E. GEETHA RANI is working as Assistant Professor in the Department of Computer Science and Engineering, MVJ College of Engineering, Whitefield, Karnataka, Bengaluru. Received Bachelor degree in Information Technology from Koneru Lakshmaiah College of Engineering, Master degree in Computer Science and Engineering from Acharya Nagarjuna University and Pursuing Ph.D in Computer Science and Engineering from GITAM University. Reviewer for many Conferences and Journals. Has 14 years of experience in Teaching and Research and Industry. Having IEEE and SCRS membership. Area of research includes Data Analytics, Communication Network, Cloud Computing and Deep Learning.
EDUCATION
Ph.D (pursuing)(Computer Science Engineering) from December 2019
Gitam University,Nagandenahalli, Bengaluru
Present Status: About to Submit Thesis
#Title of the Ph.D “Data Storage in Cloud Computing for improving security and privacy using Encryption Techniques”
Master of Business Administration (Human Resources)
Acharya Nagarjuna University, Guntur, Andhra Pradesh, Year: 2011 - 2013
M.Tech (Computer Science Engineering)
Acharya Nagarjuna University (ANU), Guntur, Andhra Pradesh, Year: 2008 - 2010
B.Tech (Information Technology)
KL College of Engineering, (ANU), Andhra Pradesh, Year: 2005 - 2008
Diploma (Electronics and Communication Engineering)
KES Polytechnic College for Women, Vijayawada, Andhra Pradesh, Year: 2002 - 2005
SSC (State)
Bishop Azariah School, Vijayawada, Andhra pradesh, Year: 2002
RESEARCH INTERESTS
Cloud Computing
Artificial Intelligence
Machine Learning
Internet of Things
A Reliable Environment with Extensive Advanced Encryption Standard Algorithm in Cloud Computing Geetha Rani E, Chetana Tukkoji Ssrg International Journal of Electronics and Communication Engineering, 2025 Web-based Cloud Computing is widely used to store data. Most firms who are shifting to the cloud find it cost-effective. Despite its popularity, it has presented several security concerns to its users. Cloud Computing data security has become a critical issue that requires prompt response. This paper proposes an appropriate usage of AES and an effective cloud-based data storage solution. The proposed data security solution is implemented by improving the standard AES algorithm. Furthermore, the proposed techniques use de-duplication to save storage space for user data. The Extensive Advanced Encryption Standard (EAES) methodology was applied, and the results were superior to the conventional Advanced Encryption Standard method. The research tries to tackle the issues stated above in stages. Initially, a broad library of strategies addressing the data security problem is explored, and their limitations are noted. The Extensive Advanced Encryption normal technology is used, yielding considerable results compared to the normal Advanced Encryption Standard approach.
FridgeSense: An AI-Powered Solution for Smart Food Tracking and Recipe Planning Sandyarani Vadlamudi, K S Shashikala, Shreeya D, Smriti Ramesh, R Calvin Francis, Geetha Rani E 2025 IEEE 7th International Conference on Computing Communication and Automation Iccca 2025, 2025 Daily refrigerator checks by global households lead them to find new recipes for their cooking. The Fridge Memory & Expiry Tracker uses advanced artificial intelligence to recommend recipes that match available ingredients based on their expiration dates. Through its advanced capabilities the system uses both camera vision technology and OCR functions to automatically identify food products and their expiration dates. The food inventory system operates in real-time and utilizes AI algorithms to suggest recipes which reduce waste and assist users in saving money while planning meals. Through a combination of artificial intelligence and practical kitchen management tools this application delivers preset settings for perishable foods along with personalized inventory tracking that provides expiration date alerts. The system description includes detailed examination and additional information about its operational method and features the expiration date detection system and AI recipe engine for sustainable food planning. The paper outlines the system structure as well as its implementation method and the camera-based mechanism to detect food expiration dates and the AI recipe engine that develops customized sustainable food planning solutions
Secure Framework Optimizes QAES Technique Used for Computing in the Cloud E. Geetha Rani, Dr. Chetana D. Tukkoji Journal of Wireless Mobile Networks Ubiquitous Computing and Dependable Applications, 2024 Several consumers are concerned about the security of their data kept in the cloud, and many see local servers as a safer choice due to perceived control. However, cloud service companies frequently promise greater security procedures and employ dedicated security specialists, making data stored in the cloud potentially more secure. When the data holder expires, new files are saved in the cloud and encrypted with the QAES technology. The data owner then receives the encrypted data request. The sender and user both analyze data before sending encoded documents to the cloud. The key will be used to remove encryption from subsequent data. If users are unable to access the desired data, they should submit a fresh request. The most recent innovation focuses on combining an enhanced form of Quantum Key Distribution (QKD) with AES. This integration resulted in Quantum-AES (QAES), a novel quantum symmetric encryption scheme. QAES is based on the development of a quantum encryption key using dynamic quantum S-Boxes (DQS-Boxes), as opposed to the frequently utilized static S-Boxes. This strategy enhances security. Comparably, time is required to build files faster than they do now. This approach prevents brute force attacks since it uses the QAES algorithm, which provides additional security.
Generative AI-Based Currency Detector for Visually Impaired E Geetha Rani, B Guru Sneha, N Harsha Vardhan, B Sai Kumar, D Anusha, Sandyarani Vadlamudi IEEE International Conference on Signal Processing and Advance Research in Computing Sparc 2024, 2024 A visually challenged person may find it challenging to distinguish between various denominations of currency. For those who are blind, this process is still challenging even though most of the Indian currency is written in unique characters. Portable solutions for isolation have emerged because of a shortage of available tools. This study details the creation and evaluation of a new assistive technology that uses an easy-to-use currency detection system to improve the financial independence of people with visual impairments. The apparatus employs sophisticated image processing techniques and deep learning algorithms to precisely recognize different banknote denominations. A compact, user-friendly interface that provides audio feedback to convey the denomination to the user ensures ease of use and privacy. A portable computer device connected to a high-resolution camera forms the basis of the system architecture. On this device, a convolutional neural network (CNN) model is trained using many datasets of cash photos in various orientations and light conditions. A high recognition accuracy rate is attained by the model, which is essential for real-world uses. Voice commands and tactile buttons work together to make it easy for users to engage with the gadget. Many daily living tasks are made more difficult by the prevalence of visual impairment, particularly those that require the recognition of currency, leaving the affected person dependent on others to complete financial transactions. Its ability to quickly and accurately identify different currencies and output format in audio feedback has proven to be highly beneficial for those with visual impairments who travel or live in multicultural environments. Moreover, positive feedback from user experience evaluations indicates that the system's practical impact extends beyond its technical achievements, with considerable improvements in confidence during financial transactions and ease of use. To ease that dependency, a unique Currency Detector System (CDS) made especially for visually impaired individuals has been created.
OpenCv Based Enhanced Criminal Identification Mechanism E Geetha Rani, Vaishnavi, Taniya Maiti, D Anusha, Sandyarani Vadlamudi, Chetana Tukkoji IEEE International Conference on Signal Processing and Advance Research in Computing Sparc 2024, 2024 This study examines how a facial recognition system might be used in real-world situations to demonstrate its efficacy. The core operation of this system is ensured by meticulously selected datasets that comprise categorized photos. An important part is a carefully constructed file called “simple faces,” which is optimized for necessary libraries such as glob, OS, NumPy, OpenCV, and OS. Important tasks like image processing and matching faces to their corresponding photos are made easier by these frameworks. The study also emphasizes the significance of having a specific file for face detection and uses OpenCV to locate facial features precisely. In addition, a sophisticated face recognition library with strong features detection, encoding, and comparison capabilities is used. This library uses CNNs and other cutting-edge pretrained deep learning models to deliver exceptional facial recognition accuracy and speed.
Peer-to-Peer File Streaming Using Web Sockets Protocol Geetha Rani E, Roshan Jose S, Joel Thomas Chacko, Joshua Paul C, Jeanette Krizelda K Icrtec 2023 Proceedings IEEE International Conference on Recent Trends in Electronics and Communication Upcoming Technologies for Smart Systems, 2023
GEETHA RANI E, CHETANA D T “Using github and grafana: Data visualization in big data”, 2nd International Conference on Computer Vision and Robotics (CVR 2022) During May 21-22 published in “Algorithms for Intelligent Systems” in the Web of Science.
GEETHA RANI E, CHETANA D T “To increase security and privacy, the QAES encryption algorithm is used for storage of data for cloud computing” INDICON 2022 IEEE 19th India Council International Conference, scheduled, during Nov 24-26, 2022 at Cochin, Kerala.
DOI: 10.1109/
GEETHA RANI E, CHETANA D T “A Survey of Recent Cloud Computing Data Security and Privacy Disputes and Defending Strategies”, Congress on Smart Computing Technologies (CSCT 2022) During Dec 11-12 Published in”Smart Innovation and Technologies” in the SCOPUS (Q3) and DBLP.
GEETHA RANI E, MOUNIKA E, Gopala Krishnan C,Tanup Bellam, Bhuvaneswari P, Kanagavalli Rengaraju “Comparative Analysis of Deepfake Video Detection Using Inception Net and Efficient Net (won BEST paper Award)” Fourth International Conference on “Emerging Research in Electronics, Computer Science and Technology” ICERECT – 2022,Financially sponsored by AICTE, New Delhi and Technical Co- sponsored by IEEE Bangalore Section during 26-27, December 2022 at P. E. S. College of Engineering, Mandya
RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)
Published a BOOK on 18/11/22 entitled as The Security Essentials - Data, Network & Computer on Flipkart and
Published a PATENT on 7/11/22 “ IoT and AI based Smart health monitoring wrist device to connect doctor-patient to assist immediate medical attention/guidance for BP, sugar, HB by exchanging data in hybrid cloud” with Application Number-202241063449
Published a PATENT on 5/1/23 “ Machine Learning based non-invasive detection and prevention of anemia at early stages using, image processing and Deep Learning algorithms for all ages of people for Healthy life” with Application Number-202311001191
