BINDU MADAVI K P
@gitam.edu
Assistant Professor, Department of Computer Science and Engineering
GITAM University
Seeking a challenging position to utilize my skills and abilities in the area of Teaching and education that offers professional growth while being resourceful, innovative, and flexible
EDUCATION
Ph.D. in Computer Science & Engineering, Sir MVIT, VTU,2022
Master of Technology in Computer Science passed out 2013 from SET, Jain University
Bachelor of Engineering in Information Science passed out 2010 from JVIT, VTU
RESEARCH INTERESTS
Cloud Computing, Cryptography, Deep Learning
Scopus Publications
Scopus Publications
K. Krishna Sowjanya and K. P. Bindu Madavi
Springer Nature Switzerland
Madavi K. P. Bindu and Sowjanya K. Krishna
CRC Press
Sowjanya K. Krishna and Madavi K. P. Bindu
CRC Press
Helna Joseph, Erin Manjus, Sujatha Arun Kokatnoor, and K. P. Bindu Madavi
Springer Nature Singapore
Bindu Madavi K. P., Krishna Sowjanya K., Tanvir Habib Sardar, and Ahamed Shafeeq B. M.
Informa UK Limited
K Krishna Sowjanya, K P Bindu Madavi, Gaurav Khater, Aaron Jacob, and Emaduddin Shamim Ahmad
IEEE
VN Manju, Dayana D S, Neha Patwari, Bindu Madavi K P, and Krishna Sowjanya K
IEEE
K. P. Bindu Madavi, K. Krishna Sowjanya, Tanvir H. Sardar, Manoj Seetharama Reddy, and Sri Ram Nimmalapudi
Springer Nature Switzerland
Bettina S Mathew, Aishwarya Chundru, Himanshi Gaur, Bindu Madavi K P, and Krishna Sowjanya K
IEEE
Md Forkan Hossain Fahim, Muhammad Mansur Usman, Md Al Mahedi Hassan, Tanvir Habib Sardar, K. P. Bindu Madavi, and Nirmala Venkatachalam
Springer Nature Switzerland
K Krishna Sowjanya and K P Bindu Madavi
CRC Press
K P Bindu Madavi and K Krishna Sowjanya
CRC Press
Bindu Madavi K P, Krishna Sowjanya K, Neha Patwari, and Shobharani D A
IEEE
Cybersecurity attacks are rising day by day due to the explosive growth of the internet. Many encryption techniques and authentication mechanisms also came into existence to avoid or minimize cybersecurity attacks. However, these traditional encryption algorithms are facing new challenges because of quantum computers. Due to their high computational capacity, quantum computers will be able to decipher the messages which are encrypted by the encryption algorithms. To guard against these sophisticated cyber attacks, the Quantum-Key Distribution (QKD) protocol and the Time-Released Encryption(TRE) algorithms are becoming popular. The paper proposes a Time-Based Quantum Key Distribution Protocol (TB-QKD), that enables a secure key exchange and decryption process between two trusted parties on an arbitrary time. The proposed TB-QKD protocol allows the sender and receiver to share the keys securely through the quantum channel with the help of QKD protocol. The algorithm encryption and decryption times for different messages have been observed and presented. Moreover, this protocol also provides a suitable solution that addresses many vulnerabilities that occur in the domain of data security and confidentiality.
K. P. Bindu Madavi, Panditi Neelaveni, Pujari Rakesh, and Singamsetty Asish
Springer Nature Singapore
Renuka R. Patil, B N Chaithanya, Vamsidhar Yendapalli, K P Bindu Madavi, and K Geetha
CRC Press
K.K. Sowjanya, K.P.B. Madavi, and G. Thahniyath
BENTHAM SCIENCE PUBLISHERS
Personal healthcare has become the most important part of present human life due to the COVID-19 pandemic. The awareness of one’s health is made easily available by adopting IoT wearable devices like Fitbit, smart watches, oximeters, etc. All these devices store sensitive information like a heartbeat, BP, distance traveled, calories burnt, stress levels, location details, etc., and are stored in third-party data servers. These servers are vulnerable to illegitimate users and also have a single point of failure. The personal data of the individuals should be protected along with its integrity. At the same time, the data stored in the servers should be decentralized to overcome the problem of a single point of attack. The objective of this article is to provide a framework that uses SHA-56 for generating the hash code and Blockchain technology to store the data. Thus, providing privacy, security, and integrity for the data.
Bindu Madavi K P, Krishna Sowjanya K, and Neha Patwari
IEEE
Internet of Things (IoT) technology is widely applied in various domains such as agriculture, health, business, etc. IoT devices mainly deal with collecting sensory data and communicating with each other with the help of the Internet. The dependability on the Internet has made these IoT devices more vulnerable to attacks done by third-party users. To ensure privacy, security, and confidentiality for the data generated by these IoT devices, there is a need for cryptographic techniques. Light-Weight Cryptography (LWC) is the most commonly used cryptographic technique to ensure security for the data generated by IoT devices. The LWC techniques consume less power for computation and are most suitable for IoT devices as they have limited capacity in terms of memory and power. This paper proposes an LWC technique for healthcare Wearable IoT device data. In the proposed method, the plain text size is 64 bits which combine the IoT-generated data, i.e., Step count, BP level, Heart rate, etc., into a single plaintext and encrypts the same. The proposed method’s performance is better than the Present LWC technique as it reduces the time for encryption and decryption.
Krishna Sowjanya K, Bindu Madavi K P, Neha Patwari, and Shobharani D A
IEEE
Accurately classifying kidney diseases, such as stones, cysts, tumors, and normal cases, is vital in effective diagnosis and treatment planning. A method for multi class classification of kidney conditions using Convolutional Neural Networks (CNNs) is proposed in this paper. The main aim is to develop a system, termed DeepKidney, that can accurately classify medical imaging data automatically. This study focuses on the multiclass classification of kidney stones, cysts, tumors, and normal cases using CNNs. We propose a novel approach called DeepKidney, which utilizes CNNs to analyze medical imaging data and extract relevant features for classification. A large and diverse dataset comprising kidney images representing different conditions is used for training the CNN model. DeepKidney aims to achieve high classification accuracy and improve diagnostic outcomes. This approach provides a comprehensive solution for distinguishing between different kidney conditions, aiding in precise diagnoses. DeepKidney's implementation has the potential to increase kidney disease classification's precision and effectiveness, resulting in better patient outcomes and less work for medical professionals.
Krishna Sowjanya K, Bindu Madavi K P, Neha Patwari, Shobharani D A, and Manju V N
IEEE
Time-released encryption (TRE) is a cryptographic technique that enables encrypted data to be automatically decrypted or made accessible after a certain period of time. The receiver is usually made known the decryption time or release time of the encrypted text. TRE uses a time delay between encryption and decryption to provide an additional layer of security. TRE produces a higher level of security when combined with other cryptographic algorithms. In this paper, the process of encryption and decryption of plain text is performed with the help of the Sequential computation technique of the TRE algorithm along with sender-induced time delay. An additional layer of security is also added by combining the TRE algorithm with two traditional algorithms i.e; RSA and RSA-OAEP to provide security for the data. Both methods are compared and the results are shown accordingly.
K.P. Bindu Madavi and P. Vijayakarthik
Chapman and Hall/CRC
K P Bindu Madavi and P. Vijaya Karthick
IEEE
Data security is a key concern for organizations considering a transfer of their on-premises applications to the cloud. Organizations must shift their security controls from historical perimeter and detection-based technologies to a focus on establishing enhanced protection at the application and data levels to ensure the confidentiality, integrity, and availability of these various systems and datasets. Data integrity is a critical component of cloud data security, preventing unauthorized alteration or removal and guaranteeing that data stays as it was when it was initially uploaded. This article presents a compacting with steganography technique which is used to hide data with substantial security and also perfect invisibility while utilizing a combination of DES, AES, and RC4 encryption methods. The objective of this study is to provide data security using steganography with the Least Significant Bit (LSB) Algorithm and Hybrid Encryption that encrypts user input and conceals it in an image file to provide the highest level of security for messages sent and received.
K. P. Bindu Madavi and P. Vijayakarthick
Springer Singapore
Bindu Madavi
Institute of Advanced Scientific Research