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Avira AntiVir Personal - FREE Antivirus ist eine zuverlässige kostenfreie Virenschutzlösung, die Ihren Computer ständig mit hoher Geschwindigkeit auf Malware, wie Viren, Trojaner, Backdoor-Programme, Hoaxes, Würmer, Dialer etc., prüft. Sie überwacht dabei jede Aktion des Nutzers und des Betriebssystems und reagiert sofort, wenn sie Malware entdeckt.
Avira AntiVir Personal ist ein benutzerfreundliches Antivirenprogramm mit vielen Schutzfunktionen. Das Produkt ist kostenfrei für Privatnutzer, nicht für gewerbliche oder geschäftliche Nutzung. Für Windows oder Unix verfügbar.
ausgeführt, sodass Sie Ihren PC unter Windows so verwenden können, wie Sie es möchten - ohne Unterbrechungen oder lange Computerwartezeiten.
Weitere Informationen finden Sie im Microsoft Center zum Schutz vor Malware
MonkeyFist is a dynamic request forgery attack tool released at Black Hat USA 09. It allows you to easily pull of dynamic request forgeries using different scenarios such as redirects, pages, POST based attacks, and even fixation type attacks.
Shuaib, Thejesh, and Harish. International Journal of Innovative Research in Information Security, 09 (2):
45-49(May 2023)1 Muhammad Kamran, Muhammad Asif, Zeeshan Ahmed, and H.B. Kekre. Ä Secure and Reliable Face Recognition Based Attendance System Using Block chain." In IEEE International Conference on Computer, Communication and Control Technology (I4CT), pp.1-5.IEEE,2021. 2 P.K.Shukla, S.K.Srivastava, and A.K.Tiwari."Deep Learning Based Face Recognition System for Attendance Management." In IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), pp.466-470.IEEE,2021 https://doi.org/10.1109/rteict.2017.8256691 3 S.A. Hameed, Zeeshan Ahmed, and H.B. Kekre. "Privacy-Preserving Face Recognition for Attendance Systems." In IEEE International Conference on Computer, Communication and Control Technology (I4CT),pp.1-5.IEEE,2021. 4 Muhammad Asif, Zeeshan Ahmed, H.B. Kekre, and A.R. Naseer. Ä Survey of Face Recognition Techniques for Attendance System." In IEEE International Conference on Computer, Communication and Control Technology (I4CT),pp.1-5.IEEE,2020. 5 H.B.Kekre, S.R.Patil, and D.S. Dharaskar.Än Accurate and Efficient Face Recognition Based Attendance System." In IEEE International Conference on Advances in Computing, Communications and Informatics (ICACCI),pp.2265-2269.IEEE,2020. 6 E Varadharajan , R Dharani , S.Jeevitha, B Kavinmathi, S. Hemalatha “ Automatic Attendance Management system using face detection” at 2020 Department of InformationTechnology. https://doi.org/10.1109/get.2016.7916753 7 Shreyak Sawhney, Karan Kacker, Samayak Jain, Shailendra Narayan ,Rakesh Garg“Real Time Smart Attendance system using face recognition techniques “ in international conference on cloud computing data science and engineering 2019. https://doi.org/10.1109/confluence.2019.8776934.
Radha, Prakhar, Shaik, Shantanu, and Veena. International Journal of Innovative Research in Information Security, 09 (2):
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Krithika, Lakshitha, Monica, Priya, and Veena. International Journal of Innovative Research in Information Security, 09 (2):
21-27(May 2023)1. Currency Recognition system using Image Processing. SANDEEP KUMAR CHAUBEY Andrew S. Morgan Kaufmann Publishers, 1995. 2. A Survey on Indian Currency Note Denomination Recognition System. Aruna Manpreet Bagga, Dr.Baljit Singh. 1995. 3. Dr. Baljith Singh, Aruna D H Indian currency note denomination system. 4. Ms. Monali Patil, Prof. Jayant Adhikari Detection of fake currency using digital image processing. 5. Arun Anoop M, Dr K.E. Kannammal Fake currency detection 6. Vidhi Roy and Sushanth Patil Fake Currency detection using image processing. 7. M. Deborah and Soniya Prathap Detection of Fake currency using edge detection. 8. Akash Rana, Avinash Kumar and Shivam Kumar Jha Detection of fake currency using machine learning technique. 9. Mayadevi, A. Gaikwad, Vaijinath, V. Bhosle and Vaibhav Currency note feature extraction. 10. Brinda M Object Detection using Haar-Like Feature Extraction..
Dhanalakshmi, Jayasurya, Manoj, and Manu. International Journal of Innovative Research in Information Security, 9 (2):
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