Artykuły w czasopismach na temat „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.
Pełny tekst źródłaJimmy, 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.
Pełny tekst źródłaKumavat, Kavita S., i Joanne Gomes. "Common Mechanism for Detecting Multiple DDoS Attacks". International Journal on Recent and Innovation Trends in Computing and Communication 11, nr 4 (4.05.2023): 81–90. http://dx.doi.org/10.17762/ijritcc.v11i4.6390.
Pełny tekst źródłaKareem, Mohammed Ibrahim, Mohammad Jawad Kadhim Abood i Karrar Ibrahim. "Machine learning-based PortScan attacks detection using OneR classifier". Bulletin of Electrical Engineering and Informatics 12, nr 6 (1.12.2023): 3690–96. http://dx.doi.org/10.11591/eei.v12i6.4142.
Pełny tekst źródłaDu, Dajun, Rui Chen, Xue Li, Lei Wu, Peng Zhou i 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 (8.01.2018): 1590–99. http://dx.doi.org/10.1177/0142331217740622.
Pełny tekst źródłaKumar, Sunil, i 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.
Pełny tekst źródłaFarane Shradha, Gotane Rutuja, Chandanshive Sakshi, Agrawal Khushi i 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.
Pełny tekst źródłaAslan, Ömer, Semih Serkant Aktuğ, Merve Ozkan-Okay, Abdullah Asim Yilmaz i 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.
Pełny tekst źródłaAlamsyah, Hendri, Riska i 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.
Pełny tekst źródłaSalih, Azar Abid, i Maiwan Bahjat Abdulrazzaq. "Cyber security: performance analysis and challenges for cyber attacks detection". Indonesian Journal of Electrical Engineering and Computer Science 31, nr 3 (1.09.2023): 1763. http://dx.doi.org/10.11591/ijeecs.v31.i3.pp1763-1775.
Pełny tekst źródłaNeelaveni, Dr R., Abhinav . i 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.
Pełny tekst źródłaSheikh, Zakir Ahmad, Yashwant Singh, Pradeep Kumar Singh i 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 (9.06.2023): 5459. http://dx.doi.org/10.3390/s23125459.
Pełny tekst źródłaSoe, Yan Naung, Yaokai Feng, Paulus Insap Santosa, Rudy Hartanto i Kouichi Sakurai. "Machine Learning-Based IoT-Botnet Attack Detection with Sequential Architecture". Sensors 20, nr 16 (5.08.2020): 4372. http://dx.doi.org/10.3390/s20164372.
Pełny tekst źródłaQiu, Ling, i Cai Ming Liu. "An Intelligent Detection Method for Network Security". Applied Mechanics and Materials 530-531 (luty 2014): 646–49. http://dx.doi.org/10.4028/www.scientific.net/amm.530-531.646.
Pełny tekst źródłaRohit 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.
Pełny tekst źródłaGavrić, Nikola, i 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.
Pełny tekst źródłaCho, 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.
Pełny tekst źródłaPanduardi, Farizqi, Herman Yuliandoko i 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.
Pełny tekst źródłaSachdev, Rithik, Shreya Mishra i 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.
Pełny tekst źródłaVinod Kumar, Boddupally, K. Pranaya Vardhan, Kurceti Subba Rao i 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.
Pełny tekst źródłaGhugar, Umashankar, Jayaram Pradhan, Sourav Kumar Bhoi i Rashmi Ranjan Sahoo. "LB-IDS: Securing Wireless Sensor Network Using Protocol Layer Trust-Based Intrusion Detection System". Journal of Computer Networks and Communications 2019 (6.01.2019): 1–13. http://dx.doi.org/10.1155/2019/2054298.
Pełny tekst źródłaPatil, Shruti, Vijayakumar Varadarajan, Devika Walimbe, Siddharth Gulechha, Sushant Shenoy, Aditya Raina i 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.
Pełny tekst źródłaGupta, Punit, i 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.
Pełny tekst źródłaRajan, Del. "Entropic DDoS Detection for Quantum Networks". Quantum Reports 4, nr 4 (13.12.2022): 604–15. http://dx.doi.org/10.3390/quantum4040044.
Pełny tekst źródłaAl-Zewairi, Malek, Sufyan Almajali i 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.
Pełny tekst źródłaFang, Xing, Wenhui Zhang, Jiming Lin i 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.
Pełny tekst źródłaSilva, Rui Filipe, Raul Barbosa i Jorge Bernardino. "Intrusion Detection Systems for Mitigating SQL Injection Attacks". International Journal of Information Security and Privacy 14, nr 2 (kwiecień 2020): 20–40. http://dx.doi.org/10.4018/ijisp.2020040102.
Pełny tekst źródłaMuhammad, Hafsat, Olumide B. Longe, Abimbola Baale, i 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.
Pełny tekst źródłaO, Belej, Spas N, Artyshchuk I i 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.
Pełny tekst źródłaHairab, Belal Ibrahim, Heba K. Aslan, Mahmoud Said Elsayed, Anca D. Jurcut i 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.
Pełny tekst źródłaHaseeb-ur-rehman, Rana M. Abdul, Azana Hafizah Mohd Aman, Mohammad Kamrul Hasan, Khairul Akram Zainol Ariffin, Abdallah Namoun, Ali Tufail i Ki-Hyung Kim. "High-Speed Network DDoS Attack Detection: A Survey". Sensors 23, nr 15 (1.08.2023): 6850. http://dx.doi.org/10.3390/s23156850.
Pełny tekst źródłaTolіupa, Serhii, Oleksandr Pliushch i 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.
Pełny tekst źródłaBdair Alghuraibawi, Adnan Hasan, Rosni Abdullah, Selvakumar Manickam i 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 (1.12.2021): 5216. http://dx.doi.org/10.11591/ijece.v11i6.pp5216-5228.
Pełny tekst źródłaAbuabid, Ali, i Abdulrahman Aldeij. "Cyber Security Incident Response". Journal of Information Security and Cybercrimes Research 7, nr 1 (2.06.2024): 29–50. http://dx.doi.org/10.26735/pnob5534.
Pełny tekst źródłaLin, Hsiao-Chung, Ping Wang i Wen-Hui Lin. "Implementation of a PSO-Based Security Defense Mechanism for Tracing the Sources of DDoS Attacks". Computers 8, nr 4 (4.12.2019): 88. http://dx.doi.org/10.3390/computers8040088.
Pełny tekst źródłaGara, Fatma, Leila Ben Saad i 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 (lipiec 2017): 22–47. http://dx.doi.org/10.4018/ijswis.2017070102.
Pełny tekst źródłaYan, Guanghua, Qiang Li, Dong Guo i 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.
Pełny tekst źródłaXuan, Cho Do, Duc Duong i 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.
Pełny tekst źródłaAlashhab, Abdussalam Ahmed, Mohd Soperi Mohd Zahid, Mohamed A. Azim, Muhammad Yunis Daha, Babangida Isyaku i 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.
Pełny tekst źródłaShang, Fute, Buhong Wang, Fuhu Yan i Tengyao Li. "Multidevice False Data Injection Attack Models of ADS-B Multilateration Systems". Security and Communication Networks 2019 (3.03.2019): 1–11. http://dx.doi.org/10.1155/2019/8936784.
Pełny tekst źródłaVermani, Kunal, Amandeep Noliya, Sunil Kumar i Kamlesh Dutta. "Ensemble Learning Based Malicious Node Detection in SDN-Based VANETs". Journal of Information Systems Engineering and Business Intelligence 9, nr 2 (1.11.2023): 136–46. http://dx.doi.org/10.20473/jisebi.9.2.136-146.
Pełny tekst źródłaLiu, Likun, Hongli Zhang, Xiangzhan Yu, Yi Xin, Muhammad Shafiq i 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.
Pełny tekst źródłaDesai, Vinod, i Dinesha Hagare Annappaiah. "Reputation-based Security model for detecting biased attacks in BigData". Indonesian Journal of Electrical Engineering and Computer Science 29, nr 3 (1.03.2023): 1567. http://dx.doi.org/10.11591/ijeecs.v29.i3.pp1567-1576.
Pełny tekst źródłaALAzzawi, 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.
Pełny tekst źródłaDasari, Kishore Babu, i 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.
Pełny tekst źródłaAl-Rajeh, Noura S., i 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.
Pełny tekst źródłaXia, Kui Liang. "Modeling and Simulation of Low Rate of Denial of Service Attacks". Applied Mechanics and Materials 484-485 (styczeń 2014): 1063–66. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.1063.
Pełny tekst źródłaSkaruz, 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.
Pełny tekst źródłaKhan, Zulfiqar Ali, i 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.
Pełny tekst źródłaBarabanov, Alexander, Denis Dergunov, Denis Makrushin i 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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