Статті в журналах з теми "IOT BOTNET DETECTION"
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Sreeja, B. P. "Survey on Internet of Things Botnet Detection Methodologies: A Report." IRO Journal on Sustainable Wireless Systems 4, no. 3 (September 15, 2022): 185–95. http://dx.doi.org/10.36548/jsws.2022.3.005.
Повний текст джерелаWazzan, Majda, Daniyal Algazzawi, Omaima Bamasaq, Aiiad Albeshri, and Li Cheng. "Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research." Applied Sciences 11, no. 12 (June 20, 2021): 5713. http://dx.doi.org/10.3390/app11125713.
Повний текст джерелаYang, Changjin, Weili Guan, and Zhijie Fang. "IoT Botnet Attack Detection Model Based on DBO-Catboost." Applied Sciences 13, no. 12 (June 15, 2023): 7169. http://dx.doi.org/10.3390/app13127169.
Повний текст джерелаJovanović, Đorđe, and Pavle Vuletić. "Analysis and characterization of IoT malware command and control communication." Telfor Journal 12, no. 2 (2020): 80–85. http://dx.doi.org/10.5937/telfor2002080j.
Повний текст джерелаWazzan, Majda, Daniyal Algazzawi, Aiiad Albeshri, Syed Hasan, Osama Rabie, and Muhammad Zubair Asghar. "Cross Deep Learning Method for Effectively Detecting the Propagation of IoT Botnet." Sensors 22, no. 10 (May 20, 2022): 3895. http://dx.doi.org/10.3390/s22103895.
Повний текст джерелаNegera, Worku Gachena, Friedhelm Schwenker, Taye Girma Debelee, Henock Mulugeta Melaku, and Yehualashet Megeresa Ayano. "Review of Botnet Attack Detection in SDN-Enabled IoT Using Machine Learning." Sensors 22, no. 24 (December 14, 2022): 9837. http://dx.doi.org/10.3390/s22249837.
Повний текст джерелаHaq, Mohd Anul. "DBoTPM: A Deep Neural Network-Based Botnet Prediction Model." Electronics 12, no. 5 (February 27, 2023): 1159. http://dx.doi.org/10.3390/electronics12051159.
Повний текст джерелаAkash, Nazmus Sakib, Shakir Rouf, Sigma Jahan, Amlan Chowdhury, and Jia Uddin. "Botnet Detection in IoT Devices Using Random Forest Classifier with Independent Component Analysis." Journal of Information and Communication Technology 21, No.2 (April 7, 2022): 201–32. http://dx.doi.org/10.32890/jict2022.21.2.3.
Повний текст джерелаAl-Duwairi, Basheer, Wafaa Al-Kahla, Mhd Ammar AlRefai, Yazid Abedalqader, Abdullah Rawash, and Rana Fahmawi. "SIEM-based detection and mitigation of IoT-botnet DDoS attacks." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (April 1, 2020): 2182. http://dx.doi.org/10.11591/ijece.v10i2.pp2182-2191.
Повний текст джерелаAlharbi, Abdullah, Wael Alosaimi, Hashem Alyami, Hafiz Tayyab Rauf, and Robertas Damaševičius. "Botnet Attack Detection Using Local Global Best Bat Algorithm for Industrial Internet of Things." Electronics 10, no. 11 (June 3, 2021): 1341. http://dx.doi.org/10.3390/electronics10111341.
Повний текст джерелаKaushik, Dr Priyanka. "Unleashing the Power of Multi-Agent Deep Learning: Cyber-Attack Detection in IoT." International Journal for Global Academic & Scientific Research 2, no. 2 (June 30, 2023): 23–45. http://dx.doi.org/10.55938/ijgasr.v2i2.46.
Повний текст джерелаRezaei, Amirhossein. "Identifying Botnet on IoT by Using Supervised Learning Techniques." Oriental journal of computer science and technology 12, no. 4 (October 28, 2019): 185–93. http://dx.doi.org/10.13005/ojcst12.04.04.
Повний текст джерелаAbu Al-Haija, Qasem, and Mu’awya Al-Dala’ien. "ELBA-IoT: An Ensemble Learning Model for Botnet Attack Detection in IoT Networks." Journal of Sensor and Actuator Networks 11, no. 1 (March 9, 2022): 18. http://dx.doi.org/10.3390/jsan11010018.
Повний текст джерелаAlmseidin, Mohammad, and Mouhammd Alkasassbeh. "An Accurate Detection Approach for IoT Botnet Attacks Using Interpolation Reasoning Method." Information 13, no. 6 (June 14, 2022): 300. http://dx.doi.org/10.3390/info13060300.
Повний текст джерелаBagui, Sikha, Xiaojian Wang, and Subhash Bagui. "Machine Learning Based Intrusion Detection for IoT Botnet." International Journal of Machine Learning and Computing 11, no. 6 (November 2021): 399–406. http://dx.doi.org/10.18178/ijmlc.2021.11.6.1068.
Повний текст джерелаS. Alrayes, Fatma, Mohammed Maray, Abdulbaset Gaddah, Ayman Yafoz, Raed Alsini, Omar Alghushairy, Heba Mohsen, and Abdelwahed Motwakel. "Modeling of Botnet Detection Using Barnacles Mating Optimizer with Machine Learning Model for Internet of Things Environment." Electronics 11, no. 20 (October 21, 2022): 3411. http://dx.doi.org/10.3390/electronics11203411.
Повний текст джерелаAlqahtani, Mnahi, Hassan Mathkour, and Mohamed Maher Ben Ismail. "IoT Botnet Attack Detection Based on Optimized Extreme Gradient Boosting and Feature Selection." Sensors 20, no. 21 (November 6, 2020): 6336. http://dx.doi.org/10.3390/s20216336.
Повний текст джерелаAlkahtani, Hasan, and Theyazn H. H. Aldhyani. "Botnet Attack Detection by Using CNN-LSTM Model for Internet of Things Applications." Security and Communication Networks 2021 (September 9, 2021): 1–23. http://dx.doi.org/10.1155/2021/3806459.
Повний текст джерелаSoe, Yan Naung, Yaokai Feng, Paulus Insap Santosa, Rudy Hartanto, and Kouichi Sakurai. "Machine Learning-Based IoT-Botnet Attack Detection with Sequential Architecture." Sensors 20, no. 16 (August 5, 2020): 4372. http://dx.doi.org/10.3390/s20164372.
Повний текст джерелаNafir, Abdenacer, Smaine Mazouzi, and Salim Chikhi. "Collaborative Life-Cycle-Based Botnet Detection in IoT Using Event Entropy." International Journal of Organizational and Collective Intelligence 10, no. 4 (October 2020): 19–34. http://dx.doi.org/10.4018/ijoci.2020100102.
Повний текст джерелаSajjad, Syed Muhammad, Muhammad Rafiq Mufti, Muhammad Yousaf, Waqar Aslam, Reem Alshahrani, Nadhem Nemri, Humaira Afzal, Muhammad Asghar Khan, and Chien-Ming Chen. "Detection and Blockchain-Based Collaborative Mitigation of Internet of Things Botnets." Wireless Communications and Mobile Computing 2022 (April 20, 2022): 1–26. http://dx.doi.org/10.1155/2022/1194899.
Повний текст джерелаAlissa, Khalid, Tahir Alyas, Kashif Zafar, Qaiser Abbas, Nadia Tabassum, and Shadman Sakib. "Botnet Attack Detection in IoT Using Machine Learning." Computational Intelligence and Neuroscience 2022 (October 4, 2022): 1–14. http://dx.doi.org/10.1155/2022/4515642.
Повний текст джерелаAfrifa, Stephen, Vijayakumar Varadarajan, Peter Appiahene, Tao Zhang, and Emmanuel Adjei Domfeh. "Ensemble Machine Learning Techniques for Accurate and Efficient Detection of Botnet Attacks in Connected Computers." Eng 4, no. 1 (February 16, 2023): 650–64. http://dx.doi.org/10.3390/eng4010039.
Повний текст джерелаHussain, Zeeshan, Adnan Akhunzada, Javed Iqbal, Iram Bibi, and Abdullah Gani. "Secure IIoT-Enabled Industry 4.0." Sustainability 13, no. 22 (November 10, 2021): 12384. http://dx.doi.org/10.3390/su132212384.
Повний текст джерелаM. Ali Alheeti, Khattab, Ibrahim Alsukayti, and Mohammed Alreshoodi. "Intelligent Botnet Detection Approach in Modern Applications." International Journal of Interactive Mobile Technologies (iJIM) 15, no. 16 (August 23, 2021): 113. http://dx.doi.org/10.3991/ijim.v15i16.24199.
Повний текст джерелаAl-Sarem, Mohammed, Faisal Saeed, Eman H. Alkhammash, and Norah Saleh Alghamdi. "An Aggregated Mutual Information Based Feature Selection with Machine Learning Methods for Enhancing IoT Botnet Attack Detection." Sensors 22, no. 1 (December 28, 2021): 185. http://dx.doi.org/10.3390/s22010185.
Повний текст джерелаShao, Zhou, Sha Yuan, and Yongli Wang. "Adaptive online learning for IoT botnet detection." Information Sciences 574 (October 2021): 84–95. http://dx.doi.org/10.1016/j.ins.2021.05.076.
Повний текст джерелаJung, Woosub, Hongyang Zhao, Minglong Sun, and Gang Zhou. "IoT botnet detection via power consumption modeling." Smart Health 15 (March 2020): 100103. http://dx.doi.org/10.1016/j.smhl.2019.100103.
Повний текст джерелаTatarnikova, T. M., I. A. Sikarev, P. Yu Bogdanov, and T. V. Timochkina. "Botnet Attack Detection Approach in IoT Networks." Automatic Control and Computer Sciences 56, no. 8 (December 2022): 838–46. http://dx.doi.org/10.3103/s0146411622080259.
Повний текст джерелаKim, Jiyeon, Minsun Shim, Seungah Hong, Yulim Shin, and Eunjung Choi. "Intelligent Detection of IoT Botnets Using Machine Learning and Deep Learning." Applied Sciences 10, no. 19 (October 8, 2020): 7009. http://dx.doi.org/10.3390/app10197009.
Повний текст джерелаApostol, Ioana, Marius Preda, Constantin Nila, and Ion Bica. "IoT Botnet Anomaly Detection Using Unsupervised Deep Learning." Electronics 10, no. 16 (August 4, 2021): 1876. http://dx.doi.org/10.3390/electronics10161876.
Повний текст джерелаLee, Seungjin, Azween Abdullah, Nz Jhanjhi, and Sh Kok. "Classification of botnet attacks in IoT smart factory using honeypot combined with machine learning." PeerJ Computer Science 7 (January 25, 2021): e350. http://dx.doi.org/10.7717/peerj-cs.350.
Повний текст джерелаMalik, Kainat, Faisal Rehman, Tahir Maqsood, Saad Mustafa, Osman Khalid, and Adnan Akhunzada. "Lightweight Internet of Things Botnet Detection Using One-Class Classification." Sensors 22, no. 10 (May 10, 2022): 3646. http://dx.doi.org/10.3390/s22103646.
Повний текст джерелаAlothman, Zainab, Mouhammd Alkasassbeh, and Sherenaz Al-Haj Baddar. "An efficient approach to detect IoT botnet attacks using machine learning." Journal of High Speed Networks 26, no. 3 (November 27, 2020): 241–54. http://dx.doi.org/10.3233/jhs-200641.
Повний текст джерелаSwathi, G. Chandana, G. Kishor Kumar, and A. P. Siva Kumar. "Central Pivot Heuristics for Botnet Attack Defense in Iot." International Journal on Recent and Innovation Trends in Computing and Communication 10, no. 10 (October 31, 2022): 78–90. http://dx.doi.org/10.17762/ijritcc.v10i10.5738.
Повний текст джерелаLee, Seungjin, Azween Abdullah, N. Z. Jhanjhi, and S. H. Kok. "Honeypot Coupled Machine Learning Model for Botnet Detection and Classification in IoT Smart Factory – An Investigation." MATEC Web of Conferences 335 (2021): 04003. http://dx.doi.org/10.1051/matecconf/202133504003.
Повний текст джерелаAlzahrani, Rami J., and Ahmed Alzahrani. "A Novel Multi Algorithm Approach to Identify Network Anomalies in the IoT Using Fog Computing and a Model to Distinguish between IoT and Non-IoT Devices." Journal of Sensor and Actuator Networks 12, no. 2 (February 28, 2023): 19. http://dx.doi.org/10.3390/jsan12020019.
Повний текст джерелаAl-Kasassbeh, Mouhammd, Mohammad Almseidin, Khaled Alrfou, and Szilveszter Kovacs. "Detection of IoT-botnet attacks using fuzzy rule interpolation." Journal of Intelligent & Fuzzy Systems 39, no. 1 (July 17, 2020): 421–31. http://dx.doi.org/10.3233/jifs-191432.
Повний текст джерелаNguyen, Giang L., Braulio Dumba, Quoc-Dung Ngo, Hai-Viet Le, and Tu N. Nguyen. "A collaborative approach to early detection of IoT Botnet." Computers & Electrical Engineering 97 (January 2022): 107525. http://dx.doi.org/10.1016/j.compeleceng.2021.107525.
Повний текст джерелаNguyen, Huy-Trung, Quoc-Dung Ngo, and Van-Hoang Le. "A novel graph-based approach for IoT botnet detection." International Journal of Information Security 19, no. 5 (October 23, 2019): 567–77. http://dx.doi.org/10.1007/s10207-019-00475-6.
Повний текст джерелаAbu Khurma, Ruba, Iman Almomani, and Ibrahim Aljarah. "IoT Botnet Detection Using Salp Swarm and Ant Lion Hybrid Optimization Model." Symmetry 13, no. 8 (July 28, 2021): 1377. http://dx.doi.org/10.3390/sym13081377.
Повний текст джерелаde Caldas Filho, Francisco Lopes, Samuel Carlos Meneses Soares, Elder Oroski, Robson de Oliveira Albuquerque, Rafael Zerbini Alves da Mata, Fábio Lúcio Lopes de Mendonça, and Rafael Timóteo de Sousa Júnior. "Botnet Detection and Mitigation Model for IoT Networks Using Federated Learning." Sensors 23, no. 14 (July 11, 2023): 6305. http://dx.doi.org/10.3390/s23146305.
Повний текст джерелаCatillo, Marta, Antonio Pecchia, and Umberto Villano. "A Deep Learning Method for Lightweight and Cross-Device IoT Botnet Detection." Applied Sciences 13, no. 2 (January 7, 2023): 837. http://dx.doi.org/10.3390/app13020837.
Повний текст джерелаFaysal, Jabed Al, Sk Tahmid Mostafa, Jannatul Sultana Tamanna, Khondoker Mirazul Mumenin, Md Mashrur Arifin, Md Abdul Awal, Atanu Shome, and Sheikh Shanawaz Mostafa. "XGB-RF: A Hybrid Machine Learning Approach for IoT Intrusion Detection." Telecom 3, no. 1 (January 4, 2022): 52–69. http://dx.doi.org/10.3390/telecom3010003.
Повний текст джерелаMyridakis, Dimitrios, Stefanos Papafotikas, Konstantinos Kalovrektis, and Athanasios Kakarountas. "Enhancing Security on IoT Devices via Machine Learning on Conditional Power Dissipation." Electronics 9, no. 11 (October 29, 2020): 1799. http://dx.doi.org/10.3390/electronics9111799.
Повний текст джерелаAL-Akhras, Mousa, Abdulmajeed Alshunaybir, Hani Omar, and Samah Alhazmi. "Botnet attacks detection in IoT environment using machine learning techniques." International Journal of Data and Network Science 7, no. 4 (2023): 1683–706. http://dx.doi.org/10.5267/j.ijdns.2023.7.021.
Повний текст джерелаKerrakchou, Imane, Adil Abou El Hassan, Sara Chadli, Mohamed Emharraf, and Mohammed Saber. "Selection of efficient machine learning algorithm on Bot-IoT dataset for intrusion detection in internet of things networks." Indonesian Journal of Electrical Engineering and Computer Science 31, no. 3 (September 1, 2023): 1784. http://dx.doi.org/10.11591/ijeecs.v31.i3.pp1784-1793.
Повний текст джерелаTrajanovski, Tolijan, and Ning Zhang. "An Automated and Comprehensive Framework for IoT Botnet Detection and Analysis (IoT-BDA)." IEEE Access 9 (2021): 124360–83. http://dx.doi.org/10.1109/access.2021.3110188.
Повний текст джерелаPopoola, Segun I., Bamidele Adebisi, Ruth Ande, Mohammad Hammoudeh, Kelvin Anoh, and Aderemi A. Atayero. "SMOTE-DRNN: A Deep Learning Algorithm for Botnet Detection in the Internet-of-Things Networks." Sensors 21, no. 9 (April 24, 2021): 2985. http://dx.doi.org/10.3390/s21092985.
Повний текст джерелаNegera, Worku Gachena, Friedhelm Schwenker, Taye Girma Debelee, Henock Mulugeta Melaku, and Degaga Wolde Feyisa. "Lightweight Model for Botnet Attack Detection in Software Defined Network-Orchestrated IoT." Applied Sciences 13, no. 8 (April 7, 2023): 4699. http://dx.doi.org/10.3390/app13084699.
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