MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641106643 A) filed by Kkr & Ksr Institute Of Technology And Sciences on September 04, 2026, for A Predictive Machine Intelligence Model For Mobile Malware Forecasting.
Inventors include Mr. Prof. Repudi Ramesh; Mrs. S. Vijaya Lakshmi; P. Bhavya Sri; P. Jayasree; M. Lekha Sri; and P. Akshitha.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: ABSTRACT [0013] The rapid increase in internet usage and digital platforms has led to a significant rise in malware attacks, phishing websites, and visually deceptive online content. Traditional detection methods, which rely mainly on signature-based techniques and manual analysis, are often ineffective in identifying newly emerging and visually obfuscated threats. To overcome these limitations, this invention proposes an image-based predictive machine intelligence model for malware detection. The system focuses on analyzing images of web pages and application interfaces to determine whether they are safe or malicious. It utilizes convolutional neural networks to extract important visual features such as layout structure, design patterns, and branding inconsistencies. Additionally, recurrent convolutional neural networks are integrated to detect and localize suspicious regions like fake login forms, malicious pop-ups, and forged user-interface components. The processed features are then passed through a classification engine that categorizes the input into four classes: safe, malicious, hackware, and beginware. The system is designed to provide accurate and real-time detection while reducing false positives. Its lightweight architecture makes it suitable for deployment in web and mobile environments. Overall, the proposed model enhances cybersecurity by providing an efficient, scalable, and intelligent solution for detecting visually deceptive malware content, thereby protecting users from data theft and online threats.
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