; Ramyaa, Ramyaa; Domschot, Evelyn; Lamb, Christopher C; Verzi, Stephen J; Kegelmeyer, W Philip; (2020). Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Information Security. arXiv preprint arXiv:2005.01800 |
| Suaboot, Jakapan; Tari, Zahir; Mahmood, Abdun; Zomaya, Albert Y; Li, Wei; (2020). Sub-curve HMM: A malware detection approach based on partial analysis of API call sequences. Computers & Security, 92, 101773. Elsevier. |
| Sun, Ruimin; Botacin, Marcus; Sapountzis, Nikolaos; Yuan, Xiaoyong; Bishop, Matt; Porter, Donald E; Li, Xiaolin; Gregio, Andre; Oliveira, Daniela; (2020). A Praise for Defensive Programming: LeveragingUncertainty for Effective Malware Mitigation. IEEE Transactions on Dependable and Secure Computing. IEEE. |
| Surendran, Roopak; Thomas, Tony; Emmanuel, Sabu; (2020). A TAN based hybrid model for android malware detection. Journal of Information Security and Applications, 54, 102483. Elsevier. |
| Tanana, Dmitry; (2020). Behavior-Based Detection of Cryptojacking Malware. 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT), 0543-0545. IEEE. |
| Tang, Ying; (2020). Beyond EM: A faster Bayesian linear regression algorithm without matrix inversions. Neurocomputing, 378, 435-440. Elsevier. |
| Tang, Zhijie; Wang, Peng; Wang, Junfeng; (2020). ConvProtoNet: Deep Prototype Induction towards Better Class Representation for Few-Shot Malware Classification. Applied Sciences, 10(8), 2847. Multidisciplinary Digital Publishing Institute. |
| Tanuwidjaja, Harry Chandra; Kim, Kwangjo; (2020). Enhancing Malware Detection by Modified Deep Abstraction and Weighted Feature Selection. |
| Thomas, Tony; Vijayaraghavan, Athira P; Emmanuel, Sabu; (2020). Adversarial Machine Learning in Cybersecurity. Machine Learning Approaches in Cyber Security Analytics, 185-200. Springer. |
| Threats, Resizing; (2020). Lehrstuhl für Sicherheit in der Informatik. . Universität München. |
| Tian, Ke; Tan, Gang; Ryder, Barbara G; Yao, Danfeng Daphne; (2020). Prioritizing data flows and sinks for app security transformation. Computers & Security, 92, 101750. Elsevier. |
| Torabi, Sadegh; Bou-Harb, Elias; Assi, Chadi; Karbab, ElMouatez Billah; Boukhtouta, Amine; Debbabi, Mourad; (2020). Inferring and Investigating IoT-Generated Scanning Campaigns Targeting A Large Network Telescope. IEEE Transactions on Dependable and Secure Computing. IEEE. |
| Tran, Nghi Phu; Nguyen, Dai Tho; Le, Huy Hoang; Nguyen, Ngoc Toan; Nguyen, Ngoc Binh; (2020). An Efficient Algorithm to Extract Control Flow-based Features for IoT Malware Detection. The Computer Journal. Oxford University Press. |
| Vasan, Danish; Alazab, Mamoun; Wassan, Sobia; Safaei, Babak; Zheng, Qin; (2020). Image-based malware classification using ensemble of CNN architectures (IMCEC). Computers & Security, 101748. Elsevier. |
| Wadkar, Mayuri; Di Troia, Fabio; Stamp, Mark; (2020). Detecting malware evolution using support vector machines. Expert Systems with Applications, 143, 113022. Elsevier. |
| Wang, Fangwei; Yang, Shaojie; Li, Qingru; Wang, Changguan; (2020). An internet of things malware classification method based on mixture of experts neural network. Transactions on Emerging Telecommunications Technologies. Wiley Online Library. |
| Wang, Guangyu; Liu, Zhijing; (2020). Android malware detection model based on lightgbm. Recent Trends in Intelligent Computing, Communication and Devices, 237-243. Springer. |
| Wang, Qi; Hassan, Wajih Ul; Li, Ding; Jee, Kangkook; Yu, Xiao; Zou, Kexuan; Rhee, Junghwan; Chen, Zhengzhang; Cheng, Wei; Gunter, C; (2020). You are what you do: Hunting stealthy malware via data provenance analysis. Symposium on Network and Distributed System Security (NDSS) |
| Wang, Shanshan; Chen, Zhenxiang; Yan, Qiben; Ji, Ke; Peng, Lizhi; Yang, Bo; Conti, Mauro; (2020). Deep and broad URL feature mining for android malware detection. Information Sciences, 513, 600-613. Elsevier. |
| Wang, Xiruo; Miikkulainen, Risto; (2020). MDEA: Malware Detection with Evolutionary Adversarial Learning. arXiv preprint arXiv:2002.03331 |
| Wilkins, Zachary; Zincir, Ibrahim; Zincir-Heywood, Nur; (2020). Exploring an artificial arms race for malware detection. Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, 1537-1545 |
| Wu, Peng; Liu, Dong; Wang, Junfeng; Yuan, Baoguo; Kuang, Wenyuan; (2020). Detection of fake IoT app based on multi-dimensional similarity. IEEE Internet of Things Journal. IEEE. |
| Xiao, Jianmao; Chen, Shizhan; He, Qiang; Feng, Zhiyong; Xue, Xiao; (2020). An Android application risk evaluation framework based on minimum permission set identification. Journal of Systems and Software, 163, 110533. Elsevier. |
| Xu, Jiayun; Li, Yingjiu; Deng, Robert; Xu, Ke; (2020). SDAC: A Slow-Aging Solution for Android Malware Detection Using Semantic Distance Based API Clustering. IEEE Transactions on Dependable and Secure Computing. IEEE. |
| Zhang, Jian; Gao, Cheng; Gong, Liangyi; Gu, Zhaojun; Man, Dapeng; Yang, Wu; Li, Wenzhen; (2020). Malware Detection Based on Multi-level and Dynamic Multi-feature Using Ensemble Learning at Hypervisor. Mobile Networks and Applications, 1-18. Springer. |
| Zhu, Dali; Xi, Tong; Jing, Pengfei; Xia, Qing; Wu, Di; Zhang, Yiming; (2020). Sadroid: A Deep Classification Model For Android Malware Detection Based On Semantic Analysis. 2020 IEEE Wireless Communications and Networking Conference (WCNC), 1-7. IEEE. |
| Zhu, Huijuan; Li, Yang; Li, Ruidong; Li, Jianqiang; You, Zhu-Hong; Song, Houbing; (2020). SEDMDroid: An enhanced stacking ensemble of deep learning framework for Android malware detection. IEEE Transactions on Network Science and Engineering. IEEE. |
| Zuhair, Hiba; Selamat, Ali; Krejcar, Ondrej; (2020). A Multi-Tier Streaming Analytics Model of 0-Day Ransomware Detection Using Machine Learning. Applied Sciences, 10(9), 3210. Multidisciplinary Digital Publishing Institute. |
| Ädel, Lukas; Eliasson, Oskar; (2020). The Development and Effectiveness of Malware Vaccination: An Experiment. |
| Čeponis, Dainius; Goranin, Nikolaj; (2020). Investigation of Dual-Flow Deep Learning Models LSTM-FCN and GRU-FCN Efficiency against Single-Flow CNN Models for the Host-Based Intrusion and Malware Detection Task on Univariate Times Series Data. Applied Sciences, 10(7), 2373. Multidisciplinary Digital Publishing Institute. |
| 이윤석; (2020). 파일 접근 행태의 LSTM 학습을 활용한 악성 코드 탐지 기법. 한국정보기술학회논문지, 18(2), 25-32 |
| • 2019 • |
| Abdessadki, Imad; Lazaar, Saiida; (2019). New Classification Based Model for Malicious PE Files Detection.. International Journal of Computer Network & Information Security, 11(6) |
| Ahlgren, Filip; (2019). Local And Network Ransomware Detection Comparison. |
| Akbanov, Maxat; Vassilakis, Vassilios G; Logothetis, Michael D; (2019). WannaCry ransomware: Analysis of infection, persistence, recovery prevention and propagation mechanisms. Journal of Telecommunications and Information Technology |
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| • 2015 • |
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| • 2014 • |
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| 武田圭史; 露木航平; (2014). 実行ファイルのプロファイリングによる調査対象ファイル特定手法の提案. コンピュータセキュリティシンポジウム 2014 論文集, 2014(2), 519-526 |
| 赵毅; 龚俭; 杨望; (2014). 恶意代码自动分析系统的研究. Journal on Communications |
| 윤재성; 장재욱; 김휘강; (2014). 행위기반의 프로파일링 기법을 활용한 모바일 악성코드 분류 기법. 정보보호학회논문지, 24(1), 145-154 |
| • 2013 • |
| CERTH, Lead Beneficiary; PU, ITI Dissemination Level; (2013). Enhanced Network Security for Seamless Service Provisioning in the Smart Mobile Ecosystem. |
| Dolmans, Ralph; Katz, Wouter; (2013). RP1: Carberp Malware analysis. |
| Guri, Mordehai; Kedma, Gabi; Sela, Tom; Carmeli, Buky; Rosner, Amit; Elovici, Yuval; (2013). Noninvasive detection of anti-forensic malware. 2013 8th International Conference on Malicious and Unwanted Software:" The Americas"(MALWARE), 1-10. IEEE. |
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| Oktavianto, Digit; Muhardianto, Iqbal; (2013). Cuckoo malware analysis. . Packt Publishing Ltd. |
| Pareek, Himanshu; Eswari, PRL; Babu, N Sarat Chandra; (2013). Malicious PDF document detection based on feature extraction and entropy. International Journal Journal of Security, Privacy and Trust Management, 2(5) |
| Pareek, Himanshu; Eswari, PRL; Babu, Sarat Chandra; (2013). APPBACS: AN APPLICATION BEHAVIOR ANALYSIS AND CLASSIFICATION SYSTEM. International Journal of Computer Science & Information Technology, 5(2), 53. Academy & Industry Research Collaboration Center (AIRCC). |
| • 2012 • |
| Kedziora, Michal; Gawin, Paulina; Szczepanik, Michal; Jozwiak, Ireneusz; (2012). Android Malware Detection Using Machine Learning And Reverse Engineering. World Wide Web, 16(1) |