IJETE VOLUME 1, ISSUE 2 JUNE – 2026
IJETEV1I2A001 - SECURE MULTIMEDIA CONTENT SHARING USING HYBRID ECC-AES ENCRYPTION WITH REAL-TIME ACCESS CONTROL
AUTHORS : Sathiyapriya P, Muthusamy P, Kavya M, Priyadharshini S, Rohini M
ABSTRACT – In the modern digital era, secure sharing of multimedia content such as audio, images, and videos has become a critical requirement in communication and information exchange. Traditional image-based steganographic techniques limit scalability and are inefficient for handling large multimedia files. To address these challenges, this project presents a robust and scalable secure multimedia content sharing framework that integrates advanced steganography with hybrid cryptographic techniques. The proposed system embeds audio data within video files instead of static images, enabling enhanced flexibility and improved capacity for large-scale multimedia protection. The video is first decomposed into frames, and selected frames undergo Discrete Wavelet Transform (DWT)-based audio embedding. To further strengthen security, a hybrid encryption approach is employed, where Elliptic Curve Cryptography (ECC) ensures secure key
generation and the Advanced Encryption Standard (AES) provides efficient data
encryption. This dual layer security mechanism guarantees confidentiality, integrity, and resistance to unauthorized access while preserving the visual quality of the video.
IJETEV1I2A002 - DETECTION OF SYNTHETIC MEDIA USING YOLO POWERED OBJECT RECOGNITION
AUTHORS : R.Arthi , G.Vishvanath Sundharam , S Udhayashankar , R Mathi , R Shanmathi
ABSTRACT – To address the growing challenge of Deepfake and synthetic video manipulation, this project proposes a hybrid Convolutional Neural Network (CNN) architecture with ResNet as the backbone for effective feature extraction. The proposed approach leverages deep feature learning to automatically capture complex spatial and temporal patterns that distinguish real videos from forged ones. Inverted residual blocks and linear bottlenecks are incorporated to preserve spatial information while optimizing memory usage and computational efficiency. Advanced training techniques are employed to enhance detection accuracy and reduce inference time. By combining intensive learning phases with CNN-based feature classification, the system achieves high accuracy and efficiency in identifying forged videos, making it a robust solution for ensuring digital media integrity in real-world applications. The proposed model is suitable for real-time deployment in digital forensics, cybersecurity monitoring, and media verification systems.
IJETEV1I2A003 - BLOCKCHAIN ASSISTED DATA RECOVERY SYSTEM USING FIDO KEY WITH FACE BIOMETRIC AUTHENTICATION
AUTHORS :Muthusamy.P , Kannan.R, B Guru Charan, K Venkata Taraka Ratna, N Siva Sankar
ABSTRACT – Today’s enterprise environments, secure and efficient data recovery is critical to maintaining operational continuity and protecting sensitive information. Traditional methods, such as password resets through email or SMS-based OTPs, are often vulnerable to attacks and require manual intervention from IT personnel, making them inefficient and insecure. To address these challenges, this project proposes a Blockchain-Assisted Data Recovery System that combines FIDO keys, face biometric authentication, and QR code scanning to enable seamless and highly secure recovery of lost or compromised credentials. By leveraging FIDO-compliant hardware keys, the system ensures password less authentication that is standardized, reliable, and resistant to phishing attacks, while face recognition provides an additional layer of accurate identity verification. The system integrates blockchain technology to store recovery credentials, access logs, and audit trails in a tamper-proof.
IJETEV1I2A004 - BLOCKCHAIN AGAINST FAKE NEWS AND DEEP FAKES
AUTHORS : Sathiyapriya P, Kohila R, G Durga Prasad, J Sumanth, V Pavan Kumar Reddy
ABSTRACT – The rise of ubiquitous deepfakes, misinformation, disinformation, and post-truth, often referred to as fake news, raises concerns over the role of the Internet and social media in modern democratic societies. Due to its rapid and widespread diffusion, digital deception has not only an individual or societal cost, but it can lead to significant economic losses or to risks to national security. Blockchain and other distributed ledger technologies (DLTs) guarantee the provenance and traceability of data by providing a transparent, immutable, and verifiable record of transactions while creating a peerto-peer secure platform for storing and exchanging information. This overview aims to explore the potential of DLTs to combat digital deception, describing the most relevant applications and identifying their main open challenges.
IJETEV1I2A005 - FROM CLICKS TO THREATS: MALICIOUS URL DETECTION IN CYBERSECURITY
AUTHORS :Muthusamy P,Vishvanath Sundharam G, D. Abhinay, G. Chennakesava Reddy, N. Shashendra Reddy
ABSTRACT – The rapid expansion of web-based applications has significantly increased exposure to cyber threats, particularly SQL Injection (SQLi) and Cross-Site Scripting (XSS) attacks. This study introduces a comprehensive framework aimed at strengthening web security through the integration of diverse detection strategies for identifying SQLi and XSS vulnerabilities. The proposed system employs automated scanning methods alongside penetration testing tools, including SQLMap for SQL Injection detection and script-driven techniques for XSS analysis. By enabling early identification of security weaknesses, the framework supports security practitioners in preventing potential attacks before they are exploited. The results highlight the critical role of proactive vulnerability assessment in safeguarding modern web applications. This research investigates advanced approaches such as heuristic-based evaluation, machine learning-driven anomaly detection, and behavior-oriented Security mechanisms to enhance the precision and effectiveness of threat detection
IJETEV1I2A006 - SECURE, ID PRIVACY AND INFERENCE THREAT PREVENTION MECHANISMS FOR DISTRIBUTED SYSTEMS
AUTHORS : Kohila R, Sathiyapriya P, P Srikanth, R Sidda Reddy, K Deepak Reddy
ABSTRACT – This paper investigates facilitating remote collection of a patient’s data in distributed system while protecting the security of the data, preserving the privacy of the patient’s ID, and preventing inference attack. The paper presents a novel framework called SPID stand for a Secure, ID Privacy, and Inference Threat Prevention Mechanisms for Distributed Systems. In designing this framework, we make the following novel contributions. The SPID presents a novel architecture that supports the use of a distributed set of servers owned by different service providers. The SPID allows the patient to access these servers using certificates generated by the patient. The SPID allows the patient to select one server to be the home server, and select a number of servers to be the foreign servers. The patient uses the foreign servers to upload data. The home server is responsible for collecting the patient’s data from the foreign servers and sending them to the healthcare provider.
IJETEV1I2A007 - MULTILAYERED DNA BASED STEGANOGRAPHY & MODIFIED RSA FRAMEWORK FOR ULTRASECURE DATA TRANSMISSION
AUTHORS : Kohila R, Selvarani C M, Surya S, Yogayuvaraj L, Sricharan G
ABSTRACT – In the modern digital era, the security of sensitive data during transmission and storage has become a major challenge due to the growing number of cyber threats.Traditional cryptographic algorithms are vulnerable to brute-force attacks, while standard steganography can be detected through advanced steganalysis. This paper introduces an innovative hybrid encryption framework that integrates DNA computing, image steganography, and a modified RSA
algorithm. The proposed system transforms plaintext into DNA-coded sequences, embeds them into a cover image using Least Significant Bit (LSB) or Discrete Wavelet Transform (DWT), and further encrypts the stego-image using modified RSA. This multi-layered architecture ensures a robust level of confidentiality, integrity, and authentication, making unauthorized decoding nearly impossible