FACULTY

Research and Industry-Academia Collaboration

研究・産学連携

SAXENA Deepika

Associate Professor

Affiliation: Department of Computer Science and Engineering/Division of Information Systems

Title: Associate Professor

E-Mail: deepika@u-aizu.ac.jp

Web site: https://scholar.google.com/citations?user=NajK_n8AAAAJ&hl=en

Education

Courses - Undergraduate: Introduction to Software Engineering (ICTG)
C++ Programming (ICTG)
Advanced Software Engineering
Algorithms and Data Structures I

Courses - Graduate

Research

Specialization: Computer system
Information security
High performance computing
Soft computing

Educational Background, Biography: Dr. Deepika Saxena is a researcher and academician in the domain of Computer Science and Engineering. Currently, she is working as an Associate Professor in the Division of Information Systems in the Department of Computer Science and Engineering, The University of Aizu, Japan. Dr. Saxena has received her Ph.D. degree in Computer Science from the National Institute of Technology, Kurukshetra, India; and Post Doc from the Department of Computer Science, Goethe University, Frankfurt, Germany. Her major research interests include Neural networks, Evolutionary algorithms, Scheduling, and Security in cloud computing, Internet traffic management, Resource management, and Quantum machine learning, DataLakes, Dynamic Caching Management. Some of her research findings are published in top-cited journals such as IEEE TSC, IEEE TCC, IEEE TNSM, IEEE TPDS, IEEE Systems Journal, IEEE Communication Letters, IEEE Networking Letters, Neurocomputing, and IET Letters. She was an invited research seminars presenter about her doctoral research work at distinguished international venues, including the QORE Seminar at Imperial College London; the University of Melbourne, Australia; National Sun Yat-Sen University, Taiwan.
She was a visiting researcher at CERN, Geneva, Switzerland during her Postdoctoral period.

Recently, her Ph.D. thesis is awarded for the Best Ph.D. Thesis Award 2023 by The European Federation of Simulation Societies in Europe, EUROSIM 2023. Dr. Saxena has more than 60 publications now which include top peer-reviewed journals, conferences, book chapters, and in these areas. She has research and academic experience working in India, Germany, and Japan. She is a Member of the Institution of Electrical and Electronics Engineers (IEEE) Japan and several IEEE societies. She is appointed as a Guest Editor in Elsevier’s Computers & Electrical Engineering Journal (Q1 Ranking, SCI journal with Impact Factor: 4.152). She is an active review board member of various Q1 and Q2 ranking journals belonging to Elsevier, Springer, IEEE, IET, Wiley, etc., and conferences.

In her doctoral research work, she has addressed critical issues in the cloud environment including high power consumption, resource wastage, inefficient resource allocation, frequent migration of computing instances, security threats, high communication cost, fault-tolerance, sustainability, etc. by proposing and implementing various Artificial Intelligence-based Cloud Resource Prediction and Management models/frameworks/approaches. Specifically, her research work includes Evolutionary Quantum Neural Network (EQNN) and Quantum Blackhole learning-based Hadamard Neural Network (QB-HNN) models which are an intelligent collaboration of computational efficiency of Quantum mechanics and adaptive machine learning capabilities of evolutionary neural networks toward the prediction of a dynamic and extensive range of cloud workloads. An Online Predictive and Multi-objective Load Balancing framework incorporating VM prediction with scaling, resource distribution, on an allocation with VM migration at a unified platform, and allowing interaction among all the intended operations to optimize and tune together for overall performance improvement of cloud services, and Traffic Entropy Learning-based Load Management (TEL-LM) model is proposed which minimizes the effects of losses of inefficient VM allocation that occur due to load prediction errors. Online Secure inter-VM Communication (OSC-MC) and Security Embedded Dynamic Resource Allocation (SEDRA) models are developed for the secure execution of sensitive workloads in a shared computing environment by identifying and terminating malicious VMs and inter-VM links before the occurrence of security threats while minimizing the occurrence of traffic congestion-based attacks. Further, a secure and multi- objective optimization-based VM Placement (SM-VMP) framework is proposed to cater to the perspectives of both cloud users and service providers in conjunction. VM Significance Ranking and Resource Estimation for High Availability Management (SRE-HM) and Fault Tolerance based Elastic Resource Management (FT-ERM) frameworks are proposed for improving the availability of cloud services. Sustainable and Secure Load Management (SaS-LM) and highly Available, Secure, and Sustainable cloud Resource Management models are established to enhance security for users with improved sustainability for data centers. A novel AI-driven VM Threat Prediction Model is developed for Multi-Risks Analysis based Cloud Cybersecurity that identified the VMs threat before its occurrence.

Current Research Theme

Key Topic

Affiliated Academic Society

Dissertation and Published Works

1) Deepika Saxena, Ishu Gupta, Rishabh Gupta, Ashutosh Kumar Singh, and Xiaoqing Wen, “An AI-Driven VM Threat Prediction Model for Multi-Risks Analysis-Based Cloud Cybersecurity” IEEE Transactions on Systems, Man, and Cybernetics: Systems (SCI IF=11.471, Q1). DOI: 10.1109/TSMC.2023.3288081 (Accepted on 12 June 2023)

2) Deepika Saxena, Jitendra Kumar, Ashutosh Kumar Singh, and Stefan Schmid, “Performance Analysis of Machine Learning Centered Workload Prediction Models for Cloud” IEEE Transactions on Parallel and Distributed Computing, 2023 (SCI IF=3.757, Q1). DOI: 10.1109/TPDS.2023.3240567

3) Deepika Saxena, Ashutosh Kumar Singh, Chung-Nan Lee, Rajkumar Buyya,’’A Sustainable and Secure Load Management Model for Green Cloud Data Centre Networks”, Nature Scientific Reports, 2023 (SCI IF=4.379, Q1). DOI: 10.1038/s41598-023-27703-3

4) Smruti Swain, Deepika Saxena, Jatinder Kumar, Ashutosh Kumar Singh, and C. -N. Lee, "An AI-driven Intelligent Traffic Management Model for 6G Cloud Radio Access Networks", in IEEE Wireless Communications Letters, 2023 DOI: 10.1109/LWC.2023.3259942.

5) Ishu Gupta, Deepika Saxena, Ashutosh Kumar Singh, and Chung -Nan Lee "SeCoM: An Outsourced Cloud based Secure Communication Model for Advanced Privacy Preserving Data Computing and Protection", IEEE Systems Journal, 2023 (Accepted), DOI: 10.1109/JSYST.2023.3272611

6) Jatinder Kumar, Rishabh Gupta, Deepika Saxena, Ashutosh Kumar Singh “Power consumption forecast model using ensemble learning for smart grid”, The Journal of Supercomputing, 2023

7) Ashutosh Kumar Singh, Smruti Swain, Deepika Saxena, and C. -N. Lee, "A Bio-Inspired Virtual Machine Placement Toward Sustainable Cloud Resource Management," in IEEE Systems Journal, 2023

8) Deepika Saxena, Ashutosh Kumar Singh, "A High Availability Management Model based on VM Significance Ranking and Resource Estimation for Cloud Applications", IEEE Transactions on Services Computing (SCI IF=11.019, Q1).

9) Deepika Saxena, Ashutosh Kumar Singh, and Rajkumar Buyya, "OP-MLB: An online VM prediction based multi-objective load balancing framework for resource management at cloud datacenter", IEEE Transactions on Cloud Computing, 2021 (SCI IF=5.697, Q1).

10) Deepika Saxena, Ishu Gupta, Ashutosh Kumar Singh, and Chung -Nan Lee "A Fault-Tolerant Elastic Resource Management Framework for High Availability of Cloud Services", IEEE Transactions on Network and Service Management, 2022 (SCI IF=4.758, Q1)

11) Deepika Saxena, Ishu Gupta, Jitendra Kumar, Ashutosh Kumar Singh, and Xiaoqing Wen, "A Secure and Multiobjective Virtual Machine Placement Framework for Cloud Data Center", IEEE Systems Journal, 2021 (SCI IF=4.802, Q1).

12) Ashutosh Kumar Singh, Deepika Saxena, Jitendra Kumar, and Vrinda Gupta, "A Quantum Approach Towards the Adaptive Prediction of Cloud Workloads", IEEE Transactions on Parallel and Distributed Systems, 2021 (SCI IF=3.757, Q1).

13) Deepika Saxena, and Ashutosh Kumar Singh, "OSC-MC: Online Secure Communication Model for Cloud Environment", IEEE Communications Letters, 2021 (SCI IF=3.436, Q1).

14) Deepika Saxena, Ashutosh Kumar Singh, "An Intelligent Traffic Entropy Learning based Load Management Model for Cloud Networks", IEEE Networking Letters, 2022 (SCI IF=3.436, Q1)

15) Rishabh Gupta, Deepika Saxena, and Ashutosh Kumar Singh, "Differential and Tri-Phase adaptive learning-based Privacy-Preserving Model for Medical Data in Cloud Environment", IEEE Networking Letters, 2022 (SCI IF=3.436, Q1).

16) Rishabh Gupta, Deepika Saxena, Ishu Gupta, Ayesha Makkar, and Ashutosh Kumar Singh, "Quantum Machine Learning-Driven Malicious User Prediction Model for Secure Cloud Communications", IEEE Networking Letters, 2022 (SCI IF=3.436, Q1).

17) Rishabh Gupta, Ishu Gupta, Ashutosh Kumar Singh, Deepika Saxena, and Chung-Nan Lee, "An IoT-Centric Data Protection Method for Preserving Security and Privacy in Cloud", IEEE Systems Journal (SCI IF=4.802, Q1)

18) Deepika Saxena, and Ashutosh Kumar Singh, "A proactive autoscaling and energy-efficient VM allocation framework using online multi-resource neural network for cloud data center", Neurocomputing 426, 2021, 248-264 (SCI IF=5.719, Q1).

19) Jitendra Kumar, Deepika Saxena, Ashutosh Kumar Singh, and Anand Mohan, "Biphase adaptive learning-based neural network model for cloud datacenter workload forecasting", Soft Computing 24, no. 19 (2020): 14593-14610 (SCI IF=3.643, Q1).

20) Deepika Saxena, and Ashutosh Kumar Singh, "Security embedded dynamic resource allocation model for cloud data centre", Electronics Letters 56, no. 20 (2020): 1062-1065 (SCI IF=1.314).

21) Deepika Saxena, and Ashutosh Kumar Singh, "OFP-TM: An Online VM Failure Prediction and Tolerance Model Towards High Availability of Cloud Computing Environments", Journal of Supercomputing, 2021 (SCI IF= 2.474, Q2).

22) Rishabh Gupta, Ishu Gupta, Deepika Saxena, and Ashutosh Kumar Singh, "A Differential Approach and Deep Neural Network-based Data Privacy-Preserving Model in Cloud Environment", Journal of Ambient Intelligence & Humanized Computing (SCI IF=3.104, Q1)

23) Ashutosh Kumar Singh, and Deepika Saxena, "A cryptography and machine learning-based authentication for secure data-sharing in federated cloud services environment", Journal of Applied Security Research (2021): 1-24 (SCOPUS IF=0.80).

24) Deepika Saxena, and Ashutosh Kumar Singh, "Auto-adaptive learning-based workload forecasting in dynamic cloud environment", International Journal of Computers and Applications (2020): 1-11 (SCOPUS IF=1.07).

25) Deepika Saxena, and Ashutosh Kumar Singh, "Communication Cost Aware Resource Efficient Load Balancing (CARE-LB) Framework for Cloud Datacenter", Recent Advances in Computer Science and Communications 12 (2020): 1-00 (SCOPUS IF=0.76).

26) Deepika Saxena, R. K. Chauhan, and Ramesh Kait, "Dynamic fair priority optimization task scheduling algorithm in cloud computing: concepts and implementations", International Journal of Computer Network and Information Security 8, no. 2 (2016): 41 (Peer Reviewed).

27) Deepika Saxena, and R. K. Chauhan, "A review on dynamic fair priority task scheduling algorithm in cloud computing", International Journal of Science, Environment and Technology 3, no. 3 (2014): 997-1003 (Peer Reviewed)

28) Ashutosh Kumar Singh, Sakshi Chhabra, Rishabh Gupta, and Deepika Saxena, "A Reliable Client Detection System during Load Balancing for Multi-tenant Cloud Environments ", SN Computer Science (SCI IF=1.29).

Under Revision

29) Deepika Saxena, Rishabh Gupta, Ashutosh Kumar Singh, Athanasios Vasilakos “Emerging VM Threat Detection and Dynamic Workload Prediction-based Resource Allocation Framework for Security Aware Energy-Efficient Cloud Environments”, IEEE Transactions on Automation Science and Engineering (SCI IF=4.938)

Under Review

30) Deepika Saxena, Ashutosh Kumar Singh, "A Real-time Resource Prediction and Self-adaptive VM Scaling Framework for Oversubscribed Cloud Services", IEEE/ACM Transactions on Networking (SCI IF=3.56, Q1)

31) Deepika Saxena, Ashutosh Kumar Singh, Hari Mohan Gaur, Anand Mohan, " A Quantum Blackhole Learning based Hadamard Neural Network Model for Dynamic Resource Reservation in Cloud Environments", IEEE Transactions on Computers (SCI IF=2.663, Q1)

32) Ashutosh Kumar Singh, Rishabh Gupta, Deepika Saxena, Jitendra Kumar, and Stefan Schmid, "Maclaurin Series based Deep Neural Network Model for Preserving Data Privacy in Cloud Infrastructure", IEEE Transactions on Information Theory (SCI IF=2.501, Q1).

33) Ashutosh Kumar Singh, Jatinder Kumar, Rishabh Gupta, Deepika Saxena, " An Ensemble Learning based Power Consumption Prediction Model for Smart Meter", Expert Systems with Applications (SCI IF=6.954, Q1).

34) Ishu Gupta, Deepika Saxena, Ashutosh Kumar Singh, Chung -Nan Lee, “A Secure and Privacy-Preserving Scheme for Healthcare Data Protection in Cloud and IoT Environments", IEEE Transactions on Dependable and Secure Computing (SCI IF=7.691).

35) Ishu Gupta, Deepika Saxena, Ashutosh Kumar Singh, Chung -Nan Lee, "A Multiple Controlled Toffoli Driven Adaptive Quantum Neural Network Model for Dynamic Workload Prediction in Cloud Environments", IEEE Transactions on Neural Networks and Learning Systems (SCI IF=14.255, Q1).

36) Smruti Rekha Swain, Deepika Saxena, Ashutosh Kumar Singh, and Chung-Nan Lee, “A Quantum Machine Learning driven Reliable Resource Allocation Model for Sustainable Cloud Data Center”, IEEE Transactions on Cloud Computing, 2021 (SCI IF=5.697, Q1).

Conferences

37) Deepika Saxena, and Ashutosh Kumar Singh, "Energy aware resource efficient-(EARE) server consolidation framework for cloud datacenter", In Advances in communication and computational technology, pp. 1455-1464. Springer, Singapore, 2021 (Scopus).

38) Deepika Saxena and Ashutosh Kumar Singh, “VM Failure Prediction based Intelligent Resource Management Model for Cloud Environments,” IEEE Second International Conference on Power, Control and Computing Technologies ICPC²T 2022, NIT Raipur, Chhattisgarh. (Scopus, Accepted and presented)

39) Deepika Saxena, and Shilpi Saxena, "Highly advanced cloudlet scheduling algorithm based on Particle Swarm Optimization", In 2015 Eighth International Conference on Contemporary Computing (IC3), pp. 111-116. IEEE, 2015 (Scopus)

40) Deepika Saxena, and Deepika Saxena, "EWSA: An enriched workflow scheduling algorithm in cloud computing", In 2015 International Conference on Computing, Communication and Security (ICCCS), pp. 1-5. IEEE, 2015 (Scopus)

41) Choudhary, Murari, Shashank Jha, Deepika Saxena, and Ashutosh Kumar Singh, "A Review of Fake News Detection Methods using Machine Learning", Second International Conference for Emerging Technology (INCET), pp. 1-5. IEEE, 2021 (Scopus).

42) Varshney, Divyanshu, Burhanuddin Babukhanwala, Javed Khan, Deepika Saxena, and Ashutosh Kumar Singh, "Machine Learning Techniques for Plant Disease Detection", In 2021 Fifth International Conference on Trends in Electronics and Informatics (ICOEI), pp. 1574-1581. IEEE, 2021 (Scopus).

43) Patel, Ramkrishna, Vikas Choudhary, Deepika Saxena, and Ashutosh Kumar Singh, "Review of Stock Prediction Using Machine Learning Techniques", In 2021 Fifth International Conference on Trends in Electronics and Informatics (ICOEI), pp. 840-846. IEEE, 2021 (Scopus).

44) Biswas, Tanmay, Sushil Kumar, Tapaswini Singh, Kapil Gupta, and Deepika Saxena, "A comparative analysis of unequal clustering-based routing protocol in WSNs.", In Soft Computing and Signal Processing, pp. 53-62. Springer, Singapore, 2019 (Scopus).

45) Deepika Saxena, Kunwar Singh Vaisla, and Manmohan Singh Rauthan, "Abstract model of trusted and secure middleware framework for the multi-cloud environment", In International Conference on Advanced Informatics for Computing Research, pp. 469-479. Springer, Singapore, 2018 (Scopus).

46) Patel, Ramkrishna, Vikas Choudhary, Deepika Saxena, and Ashutosh Kumar Singh. "LSTM and NLP Based Forecasting Model for Stock Market Analysis" In First International Conference on Advances in Computing & Future Communication Technologies (ICACFCT-2021)” to be held on 16th-17th, December 2021 in Meerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, (Accepted, Scopus).

47) Manika Sharma, Raman Mittal, Ambuj Bharati, Deepika Saxena, Ashutosh Kumar Singh, “A Survey and Classification on Recommendation Systems”, International Conference on Big Data, Machine Learning, and Applications (BigDML 2021), to be held on December 19-20, 2021 in Silchar, India (Accepted, Scopus).

48) Archana Yadav, Shivam Kushwaha, Jyoti Gupta, Deepika Saxena, and Ashutosh Kumar, "A survey of the workload forecasting methods in cloud computing", 3RD INTERNATIONAL conference on machine learning, advances in computing, renewable energy, and communication, MARC- 2021 (Accepted, Scopus)

49) Ramkrishna Patel, Vikas Choudhary, Deepika Saxena, and Ashutosh Kumar, "LSTM and NLP Based Forecasting Model for Stock Market Analysis", First International Conference on Advances in Computing and Future Communication Technologies – 2021 (ICACFCT 2021) (Accepted, Scopus)

50) Divyanshu Varshney, Burhanuddin Babukhanwala, Javed Khan, Deepika Saxena, and Ashutosh Kumar, "Plant disease detection using machine learning techniques", 3rd IEEE 2022 International Conference of Emerging Technologies (INCET), Belagavi, Karnataka (Accepted, Scopus)

Preprints

51) Deepika Saxena, and Ashutosh Kumar Singh. "An Intelligent Security Centered Resource-Efficient Resource Management Model for Cloud Computing Environments." arXiv preprint arXiv:2210.16602 (2022).

52) Deepika Saxena, and Ashutosh Kumar Singh. "Workload forecasting and resource management models based on machine learning for cloud computing environments." arXiv preprint arXiv:2106.15112 (2021).

52) Rishabh Gupta, Deepika Saxena, and Ashutosh Kumar Singh, "Data Security and Privacy in Cloud Computing: Concepts and Emerging Trends", arXiv preprint arXiv:2108.09508 (2021).

53) Deepika Saxena, Rishabh Gupta, and Ashutosh Kumar Singh, "A Survey and Comparative Study on Multi-Cloud Architectures: Emerging Issues and Challenges for Cloud Federation", arXiv preprint arXiv:2108.12831 (2021).

The aforementioned information is also available at Google Scholar and Research Gate

Last updated: 2024.04.26