Mr. Venkat Nutalapati

Explainable AI for Android Malware Detection: Delivering Transparency and Reliability

Abstract:

The android malware detection is not about detecting threats anymore; it is about understanding them. Machine learning models provide great accuracy and yet cannot be used in practice due to their black-box characteristic. As they lack clear facts about model decision-making, alert providers leave security teams in doubtful positions and unable to take any security-related action.

During this session, I will discuss how Explainable AI (XAI) can alter the detection of Android malware due to its transparency and reliability. We will discuss the importance of detecting decisions using techniques, such as SHAP, LIME, and explainability based on graphs rendering the decision interpretable, auditable, and actionable.

You will find out how XAI is used to investigate latent model biases, increase analyst trust, and advance the retention of regulatory frameworks. Practice-based case studies and implementation plans will present how organizations can construct explainable detection systems that provide performance while holding accountability.

In the future, XAI will be an essential android ecosystem security feature to prevent not only the detection of malware, but its comprehension. The session will provide a crisp guide on how to embrace the use of explainable AI methodologies and beef up protection against the contemporary mobile threats.

Profile:

Venkat is a seasoned Software Engineer with extensive experience in Android development, mobile security, and scalable platform architecture. At Walmart, he played a critical role in modernizing the mobile engineering platform by driving performance optimizations, reducing build and deployment times through custom automation and tooling. He has led key initiatives across multiple business units—including Walmart US, Sam’s Club, and Walmart International—delivering secure, reliable, and high-performance mobile experiences.

Venkat has also contributed to innovation in IoT and AI at scale, helping integrate smart device data for real-time inventory tracking, connected commerce solutions, and AI-powered product recommendation systems. His focus on platform reliability, data security, and developer productivity has made a tangible impact on both end-user experience and engineering velocity.