- The document contains messages from the Conference Chair, Organizing Chair, and Publication Chair of the Fifth International Conference on Inventive Computation Technologies (ICICT 2022). - The messages welcome attendees to the conference, note it will provide a platform to exchange ideas and share knowledge on recent advances in communication and computing technologies, and thank those involved in organizing the event. - A list of committee members for the conference is also included.

3. Message from the Conference Chair
Dear all,
Welcome to the Fifth International Conference on Inventive Computation Technologies (ICICT
2022). During the course of the event you will acquire a better understanding and state-of-the-art
awareness on Electronics, Communication and Computation technologies, and its positive
impacts on the near future. By listening to leading experts in this field, you will be equipped with
the emerging innovative techniques in the Computing and Communication domain and I hope
that this conference will enable you to implement successful research works at your area of
interest.
Prof. Dr. Subarna Shakya,
Conference Chair - ICICT 2022,
Professor,
Department of ECE,
Pulchowk Campus,
Institute of Engineering,
Tribhuvan University, Nepal.

4. Message from the Organizing Chair
It is great privilege for me to present the book of abstracts of ICICT 2022 conference to all the
conference delegates, authors and readers. I hope the readers of the book will find it to be more
useful and motivating to gain more knowledge on the state-of-the art technologies that finds out
extensive implementation in real-time applications.
ICICT 2022 has provided a platform for discussing the recent research advancements in both the
Communication and Computing Technologies domain. ICICT 2022 conference held at Nepal on
July 20-22, 2022 was primarily designed to encourage the research innovations in
Communication and Computing Methodologies. Nevertheless, the ICICT proceedings provides
an analysis on the new innovative techniques that revives the synergy that already exists between
the Computing and Communication Technologies in order to provide expedient results in the
near future.
I would like to thank all the academic staffs, members of conference committee, reviewers from
our institution and also the authors, and conference delegates, who have worked hard to produce
the informative conference proceedings. I would like to extend my special thanks to all the
external reviewers for deploying their professional expertise in making valuable suggestions to
the authors to improve their work.
Finally, I wish all the attendees of ICICT 2022 to have a memorable and highly informative
technical gathering in Nepal.
Dr. Joy Iong Zong Chen,
Organizing Chair – ICICT 2022,
Professor,
Department of Electrical Engineering,
Da-Yeh University, Changhua County,
Taiwan.

5. Message from the Publication Chair
On behalf of the Organizing Committee, I am delighted and honored to welcome all the
delegates and guests for the Fifth International Conference on Inventive Computation
Technologies (ICICT-2022) that will take place on 20-22, July, 2022.
Fifth International Conference on Inventive Computation Technologies (ICICT-2022) will give
participants a platform to exchange ideas and to create novel opportunities to share various views
and broaden their knowledge. I am sure that this conference will act as a foundation to some
great advancement in science and technology.
I hope you will enjoy the conference and the interactions with your colleagues and other
presenters here. The Conference will prove to be beneficial and also will increase the innovative
technical knowledge in you. Let us look forward to a brilliant conference. I wish all the
presenters all the very best and I hope you have a great time here.
Dr. S. Smys,
Publication Chair – ICICT 2022,
Professor,
Department of EEE,
RVS College of Engineering and Technology,
Coimbatore, India.

6. List of Committee Members
Conference Chair
Prof. Dr. Subarna Shakya,
Professor,
Department of ECE, Pulchowk Campus,
Institute of Engineering,
Tribhuvan University, Nepal.
Organizing Chair
Dr. Joy Iong Zong Chen,
Professor,
Department of Electrical Engineering,
Da-Yeh University,
Changhua County, Taiwan.
Publication Chairs
Dr. S. Smys,
Professor,
Department of EEE,
RVS College of Engineering and Technology,
Coimbatore, India.
Dr. Hoaxing Wang,
Go Perception Laboratory,
Cornell University,
USA.
Technical Program Chairs
 Dr. Nava Raj Karki, Chair, IEEE PES NEPAL CHAPTER & Professor, Department of
EEE, Tribhuvan University, Nepal.
 Dr. Suma V, Professor and Head, Department of Computer Science and Design,
Dayananda Sagar College of Engineering, Bangalore, India.
 Dr. An Braeken, Professor, Vrije Universiteit Brussel, Belgium.
 Dr. Pradeep Kumar, Professor, University of KwaZulu-Natal, Durban, South Africa.
 Dr. Przemyslaw Falkowski-Gilski, Gdansk University of Technology, Poland.

7. Technical Program Committee
 Dr. Danda B. Rawat, Howard University, Washington, DC, USA.
 Dr. Md. Monzur Morshed, Professor, University of Dhaka, Bangladesh.
 Dr. Manoj Karkee, Washington State University, USA.
 Dr. Amir Qayyum, Professor, Capital University of Science and Technology, Islamabad,
Pakistan.
 Dr. Ke-Lin Du, Affiliate Associate Professor, Department of Electrical and Computer
Engineering, Concordia University, Montreal, Canada.
 Dr. Robert Bestak, Professor, Czech Technical University in Prague, Czech Republic.
 Dr. Ayoub Khan, Associate Editor, IEEE Access Journal, USA, Scientific & Scholarly
Editor-eContent Pro Int. , USA.
 Dr. Xiao-Zhi Gao, School of Computing, University of Eastern Finland, Finland.
 Dr. Maad Kamal Al-Anni, Ministry of Higher Education and Scientific Research
MoHESR, Al-Iraqia University, College of Engineering, Republic of Iraq.
 Dr. Francisco M. Gonzalez-Longatt, Universities I Sørøst-Norge/University of South-
Eastern Norway.
 Dr. R. Dhaya, Asso. Prof. / Dept. of Computer Science, King Khalid University,
Kingdom of Saudi Arabia.
 Prof. Dr. Kuan Yew Wong, School of Mechanical Engineering, Universiti Teknologi
Malaysia, Skudai, Johor, Malaysia.
 Dr. Mohiuddin Ahmad, Professor, Dept. of EEE & Director, IICT, KUET, Khulna
University of Engineering & Technology (KUET), Khulna, Bangladesh.
 Prof. Tomonobu Senjyu, University of the Ryukyus, Nakagami District, Nishihara,
Senbaru.
 Dr. Yo-Sheng Lin, Distinguished Professor, Department of Electrical Engineering,
National Chi Nan University, Puli, Nantou, Taiwan.
 Dr. Ing. Pavel Lafata, Department of Telecommunication Engineering, Czech Technical
University in Prague, Prague, Czech Republic.
 Dr. Hui-Ming Wee, Professor, Industrial & Systems Engineering Department, Chung
Yuan Christian University, Taoyuan, Taiwan.
 Dr. Girmay Hailu, Department of Communication Systems, Eritrea Institute of
Technology, Eritrea.
 Dr. Yong Shi, Kennesaw State University, USA.
 Dr. Alaa Hamza Omran University of information technology and communications / Iraq.
 Dr. Sivaram Rajeyyagari, University Professor, Deanship of Information Technology and
E-Learning, Shaqra University | Ministry of Higher Education, Kingdom of Saudi Arabia.
 Dr. Joy Iong-Zong Chen, Professor, Department of Electrical Engineering, Dayeh
University, Taiwan.

8.  Dr. Jill Thomas, Department of Geography, Geology, Illinois State University, Normal,
IL, USA.
 Dr. Álvaro Rocha, ISEG, University of Lisbon, Lisbon, Portugal.
 Dr. V. S. Felix Enigo, Associate Professor, Department of Computer Science &
Engineering, SSN College of Engineering, Kalavakkam, India.
 Dr. T. Santhana Krishnan, AOP, Department of EEE, REC.
 Dr. Kannamal A, Associate Professor, Department of ECE, PSG College of Technology,
Coimbatore, India.
 Dr. Sridevi S, Visvesvaraya Ramanujan Computing Center, Anna University, Chennai,
India.
 Prof. Dr. Kanthavel, Dept. of Computer Engineering, King Khalid University, KSA.
 Dr. L. K. Hema, Professor & Head of the Department, Department of Electronics and
Communication Engineering, Aarupadai Veedu Institute of Technology, Paiyanoor,
Chennai, India.
 Mr. K. Jason, Department of CSE, JCT college of Engineering and Technology,
Coimbatore, India.
 Ms. A. Rajalakshmi, Associate Professor, Department of Electrical and Electronics
Engineering, Rajalakshmi Engineering College, Thandalam, Chennai, India.
 T. Janardhan Reddy, Senior Member, Biomedical Engg, Applied Mechanics Dept,
Chennai, India.
 Dr. P. Usha Rani, Senior Member IEEE, Life Member ISTE, Professor / EEE Dept., R.
M. D. Engineering College, Kavaraipettai, India.
 Dr. Swarnalatha P, Associate Professor, School of Computer Sci. Engg. , VIT University,
Vellore, Tamil Nadu, India.
 Dr. M. Saravanan, Associate Professor, Department of ECE, IFET College of
Engineering, Villupuram, India.
 Mr. M. Arun, ECE, IEEE Student Branch Counselor, Panimalar Institute of Technology,
Chennai, India.
 Dr. G. Gaswin Kastro, IEEE Student Branch Counselor, Dept of ECE Annai Vailankanni
College of Engineering, Azhagappapuram Post, Kanyakumari, India.
 Dr. D. Vasanthi Balasubramanian, Professor, CSE, IFET College of Engineering,
Villupuram, India.
 Dr. Avudaiammal. R, Professor/ECE, St. Joseph's College of Engineering, Chennai,
India.
 Dr. L. M. Merlin Livingston, Principal, Jeppiaar Institute of Technology, India.
 Dr. N. Poonguzhali, Associate Professor, Department of CSE Manakula Vinayagar
Insititue of Technology, Puducherry, India.
 Dr. J. Deny, Kalasalingam Academy of Research and Education, (Deemed to be
University) Tamilnadu. , India.
 Dr. C. Komathi, EIE, Sri Sairam Engineering College, Chennai, India.

9.  Dr. Vijay Kumar Banga, Principal, Amritsar College of Engineering and Technology,
Amritsar, Punjab, India.
 Dr. Latha Rajagopal, Professor, CSE, KSK College of Engineering & Technology,
Thanjavur, Tamil Nadu , India.
 Dr. Jawahar. P. K, B. S. Abdur Rahman Crescent Institute of Science & Technology,
GST Road, Vandalur, Chennai, India.
 Dr. Thippeswamy Mn Nitte Meenakshi Institute of Technology, Yelahanka, Bangalore,
India.
 Dr. Suresh Babu, Principal, Rajadhani Institute of Engineering & Technology, Kerala.
 Dr. P. Aruna Jeyanthy, Professor/EEE Department, Kalasalingam University,
Srivilliputhur, Tamil Nadu, India.
 Dr. V. Nandalal, Associate Professor, Department of Electronics and Communication
Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India.
 Dr. Vinoth Kumar K, Associate Professor, Department of Electrical and Electronics
Engineering, New Horizon College of Engineering(Autonomous), Bengaluru, Karnataka,
India
 Dr. Anand Raghavendra Rao, Professor, PESIT, Bangalore, Karnataka, India.
 Dr. Sushila Umesh Ratre, Department of Computer Science and Engineering, Amity
School of Engineering and Technology, Amity University, Mumbai, India.
 Dr. Sushil Kumar Jain, Associate Professor, Manipal University, Jaipur, Rajasthan, India.
 Dr. S. S. Sujatha, Associate Professor in comp. sc, S. T. Hindu College, India.
 Dr. Rasika Mallya, Associate Director, NMITD, Dadar (W), Mumbai, India.
 Dr. Dalvan Griebler, Associate Professor, Pontifical Catholic University of Rio Grande
do Sul (PUCRS), and Três de Maio Educational Society (Setrem), Brazil.
 Dr. Viji Rajendran V Associate Professor, Department of CSE, NSS College of
Engineering, Palakkad, India.
 Dr. S. V. Viraktamath, Department of Electronics & Communication Engineering, SDM
College of Engineering & Technology, Dharwad, Karnataka, India.
 Dr. V. Govindasamy, Associate Professor, Department of Information Technology,
Pondicherry Engineering College, India.
 Dr. Sudhanshu S. Gonge, Department of Computer Engineering, Vishwakarma Institute
of Technology, Upper Indira Nagar, Bibwewadi, Pune, Maharashtra, India.
 Dr. Karthik Rajendra, Professor & Dean (R&D), Dept. of Electronics & Communication,
MLR Institute of Technology, Laxman Reddy Avenue, Dundigal, India.
 Dr. Sunil L. Bangare, STES's Sinhgad Academy of Engineering, Kondhwa-Bk, Pune,
India.
 Dr. S. Mary Praveena, Associate Professor ECE Department Sri Ramakrishna Institute of
Technology, Coimbatore, India.
 Dr. Nadia Abd-Alsabour, Cairo University, Egypt.
 Dr. Punal M. Arabi, HoD, Dept. of Biomedical Engineering, ACSCE, Bangalore, India.

10.  Dr. T. Arumuga Maria Devi, Centre for Information Technology and Engineering,
Manonmaniam Sundaranar University, Tirunelveli, India.
 Dr. Dimitrios Koukopoulos, Associate Professor, University of Patras, Greece.
 Dr. P. Karthikeyan, Associate Professor, Department of Computer Science &
Engineering, School of Engineering & Technology, Jain University, Bangalore, India.
 Dr. A. Chandrasekar, Department of Computer Science, St. Joseph's College of
Engineering, Sollinganalur, Chennai, Tamilnadu, India.
 Dr. Hussein Kamal Anwer, Plymouth University, UK.
 Dr. Surekha Lanka, Director of Technology program, IT Department, Stamford
International University, Bangkok, Thailand.
 Dr. S. Selvi, Government College of Engineering, Bargur, India.
 Pr. Pascal LORENZ, University of Haute Alsace, Colmar, France.
 Dr. Manish Kumar, Department of Computer Applications, M. S. Ramaiah Institute of
Technology, Bangalore, India.
 Dr. S. Palanivelrajan, Associate Professor, Department of Electronics and
Communication Engineering, M.Kumarasamy College of Engineering, Thalavapalayam,
Karur, Tamilnadu, India.
 Dr. Vinay Chowdary, Dept. of EIC, versity of Petroleum & Energy Studies, Dehradun,
Uttarakhand, India.
 Mr. Praveen Agarwal Anand, International College of Engineering, Near Kanota, Agra
Road, Jaipur, India.
 Dr. Maizate Abderrahim, Computer Science, Hassan II University, Morocco.
 Dr. D. Sugumar, Department of Electronics and Communication Engineering, Karunya
Institute of Technology and Sciences (Deemed to be University), Coimbatore, India.
 Dr. Harpal Thethi, Professor & Head, Division of Career Services, Lovely Professional
University (LPU), Punjab, India.
 Dr. Rajesh, Associate Professor, Department of Information Technology , Mepco
Schlenk Engineering College, Sivakasi, Tamil Nadu, India.
 Dr. Prajoy Podder, Institute of ICT, BUET, Dhaka, Bangladesh.
 Dr. Paul Rodrigues, Professor, Department of Computer Engineering, King Khalid
University, Abha, Saudi Arabia.
 Dr. Md. Masud Rana, University of Technology Sydney, Australia.
 Dr. R. Manjith, Associate Professor, Department of ECE, Dr. Sivanthi Aditanar College
of Engineering Senior Member - IEEE, Vice Chairman - IEEE Photonics Society, IEEE
Madras Section, India.
 Dr. T. Revathi, HoD, IT Department, Mepco Schlenk Engineering College, Mepco
Engineering College (P. O), Sivakasi, India.
 Dr. A. Neela Madheswari, Professor, Department of Computer Science and Engineering,
Mahendra Engineering College, Namakkal, India.
 Mr. Dalvan, Pontifical Catholic University of Rio Grande do Sul (PUCRS) and Três de
Maio Faculty (SETREM), India.

11.  Mr. Subrata Paul, Annex College, Salt Lake, Kolkata, India.
 Dr. S. Velliangiri, Associate Professor, Department of CSE, B V Raju Institute of
Technology(Autonomous Institution), Narasapur, Telangana, India.
 Dr. Raghunandan G H, Department of Electronics and Telecommunication Engineering,
BMS Institute of Technology & Management, Bengaluru, India.
 Dr. Vivek Kumar Singh, Energy for Sustainability Initiative, University of Coimbra,
Portugal.
 Dr. Narayanan K, EEE Department, School of Electrical & Electronics Engineering,
SASTRA Deemed to be University, Tirumalaisamudram, Thanjavur, Tamil Nadu, India.
 Dr. V A Sankar, Ponnapalli Sreyas Institute of Engineering and Technology, Telangana,
India.
 Dr. N. Kannan, Professor and Principal, The Oxford College of Engineering,
Bommanahalli, Bengaluru, India.
 Dr. J. Jesu Vedha Nayahi (Sr. Gr.), Department of Computer Science and Engineering,
Anna University Regional Campus-Tirunelveli, India.
 Dr. Nehru K, Electrical and Computer Engineering, in national university of Singapore,
Singapore.
 Dr. Jennifer S. Raj, Professor, ECE, Gnamani College of Technology, Namakkal, India.
 Dr. Sikhinam Nagamani, Department of CSE, RGUKT IIIT, AndhraPradesh, India.
 Dr. N. Nithyavathy, IEEE Branch Counselor, Kongu Engineering College, Perundurai,
Erode, Tamil Nadu, India.
 Dr. Nikhil Padhye, Department of Mechanical Engineering, Indian Institute of
Technology Kanpur, Kanpur-208016, U. P., India.
 Dr. Joshua Samuel Raj, Professor, KVM College Road, Kokkothamangalam P. O,
Cherthala, Alappuzha, India.
 Dr. K. Rajeswari, Dept. of ECE, TCE, Madurai, India.
 Dr. Bondu Venkateswarlu, Associate Professor, Dept of Computer Science and
Engineering, Dayananda Sagar University, Bangalore, India.

12. 5th
International Conference on Inventive Computation
Technologies ICICT 2022
20-22, July 2022
Table of Contents
S. No Paper Title/ Author Name Page No
1
Provably Secure Pseudonyms based Authentication Protocol for Wearable
Ubiquitous Computing Environment
Vincent Omollo Nyangaresi
1
2
Inverse Reinforcement Learning via Deep Gaussian Process for Reactive Collision
Avoidance in Dynamic Environments
Saugat Shahi, Heoncheol Lee
8
3
Blockchain Solutions for Covid - policy Enforcement Versus Food Security: A
Demonstration of Customizable Benefits of Blockchain for e-Governance and e-
Business
Shiri Vivek, Rolika Dalela
13
4
Deep NeuralNetwork Models for Diagnosis of COVID-19 and Respiratory Diseases
by Analyzing CT-Scans and Explainability using Trained Models
Tahsin Islam, Shahriar Absar,S. M. Ali Ijtihad Nasif, Sadman Sakib Mridul
17
5
Self-Moving Sediment Removal of Water Bodies using Machine Learning
Techniques (Aqua Redeemer)
Dharanika.T, Abu Thahir.M, Guruprasaath. A,Abishak.T, Kautham D. V
25
6
Repercussion of Expressions in Facial Age Estimation
A. Deepa,Sasipraba. T
31
7
Image Encryption using Reverse Data Hiding Algorithm with Triple DES
Divya Vadlamudi, Rayavarapu Jayanth Kumar, Cherukumalli Nikhil Sai
37
8
Prevention and Retrieval of Children from Borewell using Arduino
Akhil Nair U, Babu R, Balakrishnan M, Dhanaraja Sekar S, K. Lakshmi
43
9
MPPT and ANN based Solar Tracking System using Photo Diode Sun Sensor
Sathish R, Vinod Kumar D, Jeyaganesan C
47
10
Hope Speech Detection in Tamil and English Language
Medicharla Dinesh Surya Sai Eswar,Nandhini Balaji, Vedula Sudhanva Sarma,
Yarlagadda Chamanth Krishna, Thara S
52
11
Bangla Font Recognition using Transfer Learning Method
Md. Sakibul Hasan,Golam Rabbi, Rejoan Islam, Md. Hasan Imam Bijoy, Md. Azizul
Hakim
58
12
A Review - ML and DL Classifiers for Emotion Detection in Audio and Speech Data
Yogeshkumar J Prajapati, Priyesh P. Gandhi, Sheshang Degadwala
64
13
An Improved Chatbot for Medical Assistance using Machine Learning
Achuthan. S, Balaji. S, Thanush. B, R. Reshma
71
14
Differential Evolution based Compression of CNN for Apple Fruit Disease
Classification
Mohit Agarwal,Rohit Kr Kaliyar, Suneet Kr Gupta
77
15
Audiobooks that Converts Text, Image, PDF-Audio & Speech-Text for Physically
Challenged & Improving Fluency
Kurra Santhi Sri, Chennupati Mounika, Kolluru Yamini
84

13. 16
Hierarchical K-Means Clustring Method for Friend Recommendation System
Anju Taiwade, Nitish Gupta, Rakesh Tiwari, Shashi Kumar Jain, Upendra Singh
90
17
Privacy Preservation of Medical Health Records using Symmetric Block Cipher and
Frequency Domain Watermarking Techniques
Dharmika B, Haritha D, Ch. Rupa, Vineetha Y
97
18
Analysis of Noxious Comments using Machine Learning Algorithms
R Rahul, Reddygari Varun Kumar Reddy, Murlidhar Mourya
105
19
Prediction of Delayed Trauma Following an Ischemic Stroke using Comparative
Machine Learning Study
Sakshi Mhatre, Megha Trivedi, Manasvi Mhatre
111
20
Software Defect Prediction based on Machine Learning and Deep Learning
Prathyusha Tadapaneni, Naga Chandana Nadella, Mudili Divyanjali, Y. Sangeetha
116
21
Classification of Marine Vessels using Deep Learning Models based on SAR Images
Aneesh Reddy Sannapu, Padmalaya Nayak,Shiva Keshava G, Uppala Rishik Charan,
Krishnam Naidu S
123
22
HR based Chatbot using Deep NeuralNetwork
Rachana T. V ,Vishwas H. N,Priyanka C.Nair
130
23
Classification and Comparision Study of Rice Plant Diseases using Pre- Trained
CNN Models
Raja Krishna Vamsee Kongara,Venkata Siva Charan Somasila, Nallamolu Revanth,
Rama Devi Polagani
140
24
O-RDHF:Optimized Reversible Data Hiding Framework for Media Information
Security
Manjunath Kamath. K, R Sanjeev Kunte
146
25
Trust in Cloud: Perspective from Access Control Models and Machine Learning-A
Detailed Study
S. T. Bharathi, C. Bala Subramanian
153
26
Computing Survey Assessing Digital Business Status: Simaon’s Pradu Hang Dam
Thai Native Chicken Farm
Yasinee Chakrabandhu, Suwit Chotinun, Pornchai Rachtanapun,Chalalai Jaisan,
Suphat Phongthai, Phatthranit Klinmalai, Siriwat Jinsiriwanit,
Thanapong Chaichana
161
27
Design Automation of Two-Stage Operational Amplifier using Multi-Objective
Genetic Algorithm and SPICE Framework
Purvi Das, Babita Jajodia
166
28
Career Choice using Machine Learning Algorithms
Borra Harsha,Nagella Sankeerthana, Nandeti Sravanthi, Suneetha Manne
171
29
Nearpod as a Gamification Resource for Teaching in Virtual Education: a
Mathematical Case Study
Silvia Elizabeth Freire Espín, Diego Marcelo Rodríguez Cortez
178
30
Sound Classification using Deep Learning for Hard of Hearing and Deaf People
Md. Adnan Habib, Zarif Raiyan Arefeen,Arafat Hussain,S. M. Rownak Shahriyer,
Tanzid Islam, Rafeed Rahman, Mohammad Zavid Parvez
185
31
Mobile Tourism, the use of QR Codes and the Diversification of the Tourist Offer
Angélica González-Sánchez, Marlene Coronel- Grados, Cristina Villacís-Mejía, Luis
Ludeña- Villacís
192
32
Image Processing Techniques in the Detection of Hemorrhages in Retinal Images
(STARE & DRIVE)
M. Padmapriya, V. Punitha, S. Pasupathy
198

14. 33
FPGA Implementation of High Performance Precise Signed and Unsigned Multiplier
using Ternary 6-LUT Architecture
Palle Mahendra, Ramesh S R
203
34
Emotion Recognition using Nonverbal Cues
Dudla V Joshita Lavanya, Vemula Bhargavi, Gaddala Madhu Priya, Mande Ramesh
209
35
A Password Secure Mechanism using Reformation-based Honey Encryption and
Decryption
Nirmalraj T, J.Jebathangam
215
36
Multi-Lingual Meta Embeddings in LinCE Data Set
T Ravi Teja, Thara S, K Sai Rahul, R Dinesh Kumar Reddy
222
37
Detection of Tuberculosis using Machine Learning Techniques and Image
Preprocessing
Rubeena Rustum, G. Charles Babu, P. Praveen,V. Lakshmi, Tabitha Indupalli, A.
Sowjanya
227
38
Pivot Based Seed Germination Assessment (PBSGA) Pattern for Germination
Quality Analysis
M. Rudra Kumar, Avinash Sharma, K Sreenivasulu, G. Ramesh
231
39
Resume Screening using NLP and LSTM
S Bharadwaj, Rudra Varun, Potukuchi Sreeram Aditya, Macherla Nikhil, G. Charles
Babu
239
40
Data Analytics based Gender Stereotypes Represented in the Audiovisual Narrative
of the Series "You"
Jeri-Condori, Nataly Silvana, Villanueva-Pastrana, Enzo Javier, Turriate-Guzmán,
Adriana Margarita
243
41
Implementation of an Active Noise Cancellation Technique using Deep Learning
Akarsh S. M, Rajashekar Biradar, Prashanth V Joshi
250
42
Development of Blockchain in Smart Grid using IoT
Jasrin Shiddike, Afsana Ahmed, Mohammad Farshid, Prapty Das Oaishe
255
43
Machine Learning on Web: Skin Lesion Classification using CNN
Senthil Kumar R, Amarjeet Singh, Sparsha Srinath, Vishal Arasu, Nimal Kurien
Thomas
261
44
A Secure and Efficient Location Based Routing to Maximize the Lifetime of
MANET
Hemalatha.M, M. Mohanraj
267
45
Detection of Defected Maize Leaf using Image Processing Techniques
Arabinda Dash, Prabira Kumar Sethy
272
46
Near Field Communication based Smart Augmented Reality System
Chaitanya Kumar A, Ishwara Prabhu S , Jegadeeshwaran T, Guga Priya G
277
47
Hybrid Feature Set based Mitotic Detection in Breast Histopathology Images
Deepak Naik M V, Adarsh S, Sreekumar Vijayakumar, Abhay P Nambiar, Lekha S
Nair
282
48
Classifying Speech into Offensive and Hate Categories along with Targeted
Communities using Machine Learning
Apoorv Aditya, Rithwik Vinod, Ashish Kumar, Ishan Bhowmik, J. Swaminathan
292
49
Energy Efficient Cloud Task Scheduling Policy using Virtual Machine Concept and
VMRRU Technique
Ruchi Soni, Neetesh Gupta
297
50
Enhancing Unpaired Underwater Images with Cycle Consistent Network
Srigowri M V 306

15. 51
Watermark based Image Authentication using Integer Wavelet Transform
Bibek Ranjan Ghosh, Siddhartha Banerjee,Jyotsna Kumar Mandal
313
52
Hyper-Tuned Ensemble Machine Learning Model for Credit Card Fraud Detection
Bholeshwar Prasad Verma,Vijayant Verma,Abhishek Badholia
321
53
Comparative Analysis of Epilepsy prediction using Machine Learning and Deep
Learning
Y. Sai Chandu, Shaik. Fathimabi
329
54
Anxiety Detection in Patients
Likhita Chowdary Koneru, Routhu Ramya Dedeepya,Angadi Lakshmi, G Kranthi
Kumar
337
55
Store-sales Forecasting Model to Determine Inventory Stock Levels using Machine
Learning
Akanksha, Devesh Yadav,Deepak Jaiswal, Ashwani, Ashutosh Mishra
345
56
Performance Analysis of Electronic-certificate Generation and Verification using
Blockchain and Interplanetary File System
Manjula K Pawar,Prakashgoud Patil, Ridham Sawhney, Prem Gumathanavar,
Shraddha Hegde, Kavya Maremmagol
351
57
Hybrid Feature Selection using Shapley Value and ReliefF for Medical Datasets
Neesha Jothi, Sharifah Mashita Syed-Mohamed, Heshalini Rajagopal
357
58
A Convolutional Autoencoder based Keyword Spotting in Historical Handwritten
DevanagariDocuments
Sushma S. N, Sharada B
362
59
An Experimental Study of Parallelism in Different Python Frameworks
Jerome Joseph T, J. Swaminathan
368
60
Tomato Leaf Disease Detection using Image Processing
M. Senthamil Selvi, S. Jansi Rani, A. Nisha, K. Sneka
372
61
Driver Assistant System using Yolo V3 and VGGNET
S. Jansi Rani, A V Vedha Mukund, S Uthirapathi Eswaran,M Vidul
377
62
Blockchain Adherence to System Reliability and Security
Nilton Paulo Raimundo Mendes, Jorge Rady de Almeida Júnior
382
63
Interrelation between Temporal Coordinates and Intrusion Detection Techniques in
Cyber Physical Systems
Stalin Jacob, K SureshKumar, G Balanagireddy, M. M. Vijay
391
64
A Study on Machine Learning based Diabetic Retinopathy
M D Shreyas, Asha Rani K P, Gowrishankar S
397
65
Potential Applications of Fuzzy Logic Controller in the Pulp and Paper Industry – A
Review
Pradeep Kumar Juneja, Sandeep Kumar Sunori, Mehul Manu, Priyanka Joshi,
Somesh Sharma, Prakash Garia, Amit Mittal
405
66
Transform based Lightweight CNN Models for Image Classification
Srijith M Nair, Geetha M
408
67
Automobile Price Prediction using Regression Models
Rupesh Gupta, Avinash Sharma, Vatsala Anand, Sheifali Gupta
416
68
FndIP: Fake News Detection on Social Media using Incompatible Probabilistic
Method
Rohit Kumar Kaliyar, Anurag Goswami, Mohit Agrawal
423
69
Integrated Platform for Patient abnormality detection through GEM enabled Deep
Transnet
R. Vajubunnisa Begum, K. Dharmarajan
429

16. 70
(LISACMT) Language Identification and Sentiment Analysis of English-Urdu ‘code-
mixed’ Text using LSTM
Gazi Imtiyaz Ahmad, Jimmy Singla
435
71
CatBoost and Genetic Algorithm Implementations for University Recommendation
Systems
M. G. Christopher, Jiby Maria Jose,Muhammed Nihal K. V, Tijo Thomas, Rumaise,
Shajulin Benedict
441
72
Breast Cancer Classification using Ensemble of Machine Learning Boosting
Algorithms
Md. Kamrul Hasan, Md. Tasnim Jawad
449
73
Tor vs Yggdrasil: A Comparative Study of Two Different Communication System
Kushal Kothari, Tejal Palwankar,Ayush Dubey, Priya Parate
457
74
Stage Wise Prediction of Covid -19 Pneumonia from CT images using VGG-16 and
SVM
Bipin Nair B J, Akash S, Smaran R, Hemanth V, Satvik Bhat
462
75
An Effective Long Short-Term Memory based- Driver Identification in ITS
Ankit Manderna, Sushil Kumar
470
76
Convolutional NeuralNetworks for the Intuitive Identification of Plant Diseases
D.Ramesh Reddy, Santhosh Kumar, Prakash Kodali
476
77
An Implementation and Evaluation of Blockchain-based Digital Health Passports
Ajay Bandi, Aziz Fellah
482
78
Vehicle Movement based innovative Smart highway Lighting System
Sophiya Susan S, Aakash Praveen Raj,Ashutosh Mishra,
Vachan Thambi
489
79
Building Tamil Text Dataset on LGBTQIA and Offensive Language Detection using
Multilingual BERT
Lavanya S.K, Subalalitha Chinnaudayar Navaneethakrishnan
495
80
Alzheimer’s disease: Early Stage Prediction and Classification using Multi-Model
Technique
M. Sudharsan, G. Thailambal
503
81
Crowdfunding Charity Platform using Blockchain
S.Saranya,Sai Phanindra Muvvala, Vitul Chauhan, Gadde Raja Satwik
509
82
Integrated Security Systems using Big Data
S. Uma Maheswara Rao,Lakshmanan L
517
83
Automatic Speech Recognition for the Nepali Language using CNN, Bidirectional
LSTM and ResNet
Manish Dhakal, Arman Chhetri, Aman Kumar Gupta, Prabin Lamichhane, Suraj
Pandey, Subarna Shakya
522
84
Blockchain-based Food Tracking using for Intelligent Farming using IoT
Praveen Mishra, B. Mohanraj, Gajjala Savithri, M Roshini, R. Krishnamoorthy, S.
Arun
529
85
Real Time Safe Social Distance and Face Mask Detection using YOLO Algorithm
and Deep Learning
Pushpa Latha Soniya, Velayutham R
535
86
Arduino based Maritime Border Alert System for Fisherman
Lijo Jacob varghese, A. Sakthivel, J. K. Saran Kirthic, S. Sharan, R. Shri Pavithra
540
87
Advanced Pre-Ambulance Detection System of Autostretcher Motion to ICU Ward
G. Sukanya, V. Manimegalai, S. Sudhakar, M. Nandhini, D. Sumithra, M.
Manivenkat Raj
546

17. 88
Model Identification and Controller Simulation for Distillation Column
Sandeep Kumar Sunori, Kavita Ajay Joshi, Shweta Arora,Madan Mohan Sati, Farha
Khan, Amit Mittal, Pradeep Juneja
552
89
Soft Starting of Induction Motor using MOSFET
K.P. Suresh, P. Kaleeswaran,E. Madhumitha, V. Meyvigneshwar, K. Mugundhan, P.
Padmaselvi
558
90
Auto Operation and Monitoring of Transformer using IoT Applications
Sathish R, Vinod Kumar D, Muthusami C
564
91
Certain Investigation on Impedance control of High Speed signals in Printed Circuit
Board
Shan A, V R Prakash
571
92
Methodology for Low-Cost Self Reconfiguration Process
S. Saravanan, B. Ragav Raj Kumar, S. Rishi Kumar, R. Sarudharshini, S. Shankar
577
93
Load Sharing Backup Battery in Electric Vehicle using PV Array
A. Elakya, V. Sheeba, R. Tharani, M. Swetha, A. Wilson Thomas
582
94
Design of Solar PV Emulator using Raspberry Pi Controller
Abhishek R. S, Dhanus Kanth A,Hariharan S, Hariharasudhan S,
S. Saravanan
588
95
Two-level Filtering method with Extended Lasso and Information Gain in Microarray
Data Analysis
Sarvani A, Madhavi Reddy Y, Lavanya Kampa
592
96
Comparative Study on Various Low Code Business Process Management Platforms
N. Krishnaraj, R. Vidhya, R. Shankar, N. Shruthi
598
97
Multi source based Battery Charging and Cutoff System
Sophia Jasmine G, Magdalin Mary G, Kumar C, Lohith Raj S, Nafica Parveen M,
Neshan T, Karthikeyan K
604
98
Moisture, Retention and Color Control Strategy in a Paper Mill – A Review
Pradeep Kumar Juneja, Parvesh Saini, Ashutosh Dixit, Niharika Varshney, Sandeep
Kumar Sunori
609
99
RF Energy Harvesting System: Design of Antenna, Rectenna,and Improving
Rectenna Conversion Efficiency
Mayur Rele, Dipti Patil
612
100
Analysis of DC Motor Speed Control and Interfacing it with Drowsiness Detection
Atharva Sulakhe, Arjeet Anand, Akshwin Kisore, Nandha Kishore R B,
Malayakumar Hota
621
101
Height and Weight Estimation of an Individual from Virtual Visuals
Sairam Maganti, Pranai Sri B, Mahidhar Yalamanchili, Sumesh K J
625
102
An Efficient Clipping Method for PAPR Reduction in OFDM Systems
Vijaya Kumar Padarti, Chandini Dasari,P V Venu Gopal Dokala, Venkata Sravya
Chowtapalli, L V Rama Kowshik Avula
632
103
Projective Synchronization of Uncertain Chaotic Systems with Different Dimensions
and External Noise Disturbance
Nisha Yadav, Himesh Handa
638
104
A Circular Microstrip Antenna for K Band Applications
Banuprakash.R,Manushree N, Subhiksha AP, Wadhwa Simran Deepak
644
105
Design and Implementation of a Rescue and Surveillance Robot using Cross Platform
Application
P Jeevan Narayana Raju,Venkata Gaurav Pampana, Vikranth Pandalaneni, G
Gugapriya, Chanthini Baskar
652

18. 106
Mean-Shift and Local Outlier Factor-based Ensemble Machine Learning Approach
for Anomaly Detection in IoT Devices
Amit Kumar Gulhare, Abhishek Badholia, Anurag Sharma
660
107
Design of Voice Controlled Multifunctional Computer Numerical Control (CNC)
Machine
Gayathri. N, Sundar. M, Sargurunathan. R, Sudharsan. R, Sajith A
668
108
Sustainability of Electric Vehicle in India
Rajkumar Kaushik, Chirag Arora, Shilpa Soni, Neha Kumari, Anchal Swami, Rahul
Prajapati
675
109
FLIP60-Caring for Elders An Android based Application
Pasupunooti Sri Harika, Muthyala Lalitha Sri, Movva Manish Srinivas, Polepaka
Rohit, Laxmi Kalyani
679
110
Mitigation of Voltage and Current Harmonics using Modified IC based MPPT
Controller and LCL Filter in a GCSPV System
Siddeshgowda S, M H Sidram
685
111
Electroencephalography (EEG) based Home Automation for Physically Challenged
People using Brain Computer Interface (BCI)
Lavanya Lanka, Dileep Kumar Dhulipalla, Suzan Blessy Karumuru, Nikhil Sai
Yarramaneni, Venkata Rao Dhulipalla
693
112
Investigations on IoT with SWIPT-NOMA Combination in Wireless Sensor
Networks
Reginald Jude Sixtus J, M. Tamilarsi
698
113
Analysis of Voltage Tracking in DC-DC Converter for an Electric Vehicle using
Hybrid Adaptive Controllers
M. Karthikeyan, D. Manimegalai, S. Sivarajan, S. Karthiga, U. Muthuraman
704
114
A Resistance Detection Device for Microelectronic Semiconductors: from Signal
Detection to Fusion Analysis
Peng Yuan, Qi Han, Yu Li, Tao He,Huixiang Huang, Jinhai Chen
712
115
Research on Positioning Accuracy of Welding Robot based on Visual Data Mining
and Pattern Fusion Analysis Algorithm
Yanping Shen, Mengxi Hu, Kai Teng, Caoqi Zhang, Xiang Yang, Wen Liu
716
116
A Navigation Aid Control Method in Restricted Waters based on Differential
Scintillation: Analysis from the Perspective of Real-Time Remote Sensing Images
Qi Han,Peng Yuani, Yu Li, Tao He, Huixiang Huang, Jinhai Chen
720
117
Simulation Application of Finite Element Analysis Software HFSS in Antenna
Engineering Design Under the Background of Big Data
Han Zhenhua, Aidehaijiang·Manafu
724
118
Computer-guided Design of Effective Guidance Platform for Music Appreciation
based on Mixed-Frequency Signal Recognition Algorithm
Hong Zhang
728
119
A Dynamic Prediction Platform for Semiconductor Technology Improvement Trends
and Related Enterprise Value based on Poisson Estimation
Baiyu He
733
120
Modeling the Binary Game Model of the Economic and Social Attributes of Cultural
Industry from the Perspective of Information Fusion
Xuan Mai Bui, Zhu Fan
738
121
Correlation Modeling Algorithm of CEO Cultural Heterogeneity Monitoring and R &
D Expenditure on Enterprise Asset Value based on EEG Data Acquisition Equipment
Chia-Hsien Tang, Li Wei, Yen-Hsien Lee
742

19. 122
Concurrent Testing and Research on the Reform Platform of College Guiding
Management and Service Reform based on Decentralized Disaster Recovery Backup
Wanbin Zhao
746
123
An Efficient VLSI Design of 4-bit ALU
E Vijaya Babu, Y Syamala
750
124
Computer Aided Realization of Gesar Cultural and Creative Product Design System
based on Interactive Algorithm and Cyclic Graph Theory Model
Suo Lang Sang Ge
756
125
A Novel Channel Estimation Scheme for MIMO-OFDM Systems based on CDD
C Geetha, M Vanitha, A. Parimala, D. Kalaiarasi
761
126
Advanced CO2 Ball Equipped Fire Extinguising Unmanned Aerial Vehicle
Swapna. P,Aiswarya. T, Aravinthan. V,Arun Kumar. S,
Karthikeyan. S
768
127
An Upgraded Bidirectional T-type Multilevel Inverter for Electric Vehicle
Applications
P. Lenin pugalhanthi, Balaji. S, Hari Krishna. G, Bharath. R,
Kishore. S
773
128
Evaluation of Three-Phase and Single-Phase Failure SFCL and DVR Mechanisms
M. Siva Ramkumar, A. Amudha, G. Emayavaramban, K. Balachander, Vijayakanth
S, Gunasekaran M, Dhilipkumar B
779
129
Large Scale Grid Connected System Analysis for Hybird Power Generation and
Storage Power Management System
A. Amudha, M. Siva Ramkumar, K. Balachander, G. Emayavaramban, Manikandan
S, Ragul M, Saravana Kumar S, Satheesh Kumar R
785
130
A Wearable Saftey Device for Women using IoT
Priya C, Ramya C Naresh,Mohit, Meager Pravin, Akkash
792
131
Design of Sequential and Concurrent based High Speed Multiplier in DSP
Application
Brightny A, Rajakumar G, Pooja Sen S, Carlus D Rebeak
797
132
Analysis of Performance Enhancement for DC Distribution for Residential
Distribution Network using Hybrid AC DC Distribution Network
Sujitha S, JebaraniEvangeline S, Vinoth Kumar K, Sayanth PV,Vishal Suresh,
Nahush S
806
133
Modelling and Design of Solar-Powered DC Refrigerator for Vaccines
Transportation in Remote Areas
Gunapriya B, Vinoth Kumar K, M Sugumaran, A Manjunathan, Greeshma
Chennareddy, Sahana B, Chitra S, E Kavipriya
811
134
Performance Assessment of Simulink based Speech Radio Band Extension
Technique on Elderly People
R. Praveen Kumar Emani, Pitchaiah Telagathoti, Prasad N
816
135
Design and Implementation of Advanced Controller for Aircraft Control
S. Sathya, K N Karthick, Hemachandra Gudimindla, AkshadaKulkarni, M.
Deivakani, Arshad Mohammed, Siva Ramkumar M
820
136
Isolated DC–AC Matrix Converter based Renewable Energy System for Improving
Power Quality using Proportional Integral (PI) Controller Technique
Suresh N, Dilli Srinivasan, K. Arulvendhan, BabooBarik
827
137
Bidirectional Tee-type Multilevel Inverter Hardware Design and Implementation for
Electric Vehicle Applications
Balachander K, Amudha A, Ramesh G S
834

20. 138
Impact of the Intelligent Control System in Assisting Humans Regarding Complex
Information Processing
Ambika R, Prashant Lahane,G. Kumar, Fazle Rabbi, Muhammad Anas Ma`arif,
Mohmad Kashif Qureshi
838
139
Enhancing the Accuracy of Forest Monitoring Through AI to Reduce Carbon
Footprint
Ravindra Pandey, Diksha Srivastava, Rubar H. Dizayee, Alina Lobanova, Fazle
Rabbi, Pankaj Ramesh Sutkar
844
140
Robotics and Automatics in Terms of Utilizing Rules-based Business Processes
Sridhar Thota, Rinku Sharma Dixit, Moldir NURPEIIS,Dillip Kumar Parida, Aigul
Iissova, Ardak Nigmetova
849
141
Machine Learning on the Role of Eliminating Human Error in the Manufacturing
Industry
Krishnareddy KR,Aravinda T V, Umesh Kumar Patel,Gaukhar Sadvokasova, V.
Shyamala Susan, Kiran Nair
855
142
IoT in Monitoring and Improving Manufacturing Process in Manufacturing Industry
Geo Paul K, Amardip Diwakar Kurukwar, Suraj.E.S, Hendy Tannady, N. Rajendran,
B. S. Abdur Rahman , Yogesh Katkamwar
861
143
Child Rescue System from Open Borewell using Robot
S. Prabhavathi, Pallavi Nayaka B, Nagarathna,Shobha, Sneha Tambekar
865
144
IoT based Sunlight Detecting Dual-Axis Solar Panel System
Alok Kumar, Joy Saha, Shekhar Kumar Sinha, Sk. Istiak Sarwar,Cherry Khosla
869
145
Research on Dust Prevention and Control based on the Construction of Smart Wharf
Huihui Hu Shiyong Cao, Yang Xu
875
146
An Intelligent Failure Free Data Communication Model using Predicted Remaining
Deliveries Scheme
S. Dhanasekaran,P. Vijayakarthik, D. Gobinath, N. Nithiyanandam, A. Sivanesh
Kumar, S. Agnes Shifani, U. Muthuraman,
879
147
An Automated Technology for IoT based Rail-Track Inspection to Locate Surface
Flaws by Robotics and NeuralNetworks
B Uma Maheswari,P Nithya, Sreeja Vijay, K. Tamilarasi, Anitha G, N.
Muthukumaran
886
148
Application and Parallel Sandbox Testing Architecture for Network Security
Isolation based on Cloud Desktop
KaiZhen Ye
892
149
Research on Robustness of Network Security Vulnerability Detection Algorithm
based on Recurrent Bayesian Networks
Jian He, Yan Hu
896
150
Quantitative Analysis and Research on the Multicast Algorithm of Distributed
Blockchain-Oriented e- commerce System in Village Revitalization
Zhenghua Zhao, Yang Yang
900
151
Superintendence of Spectrum in 6G era: an Appraisal
Shylaja P
905
152
Convolutional NeuralNetwork for Speaker Recognition Embedding with Biometric
System
Priyadharshini.A, Mohamed Shazuli S, Balakrishnan.R, Deepthi Joseph, Gunapriya
D
909
153
A Secured Storage Scheme for Cloud Environment using ECC-IRNS based
Deduplication Approach
Lenin J, Rasina Begum B, Sheik Yousuf T, Karthikeyan R
914

21. 154
A Novel Credit Grounded Job Scheduling Algorithm for the Cloud Computing
Environment
B. Sundaravadivazhagan, V. Malathi, V. Kavitha
925
155
Energy Efficiency in Cloud Computing using Hybrid Algorithm
Najiba Said Hamed Alzadjali, Nusrat Jabeen T,Hannah Vijaykumar MaheswariK
933
156
Cloud Computing Elastic Storage System for Storage Optimization
G. Aarthy Priscilla
941
157
Multidimensional Information Security Guarantee Strategy for Scientific Information
of University Administrative Management System based on Data Matrix Algorithm
PeiWei
948
158
Customer Identification in Healthcare using an IoT-based Multimedia Traffic
Categorization Method
R. Sridevi, Praveena Nuthakki, Sreeja Vijay, Saroj Kumar Nanda,D. Arulanantham,
R. Thandaiah Prabu
953
159
A Novel Modulation and Multiplexing Schemes for Analysis of Wireless High Speed
Optical Fiber Communication System
S Priyadharshini, L Ashok Kumar, M Sathya Priya, Samuthira Pandi V
960
160
Energy Efficient Enhanced LEACH Protocol for IoT based applications in Wireless
Sensor Networks
R. Ramya, Sathiyandrakumar Srinivasan, K Vasudevan,I Poonguzhali
966
161
Enhanced IoT based Approach to Provide Secured System
R. M. Dilip Charaan, Aron James S, D. Arul Kumar, M. D. Manigandan
975
162
Insider Attack Detection and Prevention using Server Authentication using Elgamal
Encryption
Sai Akshara Vemuri, Gogineni Krishna Chaitanya
980
163
Resource Aware Data Collection based on Node Relay Configuration in Wireless
Sensor Networks
Asha N, Syed Fiaz A S, Jayashree J,Vijayashree
986
164
Automated Banking Fraud Detection for Identification and Restriction of
Unauthorised Access in Financial Sector
Ankur Biswas, Geethamanikanta Jakka, Ramandeep Singh Deol, M. Raja Suguna,
Barun Kumar Jha, Benjamin Isaac Thomson
991
165
Security System in Parking Lot
KS. Sasmitha sree,J. Sam Jebakumar
997
166
Cloud Computing for Suitable Data Management and Security within Organisations
Lusaka Bhattacharyya,Sunil D M, Supriya G Purohit, Zhanar Toktakynovna, Endang
Fatmawati, G. V. Sriramakrishnan
1006
167
A Review of Efficient Mobility Techniques for Privacy And Secured Cloud
Computing Architectures for Infrastructure as a Service
Betty Elezebeth Samuel, Saahira banu Ahamed
1011
168
Analysis of Security Measures on the Internet of Things based Applications
Vidushi Verma,Munish Bhatia
1021
169
Automating the Storage Process on Cloud by Introducing AI concepts
Umi Salma. B, Uma Perumal, Awatef Balobaid
1030
170
Accident Emergency Alert System
Nidhi Bhatia, K. M Baalamurugan, Yash Dixit
1038
171
An IoT Assisted Secured Healthcare Management Scheme based on RFID and
Crypto Security Enhancement Model
A. Sivanesh Kumar, D. Gobinath, N. Nithiyanandam, P. Vijayakarthik, S.
Dhanasekaran,G. Vinoth Rajkumar
1044

22. 172
Sign Language Interpreter
R. Brindha, P. Renukadevi, D. Vathana,Jeyakumar.D
1052
173
An Efficient Model for Predicting Admission at Emergency Department using Data
Mining
T. Judgi, N. Srinivasan, T. Prem Jacob,A. Pravin, C. M. Suja
1057
174
ASVM: Adaboost with SVM-based Classifier Implementation for Aspect-based
Opinion Mining to Appraise Products
Blesslin Sheeba. T, T. Manimegalai, S. Ananthi, S. Kamatchi, Anitha G, U.
Muthuraman
1062
175
Design and Implementation of Book Lending System based on Web and Data Mining
Middleware
Lu Pang
1070
176
Smart Motion Capture and Scoring System for Taekwondo Training based on
Camera Network Technology
Yongzhi Yang
1075
177
Comparison Study on SPN Type Light Weight Cryptography Algorithms for IoT
Sivakumar. R, J. Jayapriya, N. Krishnan
1079
178
Construction and Implementation of Intelligent Platform for Sports Training based on
Multi- Dimensional Image Modeling
Qiulai Wu, Huan. Zhou
1084
179
Simulation and Efficiency Optimization Algorithm of Virtual Logistics Transmission
Network based on RFID Tag
Dalong Liu, Yanfang Pan, Yanxuan Li, Zhong Zheng
1088
180
Research on Intelligent Information Collection of Business Negotiation System based
on Speech Rate Change Recognition Algorithm
Yanjun He
1093
181
Construction of Neural Conditioning Vocal Training System based on Neural
Computing and Applications (NCAA) Model
Minghui Niu
1098
182
Intelligent Questionnaire Processing Information System for Precise Employment in
Colleges based on Intelligent Interactive Testing Algorithm
PeiHuang
1103
183
Research on a Chinese Character Recognition Framework based on Multi-
dimensional Image Information
Li Guo
1108
184
Research on Dynamic Modeling Algorithm of College Students & Learning
Motivation Factors based on SPSS and Artificial Intelligence Testing Machine
Suyun Yang
1113
185
Online and Offline Integration of Smart Educational Monitoring System based on
Face Recognition Smart Sign-in Devices
Danxia Zhu, Xiaozhong Shen
1118
186
JQuery Implementation of Online Platform for University Human Resource
Management Mode based on Multi-Centralized Networking Algorithm
Yue Lu
1123
187
Design of Mathematical Online Training Interactive Framework based on AI-assisted
Data Modeling Algorithm Visualization Process
Lihong Xue
1127
188
Application of Semantic Segmentation based on Deep Learning in DIM Environment
Li Ma, Xin Guo, Xiaojiao Zhang 1131

23. 189
Security Policy System for Cloud Computing Education Big Data:Test based on
DDos Large-Scale Distributed Environment
Zhiyi Xing
1135
190
Complex Pattern Recognition and Understanding Model in English Linguistics based
on Random Walk and Measure Analysis Algorithm
Zhao Zhao, Jianghong Meng, Yanru Li
1139
191
Research on C++ System Practice of Online Auxiliary Teaching Platform based on
Trusted Data Analysis
Meizhong Huang
1143
192
Implementation of CUDA and Hadoop based system for Intelligent Guiding
Evaluation Algorithm based on Data Center Data Mining
Yan Li
1147
193
Two-dimensional Data Network Modeling of Computer Network Teaching and
Innovation Ability Cultivation
Yue Qian
1154
194
Online Training Platform for Foreign Language in Colleges based on Computer-
Aided Clustering Algorithm of Embodied-Driven Efficacy Data
Qingyun Shu
1158
195
Social Network Information Dissemination and Prediction Algorithm based on
Computer Pattern Modelling and Node Estimation
Wei Gao, Zhen Chen
1163
196
Optimization of Intelligent Informatization Distributed System for Political Training
Support Service based on Flux Architecture
Yanxia Ma
1167
197
Hadoop Data Mining Analysis of Network Education Platform based on PDM New
Media Data Perspectives
Yuxia Han
1172
198
Platform Construction of Intelligent Machine Algorithm and PracticalGuidance
Course for Overlapping Data Monitoring Guiding Russian- Chinese Translation
Guang Feng
1176
199
University Internal Control Detection Platform based on Ubiquitous Distributed Data
Sensing and in-Depth Analysis Algorithm
Ting Liu
1180
200
Optimization Analysis of Start-up Automation and Debugging Technology for High-
Voltage Machinery and Electrical Equipment
Xianglong Huang
1184
201
C# Realization of Online Stability System for Primary Art Classroom based on
Multi-Dimensional Information Technology Integration Platform Technology
Xiaoli Liu, Guoqun Guo
1188
202
The Design of the Multimedia System for the Informationization of the Party
Building Work in the Primary Party Organizations of Colleges in the New Era
Hui Wan, Yu Wang
1192
203
The Application of Artificial Intelligence in the Landscape Design of Humanized
Places:from Focus Recognition to Straight Line Detection Algorithm
Shuanghong Cheng, Chunyan Wu, Fancui Wei, Yonglin Wang, Youguo Wang,
donghuili, Hui Wang, Zhongliang Xu
1196
204
Prediction Algorithm of Guiding Effectiveness based on Fuzzy Data Network
Structure Specification with Character Color Class
Zhenping Yuan
1200

24. 205
Java Implementation of Teacher Information Ability Measurement and Analysis
Intelligent System (AMAIS) based on ICT-TPACK and Recurrent NeuralNetwork
Kuiliang Fu
1204
206
Online Immersive Platform Image Processing Algorithm for Art Courses based on
Virtual Equipment Digital Media Technology
Xiaoli Liu, Guoqun Guo
1209
207
An Early Warning Mechanism for the Environmental Carrying Capacity of Forest
Tourist Attractions and Hotels Online Operations based on Big Data Integration
Technology
Shuaishuai Hao, Lijuan Lian
1213
208
Japanese Multimodal Guidance Framework based on Computer Network Ecological
Environment
Weijie Yao
1217
209
The Design of the Informatization System Developed by the Local Medical Colleges
under the Background of Rural Revitalization
Zhang Liping, Yao Zufu, Yang yang, Yang Zilu, Guo Yiqing
1221
210
Network culture-oriented Monitoring of Colleges based on Word Vector and Data
Stream Clustering with New Development Concept
Ruiping Chen
1225
211
XML Interactive Data Analysis of Online Solutions for Students & Innovative
Ability Training Integrating Engineering Intelligent Information Algorithms
Zhengli Zhang
1230
212
Traffic Prediction for an Intelligent Transportation System using ML
Maithili Saisree Medikonduru, Aswini Devadari, Sravani Chowdary Kasaraneni,
Moksha Bhavani Thota, Sri Harsha Yakkala
1234
213
User-Centered Evaluation and Design Suggestions for NFT Marketplaces
S. Viannis Murphy Caxton, K. Naveen, R. Karthik, S. Sathya Bama
1242
214
Online Harassment Detection using Machine Learning
Raj Ahirwar, M. Ajay, N. Sathyabalan, K. Lakshmi
1250
215
C++ Implementation of Intelligent Information Platform (IIP) for Tax Planning of
SMEs under the New Accounting Standards of Abnormal Data Mining
Ruipeng Gu
1253
216
An Automated Self Rating Questionnaire Assessment Tool for the evaluation of
Entrepreneurial Competencies using SVM Algorithm
Aruna P, Christy Sujatha D, Surya Prakash S, Prince R
1258
217
Advanced Deep Learning Techniques with Attention Mechanisms for Acoustic
Emotion Classification
S. Jothimani, S. N. Sangeethaa, K. Premalatha
1263
218
Fake News Detection using Voting Ensemble Classifier
Reshmi T S, Daniel Madan Raja S
1269
219
NBA web portal: A Comprehensive Survey on NBA Accreditation and MERN Stack
for the Purpose of Implementing a Portal
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220
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221
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25. 222
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Analysis of Student Sentiment Level using PerceptualNeuralBoltzmann Machine
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Corn Leaf Disease Detection; A Survey
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227
Forest Fire Detection and Prediction – Survey
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Multiple Transfer Learning-AI Design for Lung Disease-Pneumothorax and Tension
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229
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230
UML-based Online Interactive Learning Platform Development and Data
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Cong Wang, Qing Ma, Wei Guo
1344
231
Multi Class Ensemble Classification for Crop Recommendation
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232
Feature Point Matching for Human-Computer Interaction Multi-Feature Gesture
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1354
233
Application of SPSS Cluster Analysis in the Smart Promotion Strategies of Cross-
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1358
234
Comprehensive Data Collection and Feedback Algorithm for Smart Music Online
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1364
235
Intelligent Analysis of the Relationship Between the Topological Design of the
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236
Construction and Implementation of a Data-Oriented Platform for Rural Ecological
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A Combined Deep CNN-LSTM Network for Chromosome Classification for
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238
Detection and Diagnosis of Meningioma Brain Tumors using Proposed CNN
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1384

26. 239
Facial Recognition based Attendance
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1390
240
Construction of Campus Football Information Service Platform under the
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1396
241
A Novel IoT based Home Sensing System using Sensor Networks
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242
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243
The Commonalities in Social Engineering Attacks through E- Commerce Shopping
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244
Multiple Class Breast Cancer Detection Method based on Deep Learning and
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245
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246
HDP-IoT:An IoT Framework for Cardiac Status Prediction System using Machine
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1427
247
On Automatic Target Recognition (ATR) using Inverse Synthetic Aperture Radar
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248
Optimization of Intelligent Student Educational Smart Cloud Architecture based on
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249
Application of Simple Database Algorithm and Big Data Technology in College
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Multi-port Realization of Modeling Platform for Impact of Negative Financial
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251
Java Programming Implementation of Hierarchical Sharing Architecture of
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252
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253
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1462
254
Efficient Development of Supervised Learning Algorithm for Kidney Stone
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1467

27. 255
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Ghosal, Mohammad Ishrat
1474
256
A Deep Learning-based Approach on Vehicle Detection, Tracking, and Counting
System
N. Rajavinu, B. Swaminathan, Shameer A P, Dwaitha Jagadish, DebaratiGhosal,
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1480
257
Monitoring Novel Corona Virus using Machine Learning
M.Mohan, Vansh Agrawal, Mehak Malik, Atul
1486
258
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261
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1521
264
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1528
265
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1536
266
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1540
267
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268
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Anantadjaya, S. M. K Quadri
1549
269
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270
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271
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1568

28. 273
Prediction of Lung Cancer using Data Mining Techniques
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1574
274
Predicting Employee Attrition through Machine Learning
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1579
275
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276
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277
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Platform Virtual Cloud Online Data Transmission Algorithm in Post- Epidemic Era
Jiaqi Lu
1616

29. Provably Secure Pseudonyms based
Authentication Protocol for Wearable Ubiquitous
Computing Environment
Vincent Omollo Nyangaresi
Faculty of Biological & Physical Sciences, Tom Mboya University College, Homabay, 40300, Kenya
vnyangaresi@tmuc.ac.ke
Abstract— Wireless body area networks and medical servers
exchange sensitive and private patient data that should be
protected from malicious entities. To achieve this, numerous
security solutions have been presented in literature. However,
some of these security protocols have many security
vulnerabilities that expose the wireless body area networks to
attacks. In addition, the high computation, storage and
communication overheads in some of the current schemes
render them unsuitable for resource constrained sensor hubs.
As such, the protection of exchanged packets is necessary but
challenging. In this paper, a protocol that leverages on elliptic
curve cryptography and pseudonyms is developed to address
some of these issues. The protocol is demonstrated to be secure
under the Burrows–Abadi–Needham (BAN) logic. In addition,
it is shown to be resilient against some typical attacks models in
wireless body area networks. Moreover, its computation and
communication complexities are the lowest among other
relatedscheme.
Keywords — Authentication, ECC, privacy, protocol, pseudonyms,
security.
I. INTRODUCTION
The proliferation of mobile devices and sensors has led to
the increase in the deployment of these devices in many
application domains. One of such application areas is in
smart health where medical sensors can be implanted in the
patient’s body or placed in the vicinity of the patient to
provide remote monitoring. The collected sensor data is then
forwarded to the hospital medical servers for analysis and
appropriate response. These sensors form the Wireless Body
Area Network (WBAN) which has been deployed to offer
real-time healthcare monitoring for the elderly as well as
patients. As explained in [1], the data in WBANs is highly
sensitive and confidential. As such, it is critical that the
communicating parties establish some trust levels before
exchanging the collected data [2]. Privacy is another goal
that should be upheld as the sensors communicate with
remote medical servers. Unfortunately, the transmission of
these messages is over open public channels which are
vulnerable to numerous attacks [3]. As such, numerous
adversarial attacks can be launched against WBANs [1].
According to [4], these attacks can be categorized as passive
and active, and they render healthcare security quite
challenging.
As explained in [5], strong authentication protocols and
other security solutions are necessary for the successful
deployment of WBANs. In addition, there is need for secure
encryption algorithms to prevent any malicious access to
patient’s data [6]. To prevent adversarial tracking of the
transmitted data, the communication process should be
anonymous. However, the extreme resource constrained
nature of the sensors in terms of power, computation,
memory and communication places some restrictions on the
deployable cryptographic operations. To this end, this paper
makes the following contributions:
 A protocol that leverages on elliptic curve
cryptography and pseudonyms is developed to
thwart traceability attacks.
 Time-stamping is deployed in all exchanged
messages to protect against packet replay attacks.
 Elaborate formal security analysis is carried out to
demonstrate the trustworthiness as well as resilient
of the exchanged messages against eavesdropping
attacks.
 Informal security analysis is executed to show the
resilience of the proposed protocol against typical
WBANs attack models.
 The performance and comparative evaluation is
carried out to demonstrate the lightweight nature of
the proposed protocol.
The rest of this paper is structured as follows: Section II
presents the related work, while Section III discusses the
system model of this protocol. On the other hand, Section
IV gives a presentation of the analysis and comparative
evaluation while Section V concludes the paper and
provides future research directions.
II. RELATED WORK
Security, privacy and performance challenges in WBANs
have attracted much attention from the research community
and hence numerous protocols have been developed. For
instance, body-motion based security protocol is presented
in [7], while a Diffie–Hellman (DH) anonymous
authentication scheme is developed in [8]. On the other
hand, a biometric-based authentication and key management
protocol is introduced in [9]. However, the approach in [9]
has high communication overheads. On the other hand,
blockchain technology has been deployed for security
scheme in [10]. Unfortunately, this protocol has high
computation overheads and high storage requirements due
to the deployed blockchains [11]. To ensure anonymous and
efficient WBAN communication, an authentication scheme
is presented in [12]. In addition, digital signatures have been
deployed in [13], while an Elliptic Curve Cryptosystem
(ECC) based scheme is presented in [14]. However, the
approach in [13] uses asymmetric key generation techniques
which call for pairs of private and public keys, effectively
Proceedings of the Fifth International Conference on Inventive Computation Technologies (ICICT 2022)
DVD Part Number: CFP22F70-DVD; ISBN:978-1-6654-0836-3
978-1-6654-0837-0/22/$31.00 ©2022 IEEE 1

30. rendering it complicated and computationally extensive
[15]. For the scheme in [14], forward key secrecy and
privacy cannot be assured. In addition, it is susceptible to
user impersonation attacks.
To address some of the privacy and security constraints in
WBANs, two authentication protocols have been presented
in [16] and [17]. However, these protocols have relatively
high communication and computation overheads and may
not withstand impersonation attacks. In addition, they do not
offer untraceability and forward key secrecy. Although the
scheme in [18] provides anonymity and efficiency during
the authentication process, it cannot withstand
impersonation attacks. To curb this challenge, an improved
authentication protocol is presented in [19]. Based on
bilinear pairing operations, two authentication protocols are
developed in [20] and [21]. Although these protocols offer
anonymity, the bilinear pairing operations render these two
schemes computationally extensive [22].
III. SYSTEM MODEL
The Body Sensor Units (BSUs), Data Aggregator (DA),
Gateway Node (GWN), Hospital Medical Server (HMS) and
Administrator (Adm) are the main entities in the proposed
protocol. Here, the BSUs measure various bio-medical data,
while the DA amalgamates data from all the BSUs that it
then forwards to the HMS.
On its part, the HMS analyzes the received data and
appropriate response is initiated. Some of these responses
may be initiated by the Adm, who is the medical expert at
the remote hospital. The GWN generates the required
security tokens to enable the BSUs and the HMS
communicate securely. Table 1 presents the notations used
in this paper, including their descriptions.
TABLE 1. NOTATIONS
Symbol Description
p A prime denotingthe size ofthe
finite field
α, β Elliptic curveparameters
δ (xp, yp) Point generator
σ Order of the base point generator δ
φ Co-factor
GMK GWN master key
GV GWN privatekey
GU GWN public key
Ri Random numbers
|| Concatenationoperation
⊕ XOR operation
IDB Identityofthe BSU
IDA Administrator identity
SKA Administrator’s secret key
TSPi Timestamps
SBG Sharedkey between BSU andGWN
ϕBA Sharedsession key between BSU
andadministrator
The proposed protocol is composed of four major phases,
which include registration, login, mutual authentication and
key negotiation phase. The specific details of these phases
are discussed in the sub-sections below.
A. Registration phase
This phase comprises of both BSU and administrator
registration. At the onset, the GWN generates security
parameter set {p, α, β, δ, σ, φ}. Essentially, these are the
ECC encryption parameters that are deployed to derive other
security parameters. Next, the GWN generates its secret key
GMK and private-public key pair {GV, GU}.
BSU Registration: The following four steps are employed
to register the BSU to its respective GWN.
Step 1: The BSU generates random number R1 and
determines the current timestamp TSP1. It uses these
parameters together with the shared key between the BSU
and GWN to derive parameters A1 = R1 ⊕ SBG and A2 = h
(SBG ||R1||IDB||TSP1). Finally, it constructs registration request
message RM1 = {IDB, A1, A2, TSP1} that is then forwarded
to the GWN over public channels as shown in Fig.2.
Step 2: Upon receiving message RM1, the GWN validates
the freshness of this message using timestamp TSP1. The
session is terminated on condition that RM1 fails the
freshness check.
Fig. 2: Registration Phase
Otherwise, the GWN derives R1
*
= A1⊕ SBG followed by
the confirmation of whether A2 h (SBG||R1
*
||IDB||TSP1).
Here, the session is terminated if this verification fails.
However, if the verification is successful, the GWN
computes parameters B1 = h (IDB||GMK) and B2 = B1⊕ h
(IDB||SBG).
Step 3: The GWN determines the current timestamp TSP2
that it utilizes to derive parameter B3 = h (B1||SBG ||TSP2). It
then composes registration response message RM2 = {B2,
B3, TSP2,p, α, β, δ, σ, φ, GU} that is forwarded to the BSU.
Step 4: On receiving message RM2, its freshness is checked
using timestamp TSP2 such that the session is dropped if the
BSUs
GWN
DA HMS Adm
Fig. 1: Communication Model
BSU
Generate R1 &
determine TSP1
Derive A1& A2
Construct RM1
GWN
{RM1}
Validate TSP1
Derive R1
*
& verify A2
Compute B1 & B2
Determine TSP2
Derive B3
Compose RM2
{RM2}
Validate TSP2
Re-compute B1
*
Validate B3
Store {B1, p, α, β, δ, σ, φ, GU}
HMS
Select R2 & IDA
Compute C1
Construct RM3
{RM3}
Compute C2 & C3
Construct RM4
{RM4}
Store {R2, C1, C3, p, α, β,
δ, σ, φ, GU} in SC
Proceedings of the Fifth International Conference on Inventive Computation Technologies (ICICT 2022)
DVD Part Number: CFP22F70-DVD; ISBN:978-1-6654-0836-3
978-1-6654-0837-0/22/$31.00 ©2022 IEEE 2

31. message fails this check. Otherwise, the BSU re-computes
B1
*
= B2 ⊕h (IDB|| SBG). It then checks whether B3 = h
(B1
*
||SBG ||TSP2) such that the session is dropped if this
verification fails. Otherwise, the BSU stores parameter set
{B1, p, α, β, δ, σ, φ, GU} in its memory.
Administrator Registration: The following three steps are
executed to register the hospital medical server
administrator to the GWN.
Step 1: The administrator Aj selects random number R2 and
identity IDA. It then uses these values to derive parameter
C1 = h (R1||IDA ||SKA). Next, it constructs registration
request message RM3 = {IDA, C1} that it forwards to the
GWN over some secure channels as shown in Fig.2.
Step 2: Upon receiving message RM3, the GWN derives C2
= h (IDA ||GMK) and C3 = C2 ⊕ C1. Finally, it constructs
registration response message RM4 = {C3, p, α, β, δ, σ, φ,
GU} that is forwarded to the administrator over secure
channels.
Step 3: On getting message RM4, the administrator
combines the security values in RM4 with random number
R2. Thereafter, this parameter set {R2, C1, C3, p, α, β, δ, σ, φ,
GU} is inserted into the smart card, SC.
B. Login Phase
Whenever the hospital medical server administrator wants to
access the BSU collected data, login is executed. To
accomplish this, the smart card SC is utilized. The following
three steps are followed during the login process.
Step 1: The administrator inserts the SC into the card reader
followed by the input of identity IDA and secret key SKA.
Step 2: Using the stored random number R1 and the
inserted parameters, the SC derives parameter C1
*
= h
(R1||IDA||SKA).
Step 3: Using the stored security parameter C1, the SC
verifies whether C1
*
= C1. Here, the login attempt is rejected
if this verification is not successful. Otherwise, the
legitimacy of the administrator is confirmed.
C. Authentication and Key Negotiation
After successful login phase, the administrator is now ready
to access the BSU collected data. However, strong mutual
authentication must be executed between the administrator
and the BSU before this access is granted. In addition, the
two must agree on some session key to be deployed for
traffic protection. The following 6 steps are carried out
during this authentication and key negotiation phase.
Step 1: Using security parameter C1
*
derived during the
login phase, the administrator through the SC computes C2
= C3 ⊕C1
*
. The SC then selects some random number R3
[1, σ-1] and determines the current timestamp TSP3. Using
these values, the SC derives parameters D1 = (R3.δ), D2 = h
(TSP3||R3.GU), D3 = (IDA, IDB)⊕D2 and D4 = h
(D1||D3||C2||TSP3). The SC composes authentication request
message AM1 = {D1, D3, D4, TSP3} and forwards it to the
BSU over public channels as shown in Fig.3.
Step 2: After obtaining message AM1, the BSU confirms its
freshness using timestamp TSP3 such that the authentication
request is rejected if this test flops. Otherwise, the BSU
selects randomnumber R4 [1, σ-1] and determines current
timestamp TSP4. These values are then used to compute
parameters E1 = (TSP4.δ) and E2 = h (E1||D4||B1||TSP4).
Finally, the BSU constructs authentication request message
AM2 = {D1, D3, D4, TSP3, E1, E2, TSP4} that it transmits to the
GWN over public channels.
Step 3: On receiving message AM2, its freshness is checked
using timestamps TSP3 and TSP4 such that the request is
rejected if these two timestamps fail this test. Otherwise, the
GWN derives security parameter D2
*
= h (TSP3||GV . D1),
(IDA
*
, IDB
*
) = D3 ⊕D2
*
, C2
*
= h (IDA
*
||GMK) and B1
*
= h
(IDB
*
||GMK).
Step 4: Using the computed parameters, the GWN checks if
D4 h (D1||D3||C2
*
||TSP3) such that the request is rejected
when this validation is unsuccessful. Otherwise, it proceeds
to confirm if E2 h (E1||D4||B1
*
||TSP4). Provided that this
verification is unsuccessful, the request is terminated.
Otherwise, the GWN proceeds to compute parameters E3 =
h (D1||B1||E2||E1 ||TSP4) and E4 = h (E1||C2||D4||D1||TSP3).
Finally, it composes authentication response message AM3
= {E3, E4} that it forwards to the BSU.
Step 5: Upon obtaining message AM3, the BSU uses
parameter D1 sent by the administrator in message AM1 to
check if E3 h (D1||B1||E2 ||E1||TSP4). Here, the request is
dropped if the verification flops. Otherwise, the BSU
computes the session key ϕBA = h (R4.D1). Since D1 =
(R3.δ), the session key can also be written as ϕBA = h (R3. R4
. δ). Finally, it composes authentication response message
AM4 = {E1, E4} that it transmits over to the administrator.
Fig. 3: Authentication and Key Negotiation
Step 6: After receiving message AM4, the administrator
deploys parameter E1 obtained from the BSU to check if E4
h (E1||C2||D4||D1||TSP3). Here, the message is rejected when
this validation fails. Otherwise, the administrator re-
computes the shared session key ϕBA
*
= h (R3.R4.δ).
IV. ANALYSIS AND COMPARATIVE EVALUATION
The formal, informal and performance evaluation of the
proposed protocolare discussed in this section as follows.
Adm BSU GW
N
Derive C2 & select R3
Determine TSP3
Compute D1, D2, D3 & D1
Compose AM1
{AM1}
Validate TSP3 & choose R4
Determine TSP4
Derive E1 & E2
Construct AM2
{AM2}
Validate TSP3 & TSP4
Compute D2
*
, IDA
*
, IDB
*
,
C2
*
& B1
*
Verify D4 & E2
Derive E3 & E4
Compose AM3
{AM3}
Validate E3
Derive ϕBA
Construct AM4
Validate E4
Derive ϕBA
*
{AM4}
Proceedings of the Fifth International Conference on Inventive Computation Technologies (ICICT 2022)
DVD Part Number: CFP22F70-DVD; ISBN:978-1-6654-0836-3
978-1-6654-0837-0/22/$31.00 ©2022 IEEE 3

32. A. Formal Security Evaluation
In this section, the Burrows–Abadi–Needham (BAN) is
deployed to demonstrate the trustworthiness as well as
resilient of the exchanged messages against eavesdropping
attacks. To accomplish this, the notations and logic rules in
Table 2 and Table 3 are deployed.
TABLE 2. BAN LOGIC NOTATIONS
Symbol Description
A| B A believes B
A ⨞ A sees B
A| ~ B A once saidB (A sent B)
A|⇒ B A controls B
A ↔ A andC communicate usingshared
key z
#B B is fresh
→ C z is the public key of C
{B}z Message B is encryptedusing z
Message B is encipheredusing
private key z
Suppose that GWN is a trustworthy network entity, and it
believes that the adminsitrator has said message B which it
also believes to be fresh. As such, the GWN can transmit
message B to the BSU. Similarly, suppose that the BSU
believes that message B is fresh and that the GWN once said
B.
TABLE 3. BAN LOGIC POSTULATES
Rule Description
Freshness rule (FR) |
|
Jurisdiction rule (JR) | ⇒ | |
|
⨞ rule (⨞ | → ⨞
⨞
,
| ↔ ⨞
⨞
,
| → ⨞
⨞
,
| introductionrule (| ) | → ⨞
| |
,
| ↔ ⨞
| |
,
| eliminationrule (| ) | | | B
| |
# () – introductionrule (# IR)
|
↔ introduction rule (IR) | | |
| A ↔
Eliminationrule (ER) | |
| |
,
| |
| |
,
|
|
,
⨞
⨞
,
|
|
Consequently, the BSU believes that the administrator
(Adm) said B. This is represented in BAN logic format
(BLF1) as follows.
BLF1:
| | | | | |
| |
Using the | elimination rule, BLF1 is simlified to BLF2,
which is the same as the message that BSU transmits to the
GWN.
BLF2:
| | | |
| |
Suppose that the GWN believes that BSU once said another
message B, and it also believes that this B is fresh. Then, the
GWN would transmit B to the Adm. Similalrly, if the Adm
believes B is fresh and that GWN once said B, then the Adm
believes BSU said B. Using the same argment, BLF3 is
obtained.
BLF3:
| | | |
| |
To show that the administrator and the BSU negotiate
shared session key, the following goals are formulated:
Goal 1: A | A ↔ B
Goal 2: B | A ↔ B
Before the execution of the BAN logic proofs, the
exchanged messages during the authentication and session
key negotiation phase are represented in idealized form (IV)
as shown in Table 4.
TABLE 4. IDEALIZED MESSAGES
Adm → BSU: AM1 = {D1, D3, D4, TSP3}
IV:
BSU → GWN: AM2 ={D1, D3, D4, TSP3, E1, E2, TSP4}
GWN → BSU: AM3 = {E3, E4}
BSU → Adm: AM4 = {E1, E4}
IV: { }
Thereafter, the following twelve initial state assumptions are
made as shown in Table 5.
TABLE 5. INITIAL STATE ASSUMPTIONS
SNo. Assumption
IA1 GWN| #(D1)
IA2 GWN| #(E1)
IA3 BSU| #(D1)
IA4 Adm| #(E1)
IA5 Adm| GWN ↔ A
IA6 GWN| GWN ↔ A
IA7 Adm| GWN ↔ A
IA8 GWN| GWN ↔ A
IA9 BSU| GWN ↔ B
IA10 GWN| GWN ↔ B
IA11 | A | B B | | B
B | A | B
IA12 | B | B A | | B
A | B | B
IA13 BSU| Adm ⇒ D1
IA14 Adm| BSU ⇒ E1
Afterwards, the BAN logic proofs (BLPs) are carried out
based on the initial assumptions, BAN logic rules and
idealized messages as shown in Table 6.
TABLE 6. BAN LOGIC PROOFS
Based on AM2, BLP1 is obtained
BLP1:
GWN ⨞
Usingthe ER in BLP1 yields BLP2 andBLP3:
BLP2: GWN ⨞
BLP3: GWN ⨞
The application ofthe (| ) to bothBLP2 andIA6 results in BLP4:
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33. BLP4: GWN| Adm| {
Accordingto BLP3,IA10 and(| ), BLP5 is obtained:
BLP5: GWN| BSU| {
On the otherhand, the applicationof ER in BLP4 results in BLP6:
BLP6: GWN| Adm| D1
Once again, ER is appliedin BLP5 toyieldBLP7:
BLP7: GWN| BSU| E1
Based on IA1, BLP6 andthe (| ),BLP8 is obtained:
BLP8: GWN| Adm| D1
On the other hand, the application of (| ) to both IA2 and BLP7 results in
BLP9:
BLP9: GWN| BSU| E1
Based on AM3 and IA11, it can be shown the BSU believes GWN, which in
turn believes message D1. Similarly, BSU believes Adm, which in turn
believes message D1. In particular, basedon AM3, BLP10 is obtained:
BLP10: BSU ⨞
ApplyingER on BLP10 results in BLP11:
BLP11: BSU ⨞
On the otherhand, the applicationof (| ) to BLP11 andIA9 yields BLP12:
BLP12: BSU| GWN | }
ApplyingER on BLP12 yields BLP13:
BLP13: BSU| GWN| D1
However, usingthe (| ) on bothIA3 andBLP13 yields BLP14:
BLP14: BSU| GWN| D1
Accordingto BLP8,BLP14 andIA11, BLP15 is obtained:
BLP15: BSU| Adm| D1
On the other hand, the application of (| ) on BLP15 and IA3 results in
BLP16:
BLP16: BSU| Adm| D1
Usingthe JR on both BLP16 andIA13 yields BLP17:
BLP17: BSU| D1
Since R4 is stochastically generated by the BSU, then in accordance with (#
IR), BLP18 is obtained:
BLP18: BSU| # (R4)
Based on the (# IR),BLP18, IA3 andIA5, BLP19 results:
BLP19: BSU| # (ϕBA)
However, accordingtoIR, BLP17 andBLP19, BLP20 is obtained:
BLP20: B | B
ϕ
↔ A
Basically, proofs BLP18 toBLP20 proofs Goal 1.
Using AM4, it can be shown that the Adm believes GWN, which in turn
believes in message E1. As such, based on IA12, it can be shown that the
Adm believes BSU, which in turn believes message E1. Specifically, based
on AM4, BLP21 is obtained:
BLP21: Adm ⨞ { }
The application ofER on BLP21 results in BLP22:
BLP22: Adm ⨞ { }
On the otherhand, applying (| ) on bothBLP22 andIA7 yields BLP23:
BLP23: Adm| | { }
Usingthe ER on BLP23 results in
BLP24: Adm| B | E1
Applyingthe (| ) onbothBLP23 andIA4 yields BLP25:
BLP25: Adm| | E1
Accordingto BLP25, BLP9 andIA12, BLP26 is obtained:
BLP26: Adm| B | E1
On the other hand, the application of (| ) on BLP26 and IA4 yields
BLP27:
BLP27: Adm| B | E1
UsingJR on both BLP27 andIA14 results in BLP28:
BLP28: Adm| E1
Since R4 is randomly generated by the Adm, then by (# IR), BLP29 is
obtained:
BLP29: Adm| #(R4)
On the otherhand, using (# IR) on BLP29, IA4 andIA6 results in BLP30:
BLP30: Adm| #(ϕBA)
Finally, applying IR on bothBLP27 andBLP30 yields BLP31:
BLP31: A | B
ϕ
↔ A
In essence, BLP29 to BLP31 proof Goal 2. Therefore, the
two security goals are successfully achieved, and hence the
proposed protocolis provably secure under the BAN logic.
B. Informal security Analysis
In this section, the proposed protocol is shown to be resilient
against numerous attacks. To accomplish this, typical
WBANs attack models are deployed as discussed below.
Lemma 1: The proposed protocol is robust against
impersonation attacks.
Proof: Suppose that an attacker is interested in
masquarading as the administrator. To achieve this, an
attempt is made to construct message AM1 = {D1, D3, D4,
TSP3}. Here, D1 = (R3.δ), D2 = h (TSP3||R3.GU), D3 = (IDA ,
IDB)⊕D2, D4 = h (D1||D3||C2||TSP3) and C2 = h (IDA||GMK).
Clearly, this requires random number R3, point generator δ,
GWN public key GU , identities IDA and IDB, as well as the
GWN master key GMK. Since all these security parameters
are unavailable to the adversary,this attack flops.
Lemma 2: Traceability attacks are prevented in this
protocol.
Proof: The aim of this attack is to track administrators or
BSUs based on their identities. However, during the
authentication and key agreement phase, these identities are
sufficiently protected. For instance, message AM1 = {D1,
D3, D4, TSP3} is sent by the administrator towards the BSU.
Although the administrator and BSU identities are contained
in parameter D3, where D3 = (IDA , IDB)⊕D2, they are
masked with hashed parameter D2. Similarly, these
identities cannot be easily determined from message AM4 =
{E1, E4 } that is sent from the BSU towards the
administrator.
Lemma 3: The proposed protocol is robust against smart
card loss attacks.
Proof: Suppose that an attacker has obtained the
administrator’s smart card and wants to compose
message AM1 = {D1, D3, D4, TSP3} to send to the
unsuspecting BSU. Here, D1, D3 and D4 are derived as in
Lemma 1. Evidently, parameter C1
*
derived during the login
phase is required to compute parameter C2 = C3 ⊕C1
*
,
which is one of the components of parameter D4. As such,
this attack fails.
Lemma 4: Packet replay attacks are thwarted in the
proposed protocol.
Proof: The goal of this attack is to capture the exchanged
messages, modify them and forward them to the
unsuspecting receivers. The assumption made is that an
attacker has captured messages AM1, AM2, AM3 and AM4,
where AM1 = {D1, D3, D4, TSP3}, AM2 = {D1, D3, D4, TSP3,
E1, E2, TSP4}, AM3 = {E3, E4}, AM4 = {E1, E4 }, E1 = (TSP4 .
δ), E3 = h (D1||B1||E2||E1||TSP4) and E4 = h
(E1||C2||D4||D1||TSP3). Evidently, all these messages
incorporate timestamps TSP3 and TSP4. Consequently, any
replayed message will fail the freshness checks at the
receiver side.
C. Performance Evaluation
In this section, the performance of the proposed protocol is
valuated using computation and communication
complexities as discussed below.
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34. Computation complexity: To compute this performance
metric, the execution time for the various cryptographic
operations during authentication and key agreement phase is
derived. During this phase, 5 hashing operations (TH) and 3
ECC scalar multiplication (TEM) operations are executed at
the Adm side. On the other hand, 3TH and 2TEM operations
are executed at the BSU. In addition, 7TH and 1TEM
operations are executed at the GWN. As such, the proposed
protocol requires 15TH and 6TEM operations. Here, the SHA-
1 TH = 0.0394 ms and TEM = 3.66 ms. As such, the proposed
protocol takes 22.55 ms during the authentication and key
negotiation phase. This is depicted in Fig. 4 below. On the
other hand, the schemes in [17], [16], [8] and [9] take 33.12
ms, 94.96 ms, 24.15 ms and 27.66 ms respectively. Based
on these values, it is evident that the proposed protocol has
the lowest computation complexity. As such, it is the most
suitable for deployment in the computation-limited sensor
hubs.
Fig. 4: Computation Conplexities
Communication complexity: The sizes of the exchanged
messages during the authentication and key agreement
phase are considered in the derivation of this metric. During
this phase, messages AM1, AM2, AM3 and AM4 are
exchanged among the Adm, BSU and GWN. Here, AM1 =
{D1, D3, D4, TSP3}, AM2 = {D1, D3, D4, TSP3, E1, E2, TSP4},
AM3 = {E3, E4} and AM4 = {E1, E4 }. Based on the values
in [23], the sizes of hash values, timestamps, random
numbers and identities are 160 bits, 32 bits, 128 bits and
160 bits respectively. Here, the sizes of these messages
are derived as follows:
AM1: D1 = 128, D3 = D4 =160, TSP3 =32
AM2: D1 = 128, D3 = D4 = E2 =160, TSP3 = TSP4 =E1 = 32
AM3: E3 = E4=160
AM4 is E1 =32, E4 = 160
As such, AM1 = 480 bits, AM2 = 704 bits, AM3 =320 bits
and AM4 = 192 bits. Consequently, the total communication
complexity of the proposed protocol is 1696 bits, as shown
in Fig. 5.
Fig. 5: Communication Complexities
However, the communication complexities of the schemes
in [17], [16], [8] and [9] are 1824 bits, 4832 bits, 2016 bits
and 4008 bits respectively. Therefore, the proposed protocol
has the lowest communication complexity. Consequently, it
is the most suitable for deployment in communication-
limited sensornodes.
V. CONCLUSION AND FUTURE WORK
Wireless body area networks have stringent privacy, trust
and security requirements that must be fulfilled for wider
adoption of these networks. Although security solutions
such as cryptography can be deployed to boost trust among
the communicating entities, most of the current
cryptographic techniques are unsuitable for body sensor
units due to high computation complexities. Owing to the
sensitivity of the exchanged packets, anonymity of the
communicating entities must also be upheld. The developed
protocol has been demonstrated to be formally secure under
the BAN logic model. In addition, its resilience against
common attack models in wireless body area networks has
been elaborated. Future research directions may include the
evaluation of this protocol against other attack models that
were not within the scope of the current work.
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36. Inverse Reinforcement Learning via Deep Gaussian
Process for Reactive Collision Avoidance in
Dynamic Environments
Saugat Shahi
Department of IT Convergence Engineering
Kumoh National Institute of Technology
Gumi, Korea
irl5485@kumoh.ac.kr
Heoncheol Lee
Department of IT Convergence Engineering
Kumoh National Institute of Technology
Gumi, Korea
hclee@kumoh.ac.kr
Abstract— This paper deals with an automatic vehicle which
navigates from the start to goal point avoiding the moving as
well as static obstacles in dynamic environments. This research
study proposes a novel approach for reactive collision avoidance
based on Inverse Reinforcement Learning(IRL) whichcanlearn
complex reward structures with few demonstrations based on
Deep Gaussian Process (DPG) to inherit the features from the
normal distribution of the data collected from the LIDAR
sensor. The simulation results showed that the accuracy of the
proposed approach was higher than that of other approaches.
Keywords— Dynamic Environment; Inverse Reinforcement
Learning; Deep Gaussian Process; Reactive Collision Avoidance
I. INTRODUCTION
The concept of the collision avoidance is to ensure the major
safety for the autonomous mobile robots/vehicles which aims
to optimize the collision-free navigation [1]. In the recent
years multiple approaches has been made to develop a better
collision avoidance system and achieved a remarkable result.
A collision free navigation in a static environment (non-
moving obstacles) is quite straight forward task and
researchers has given better accuracy while environment with
dynamic (moving) obstacles is still a field that needs to be
discussed in terms of collision avoidance. It is tough to predict
the nature of the moving objects randomly and to enable
mobile robots to navigate towards the goal point avoiding
these dynamic bodies is quite challenging [2].
To overcome these problems, researchers have proposed
many models in the related fields. Socially Adaptive Path
Planning in Human Environments Using Inverse
Reinforcement Learning [3] proposed generating human-like
path trajectory in a dynamic environment via path planning
modules, however the predefined path was unable to minimize
the errors between the reference and actual path to avoid
collision. Socially compliant mobile robot navigation via
inverse reinforcement learning [4] discusses user-defined
features to match the models’ parameters through observed
behavior by tele-operations. Still, it lacks to explore the space
of routes from the robot’s current position to its target position
as quickly as possible. Learning to drive using Inverse
Reinforcement Learning and Deep Q-Networks [5] develops
a system to extract the reward for collision-free motion, but
the learning accuracy of the agent in the environment was
average along with the number of demonstrations. Prediction
of Reward Functions for Deep Reinforcement Learning via
Gaussian Process Regression [6] highlights the technique for
reward acquisition based on sparse Gaussian process for
obstacle avoidance navigation of the mobile robot. The
limited demonstration is still a drawback for the agent to adapt
the environment efficiently. Learn to Make Decision with
Small Data for Autonomous Driving: Deep Gaussian Process
and Feedback Control [7] discusses the regression model on
small dataset and combine the feedback control for
autonomous driving while the dataset volume is a concern for
autonomous vehicle to make decision. Decision making quite
rely on the size of the sample dataset. Fast, On-line Collision
Avoidance for Dynamic Vehicles Using Buffered Voronoi
Cells [8] highlights distributed collision avoidance for
dynamic vehicles based on Voronoi cell and provide an
extension with higher-order dynamics. The noisy relative
position sensor works well but lack of communication
networks minimizes the accuracy of the model. A survey of
robotic motion planning in dynamic environments [9] is a
critical review for velocity-based motion planning such as
artificial potential field, artificial intelligence-based
approaches. It attempts to classify the robotic motion planning
based on technique and their performance.
The major contribution of the paper is summarized as follows:
(1) To propose an Inverse reinforcement learning technique to
extract a reward structure and to develop a collision-free
learning model for the robot to adapt the environment with
static as well as dynamic bodies.
(2) Apply a deep Gaussian process to predict the reward
function from the inherited features based on the dataset
collected from the LIDAR sensor when the robot comes in the
contact with the obstacles navigating through the
environment.
The rest of the paper is organized as follows: In Section II
introduces the limitations and the problems of the collision
avoidance methods along with the robot’s model. Next,
Section III describes the proposed reactive collision avoidance
method which consists of Inverse reinforcement learning
based collision-free model, the sensors applied and the
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