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- International Journal of Innovative Research in Information Security is an International peer-reviewed research publishing journal with a laser-beam focal aim of promoting and publishing original high quality research dealing with theoretical and scientific aspects in all disciplines of Information Technology. It is a monthly published online international scientific research journal focusing on issues in information technology research.
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- 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.
- 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..
- International Journal of Innovative Research in Information Security, 9 (2): 10-14 (May 2023)1. Adler, A.; Schuckers, S. Biometric vulnerabilities, overview. In Encyclopedia of Biometrics; Li, S.Z., Jain, A., Eds.; Springer: Boston, MA, USA, 2009. https://doi.org/10.1007/978-0-387-73003-5_65 2. Nguyen, H.T. Fingerprints Classification through Image Analysis and Machine Learning Method. Algorithms 2019, 12, 241. https://doi.org/10.3390/a12110241 3. Biometric Systems Lab—FVC2000: Fingerprint Verification Competition. Available online: FVC2000 (unibo.it)(accessed on 22 January 2021). 4. Tang, Y.; Gao, F.; Feng, J. Latent fingerprint minutia extraction using fully convolutional network. In Proceedings of the 2017 IEEE International Joint Conference on Biometrics, Denver, CO, USA, 1–4 October 2017; pp. 117–123. https://doi.org/10.1109/btas.2017.8272689 5. Huang, X.; Qian, P.; Liu, M. Latent fingerprint image enhancement based on progressive generative adversarial network. In Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, Seattle, WA, USA, 14–19 June 2020; pp. 3481–3489. https://doi.org/10.1109/cvprw50498.2020.00408 6. Neurotechnology Company—Sample Fingerprint Databases. Available online: Download biometric algorithm demo software, SDK trials, product brochures. (neurotechnology.com)(accessed on 22 January 2021). 7. Fingerprint Image identification for crime detection (2019) Fingerprint Image Identification for Crime Detection | IEEE Conference Publication | IEEE Xplore https://doi.org/10.1109/iccsp.2019.8698014.
- International Journal of Innovative Research in Information Security, 9 (2): 15-20 (May 2023)1 D. Pavithra; Ranjith Balakrishnan, “IOT based monitoring and control system for home automation”, IEEE Explore, Communication Technologies (GCCT). https://doi.org/10.1109/gcct.2015.7342646 2 Dr. M. Suresh, A. Amulya, M. Hari Chandana, P. Amani, T. Lakshmi Prakasam. “Anti theft flooring system using raspberry pi using” in Compliance Engineering journal, vol 12, no. 7, pp. 306 – 317, 2021. 3 Sonali Das, Dr. Neelanarayan, “ IOT Based Anti Theft Flooring System” in IJESC , vol 10, no.4, pp. 25463-25466,2020. 4 Siddalingesha G.R, H. M. Shamita, “IOT Based Anti Theft System for home” in IRJET, vol 8, no. 10, pp. 509 – 513, 2021. 5 Sanjana Kute, Ruthvik Pimpalkar, Shivajirao S, “Theft Detection System” in IRE Journals, vol 4, no 10, 2456 – 2462, 2021. 6 Gaurav Sable, Gaurav Sharma, Manish Bhalerao, Yash Ramugade, “IOT Based Theft Detection using Raspberry Pi” in IJIRT, vol 11, no 12, 2356 – 2360, 2022. 7 Mohd Musab, Ms. Seema Kaloria, Ankit Chhipa, Anand Sharma, Fardeen Mansoori, “IOT Based Anti-Theft Security System” in IJRTI, vol 7, no 6, pp. 106 – 109, 2022. 8 Santosh Mahale, Shivam Gujrathi, Pratik Bramhecha, Kalyani Bedarkar, Rohini Shinde, Yashraj Patil, “Anti-Theft Detection System” in IJIRSET, vol 9, no 4, pp. 1889 – 1895, 2020. 9 Sharnil Pandya, Hemant Ghayvat, Ketan Kotecha, Mohammed Awais, Saeed Akbarzadeh, Prosanta Gope , Subhas Chandra Mukhopadhyay and Wei Chen, “Smart Home Anti-Theft System” in applied system innovation, vol 1, no 42, pp. 1-22, 2018 https://doi.org/10.3390/asi1040042 10 Mr. Vikrant A. Agaskar, “ IOT BASED IOT Based Theft Detection” in IJCRT, vol 6, no 2, pp. 231 – 234, 2018..
- International Journal of Innovative Research in Information Security, 09 (2): 50-54 (May 2023)1. Muhlenbach, F. and Rakotomalala, R. (2015), “Discretization of Continuous Attributes,” In: Wang, J., Ed., Encyclopedia of Data Warehousing and Mining, Idea Group Reference, 397-402. https://doi.org/10.4018/978-1-59140-557-3.ch076 2. M. Liu, D. Zhang, and D. Shen, “Relationship induced multi- 52 template learning for diagnosis of alzheimer’s disease and mild cognitive impairment,” IEEE transactions on medical imaging, vol. 35, no. 6, p. 1463—1474, (2016). https://doi.org/10.1109/tmi.2016.2515021 3. Abdullah Caliskan, Hasan Badem, A. Baştürk, M.E. Yüksel, “Diagnosis Of The Parkinson Disease By Using Deep Neural Network Classifier”, Journal Of Electrical And Electronics Engineering, (2017):3311-3318 4. M. Abdar and M. Zomorodi-Moghadam, “Impact of Patients’ Gender on Parkinson’s disease using Classification Algorithms” Journal of AI and Data Mining, vol. 6, (2018). 5. 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