Zeitschriftenartikel zum Thema „Security attacks detection“
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Jimmy, FNU. „Cyber security Vulnerabilities and Remediation Through Cloud Security Tools“. Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 3, Nr. 1 (12.04.2024): 196–233. http://dx.doi.org/10.60087/jaigs.vol03.issue01.p233.
Der volle Inhalt der QuelleJimmy, Fnu. „Cyber security Vulnerabilities and Remediation Through Cloud Security Tools“. Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 3, Nr. 1 (12.04.2024): 196–233. http://dx.doi.org/10.60087/jaigs.vol03.issue01.p234.
Der volle Inhalt der QuelleKumavat, Kavita S., und Joanne Gomes. „Common Mechanism for Detecting Multiple DDoS Attacks“. International Journal on Recent and Innovation Trends in Computing and Communication 11, Nr. 4 (04.05.2023): 81–90. http://dx.doi.org/10.17762/ijritcc.v11i4.6390.
Der volle Inhalt der QuelleKareem, Mohammed Ibrahim, Mohammad Jawad Kadhim Abood und Karrar Ibrahim. „Machine learning-based PortScan attacks detection using OneR classifier“. Bulletin of Electrical Engineering and Informatics 12, Nr. 6 (01.12.2023): 3690–96. http://dx.doi.org/10.11591/eei.v12i6.4142.
Der volle Inhalt der QuelleDu, Dajun, Rui Chen, Xue Li, Lei Wu, Peng Zhou und Minrui Fei. „Malicious data deception attacks against power systems: A new case and its detection method“. Transactions of the Institute of Measurement and Control 41, Nr. 6 (08.01.2018): 1590–99. http://dx.doi.org/10.1177/0142331217740622.
Der volle Inhalt der QuelleKumar, Sunil, und Maninder Singh. „Detection and Isolation of Zombie Attack under Cloud Environment“. Oriental journal of computer science and technology 10, Nr. 2 (12.04.2017): 338–44. http://dx.doi.org/10.13005/ojcst/10.02.12.
Der volle Inhalt der QuelleFarane Shradha, Gotane Rutuja, Chandanshive Sakshi, Agrawal Khushi und Khandekar Srushti. „Detection of cyber-attacks and network attacks using Machine Learning“. World Journal of Advanced Engineering Technology and Sciences 12, Nr. 1 (30.05.2024): 128–32. http://dx.doi.org/10.30574/wjaets.2024.12.1.0184.
Der volle Inhalt der QuelleAslan, Ömer, Semih Serkant Aktuğ, Merve Ozkan-Okay, Abdullah Asim Yilmaz und Erdal Akin. „A Comprehensive Review of Cyber Security Vulnerabilities, Threats, Attacks, and Solutions“. Electronics 12, Nr. 6 (11.03.2023): 1333. http://dx.doi.org/10.3390/electronics12061333.
Der volle Inhalt der QuelleAlamsyah, Hendri, Riska und Abdussalam Al Akbar. „Analisa Keamanan Jaringan Menggunakan Network Intrusion Detection and Prevention System“. JOINTECS (Journal of Information Technology and Computer Science) 5, Nr. 1 (25.01.2020): 17. http://dx.doi.org/10.31328/jointecs.v5i1.1240.
Der volle Inhalt der QuelleSalih, Azar Abid, und Maiwan Bahjat Abdulrazzaq. „Cyber security: performance analysis and challenges for cyber attacks detection“. Indonesian Journal of Electrical Engineering and Computer Science 31, Nr. 3 (01.09.2023): 1763. http://dx.doi.org/10.11591/ijeecs.v31.i3.pp1763-1775.
Der volle Inhalt der QuelleNeelaveni, Dr R., Abhinav . und Sahas . „Analysis of Efficient Intrusion Detection System using Ensemble Learning“. International Journal for Research in Applied Science and Engineering Technology 11, Nr. 5 (31.05.2023): 1521–30. http://dx.doi.org/10.22214/ijraset.2023.51858.
Der volle Inhalt der QuelleSheikh, Zakir Ahmad, Yashwant Singh, Pradeep Kumar Singh und Paulo J. Sequeira Gonçalves. „Defending the Defender: Adversarial Learning Based Defending Strategy for Learning Based Security Methods in Cyber-Physical Systems (CPS)“. Sensors 23, Nr. 12 (09.06.2023): 5459. http://dx.doi.org/10.3390/s23125459.
Der volle Inhalt der QuelleSoe, Yan Naung, Yaokai Feng, Paulus Insap Santosa, Rudy Hartanto und Kouichi Sakurai. „Machine Learning-Based IoT-Botnet Attack Detection with Sequential Architecture“. Sensors 20, Nr. 16 (05.08.2020): 4372. http://dx.doi.org/10.3390/s20164372.
Der volle Inhalt der QuelleQiu, Ling, und Cai Ming Liu. „An Intelligent Detection Method for Network Security“. Applied Mechanics and Materials 530-531 (Februar 2014): 646–49. http://dx.doi.org/10.4028/www.scientific.net/amm.530-531.646.
Der volle Inhalt der QuelleRohit Khedkar et al. „Detection of Cyber Attacks and Network Attacks Using Machine Learning Algorithms“. Proceeding International Conference on Science and Engineering 11, Nr. 1 (18.02.2023): 241–52. http://dx.doi.org/10.52783/cienceng.v11i1.120.
Der volle Inhalt der QuelleGavrić, Nikola, und Živko Bojović. „Security Concerns in MMO Games—Analysis of a Potent Application Layer DDoS Threat“. Sensors 22, Nr. 20 (14.10.2022): 7791. http://dx.doi.org/10.3390/s22207791.
Der volle Inhalt der QuelleCho, Youngho. „Intelligent On-Off Web Defacement Attacks and Random Monitoring-Based Detection Algorithms“. Electronics 8, Nr. 11 (13.11.2019): 1338. http://dx.doi.org/10.3390/electronics8111338.
Der volle Inhalt der QuellePanduardi, Farizqi, Herman Yuliandoko und Agus Priyo Utomo. „Network Security Using Honeypot and Attack Detection with Android Application“. Indonesian Journal of Engineering Research 2, Nr. 2 (27.11.2021): 53–60. http://dx.doi.org/10.11594/10.11594/ijer.02.02.04.
Der volle Inhalt der QuelleSachdev, Rithik, Shreya Mishra und Shekhar Sharma. „Comparison of Supervised Learning Algorithms for DDOS Attack Detection“. International Journal for Research in Applied Science and Engineering Technology 10, Nr. 8 (31.08.2022): 1766–72. http://dx.doi.org/10.22214/ijraset.2022.46506.
Der volle Inhalt der QuelleVinod Kumar, Boddupally, K. Pranaya Vardhan, Kurceti Subba Rao und Thipparthy Navya Sree. „IDENTIFICATION OF UNSATURATED ATTACKS IN VIRTUALIZED INFRASTRUCTURES WITH BIG DATA ANALYTICS IN CLOUD COMPUTING“. Journal of Nonlinear Analysis and Optimization 14, Nr. 02 (2023): 286–92. http://dx.doi.org/10.36893/jnao.2023.v14i2.286-292.
Der volle Inhalt der QuelleGhugar, Umashankar, Jayaram Pradhan, Sourav Kumar Bhoi und Rashmi Ranjan Sahoo. „LB-IDS: Securing Wireless Sensor Network Using Protocol Layer Trust-Based Intrusion Detection System“. Journal of Computer Networks and Communications 2019 (06.01.2019): 1–13. http://dx.doi.org/10.1155/2019/2054298.
Der volle Inhalt der QuellePatil, Shruti, Vijayakumar Varadarajan, Devika Walimbe, Siddharth Gulechha, Sushant Shenoy, Aditya Raina und Ketan Kotecha. „Improving the Robustness of AI-Based Malware Detection Using Adversarial Machine Learning“. Algorithms 14, Nr. 10 (15.10.2021): 297. http://dx.doi.org/10.3390/a14100297.
Der volle Inhalt der QuelleGupta, Punit, und Pallavi Kaliyar. „History Aware Anomaly Based IDS for Cloud IaaS“. INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 10, Nr. 6 (30.08.2013): 1779–84. http://dx.doi.org/10.24297/ijct.v10i6.3205.
Der volle Inhalt der QuelleRajan, Del. „Entropic DDoS Detection for Quantum Networks“. Quantum Reports 4, Nr. 4 (13.12.2022): 604–15. http://dx.doi.org/10.3390/quantum4040044.
Der volle Inhalt der QuelleAl-Zewairi, Malek, Sufyan Almajali und Moussa Ayyash. „Unknown Security Attack Detection Using Shallow and Deep ANN Classifiers“. Electronics 9, Nr. 12 (26.11.2020): 2006. http://dx.doi.org/10.3390/electronics9122006.
Der volle Inhalt der QuelleFang, Xing, Wenhui Zhang, Jiming Lin und Yuming Liu. „Research on SDN Fingerprint Attack Defense Mechanism Based on Dynamic Disturbance and Information Entropy Detection“. Security and Communication Networks 2022 (13.08.2022): 1–14. http://dx.doi.org/10.1155/2022/1957497.
Der volle Inhalt der QuelleSilva, Rui Filipe, Raul Barbosa und Jorge Bernardino. „Intrusion Detection Systems for Mitigating SQL Injection Attacks“. International Journal of Information Security and Privacy 14, Nr. 2 (April 2020): 20–40. http://dx.doi.org/10.4018/ijisp.2020040102.
Der volle Inhalt der QuelleMuhammad, Hafsat, Olumide B. Longe, Abimbola Baale, und U.-O. Ekpo Antai. „Towards the Development of a Machine Learning Enhanceed Framework for Honeypot and CAPTCHA Intrusion Detection Systems“. Advances in Multidisciplinary and scientific Research Journal Publication 34 (30.12.2022): 43–50. http://dx.doi.org/10.22624/aims/accrabespoke2022/v34p4.
Der volle Inhalt der QuelleO, Belej, Spas N, Artyshchuk I und Fedastsou M. „Construction of a multi-agent attack detection system based on artificial intelligence models“. Artificial Intelligence 26, jai2021.26(1) (30.06.2021): 22–30. http://dx.doi.org/10.15407/jai2021.01.022.
Der volle Inhalt der QuelleHairab, Belal Ibrahim, Heba K. Aslan, Mahmoud Said Elsayed, Anca D. Jurcut und Marianne A. Azer. „Anomaly Detection of Zero-Day Attacks Based on CNN and Regularization Techniques“. Electronics 12, Nr. 3 (23.01.2023): 573. http://dx.doi.org/10.3390/electronics12030573.
Der volle Inhalt der QuelleHaseeb-ur-rehman, Rana M. Abdul, Azana Hafizah Mohd Aman, Mohammad Kamrul Hasan, Khairul Akram Zainol Ariffin, Abdallah Namoun, Ali Tufail und Ki-Hyung Kim. „High-Speed Network DDoS Attack Detection: A Survey“. Sensors 23, Nr. 15 (01.08.2023): 6850. http://dx.doi.org/10.3390/s23156850.
Der volle Inhalt der QuelleTolіupa, Serhii, Oleksandr Pliushch und Ivan Parkhomenko. „CONSTRUCTION OF ATTACK DETECTION SYSTEMS IN INFORMATION NETWORKS ON NEURAL NETWORK STRUCTURES“. Cybersecurity: Education, Science, Technique 2, Nr. 10 (2020): 169–83. http://dx.doi.org/10.28925/2663-4023.2020.10.169183.
Der volle Inhalt der QuelleBdair Alghuraibawi, Adnan Hasan, Rosni Abdullah, Selvakumar Manickam und Zaid Abdi Alkareem Alyasseri. „Detection of ICMPv6-based DDoS attacks using anomaly based intrusion detection system: A comprehensive review“. International Journal of Electrical and Computer Engineering (IJECE) 11, Nr. 6 (01.12.2021): 5216. http://dx.doi.org/10.11591/ijece.v11i6.pp5216-5228.
Der volle Inhalt der QuelleAbuabid, Ali, und Abdulrahman Aldeij. „Cyber Security Incident Response“. Journal of Information Security and Cybercrimes Research 7, Nr. 1 (02.06.2024): 29–50. http://dx.doi.org/10.26735/pnob5534.
Der volle Inhalt der QuelleLin, Hsiao-Chung, Ping Wang und Wen-Hui Lin. „Implementation of a PSO-Based Security Defense Mechanism for Tracing the Sources of DDoS Attacks“. Computers 8, Nr. 4 (04.12.2019): 88. http://dx.doi.org/10.3390/computers8040088.
Der volle Inhalt der QuelleGara, Fatma, Leila Ben Saad und Rahma Ben Ayed. „An Efficient Intrusion Detection System for Selective Forwarding and Clone Attackers in IPv6-based Wireless Sensor Networks under Mobility“. International Journal on Semantic Web and Information Systems 13, Nr. 3 (Juli 2017): 22–47. http://dx.doi.org/10.4018/ijswis.2017070102.
Der volle Inhalt der QuelleYan, Guanghua, Qiang Li, Dong Guo und Bing Li. „AULD: Large Scale Suspicious DNS Activities Detection via Unsupervised Learning in Advanced Persistent Threats“. Sensors 19, Nr. 14 (19.07.2019): 3180. http://dx.doi.org/10.3390/s19143180.
Der volle Inhalt der QuelleXuan, Cho Do, Duc Duong und Hoang Xuan Dau. „A multi-layer approach for advanced persistent threat detection using machine learning based on network traffic“. Journal of Intelligent & Fuzzy Systems 40, Nr. 6 (21.06.2021): 11311–29. http://dx.doi.org/10.3233/jifs-202465.
Der volle Inhalt der QuelleAlashhab, Abdussalam Ahmed, Mohd Soperi Mohd Zahid, Mohamed A. Azim, Muhammad Yunis Daha, Babangida Isyaku und Shimhaz Ali. „A Survey of Low Rate DDoS Detection Techniques Based on Machine Learning in Software-Defined Networks“. Symmetry 14, Nr. 8 (29.07.2022): 1563. http://dx.doi.org/10.3390/sym14081563.
Der volle Inhalt der QuelleShang, Fute, Buhong Wang, Fuhu Yan und Tengyao Li. „Multidevice False Data Injection Attack Models of ADS-B Multilateration Systems“. Security and Communication Networks 2019 (03.03.2019): 1–11. http://dx.doi.org/10.1155/2019/8936784.
Der volle Inhalt der QuelleVermani, Kunal, Amandeep Noliya, Sunil Kumar und Kamlesh Dutta. „Ensemble Learning Based Malicious Node Detection in SDN-Based VANETs“. Journal of Information Systems Engineering and Business Intelligence 9, Nr. 2 (01.11.2023): 136–46. http://dx.doi.org/10.20473/jisebi.9.2.136-146.
Der volle Inhalt der QuelleLiu, Likun, Hongli Zhang, Xiangzhan Yu, Yi Xin, Muhammad Shafiq und Mengmeng Ge. „An Efficient Security System for Mobile Data Monitoring“. Wireless Communications and Mobile Computing 2018 (11.06.2018): 1–10. http://dx.doi.org/10.1155/2018/9809345.
Der volle Inhalt der QuelleDesai, Vinod, und Dinesha Hagare Annappaiah. „Reputation-based Security model for detecting biased attacks in BigData“. Indonesian Journal of Electrical Engineering and Computer Science 29, Nr. 3 (01.03.2023): 1567. http://dx.doi.org/10.11591/ijeecs.v29.i3.pp1567-1576.
Der volle Inhalt der QuelleALAzzawi, Abdulbasit. „SQL Injection Detection Using RNN Deep Learning Model“. Journal of Applied Engineering and Technological Science (JAETS) 5, Nr. 1 (10.12.2023): 531–41. http://dx.doi.org/10.37385/jaets.v5i1.2864.
Der volle Inhalt der QuelleDasari, Kishore Babu, und Nagaraju Devarakonda. „Detection of Different DDoS Attacks Using Machine Learning Classification Algorithms“. Ingénierie des systèmes d information 26, Nr. 5 (31.10.2021): 461–68. http://dx.doi.org/10.18280/isi.260505.
Der volle Inhalt der QuelleAl-Rajeh, Noura S., und Amal A. Al-Shargabi. „Dual Spectral Attention Model for Iris Presentation Attack Detection“. International Journal of Interactive Mobile Technologies (iJIM) 18, Nr. 10 (22.05.2024): 71–89. http://dx.doi.org/10.3991/ijim.v18i10.46981.
Der volle Inhalt der QuelleXia, Kui Liang. „Modeling and Simulation of Low Rate of Denial of Service Attacks“. Applied Mechanics and Materials 484-485 (Januar 2014): 1063–66. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.1063.
Der volle Inhalt der QuelleSkaruz, Jarosław. „Database security: combining neural networks and classification approach“. Studia Informatica, Nr. 23 (22.12.2020): 95–115. http://dx.doi.org/10.34739/si.2019.23.06.
Der volle Inhalt der QuelleKhan, Zulfiqar Ali, und Akbar Siami Namin. „A Survey of DDOS Attack Detection Techniques for IoT Systems Using BlockChain Technology“. Electronics 11, Nr. 23 (24.11.2022): 3892. http://dx.doi.org/10.3390/electronics11233892.
Der volle Inhalt der QuelleBarabanov, Alexander, Denis Dergunov, Denis Makrushin und Aleksey Teplov. „AUTOMATIC DETECTION OF ACCESS CONTROL VULNERABILITIES VIA API SPECIFICATION PROCESSING“. Voprosy kiberbezopasnosti, Nr. 1(47) (2022): 49–65. http://dx.doi.org/10.21681/2311-3456-2022-1-49-65.
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