most citedOptimizing Spot Instance Reliability and Security Using Cloud-Native Data and Tools

6 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2025★ 1 cited

Adaptive Security Policy Management in Cloud Environments Using Reinforcement Learning

Muhammad Saqib, Dipkumar Mehta, Fnu Yashu +1

The security of cloud environments, such as Amazon Web Services (AWS), is complex and dynamic. Static security policies have become inadequate as threats evolve and cloud resources…

cs.DC2025

Optimizing Intra-Container Communication with Memory Protection Keys: A Novel Approach to Secure and Efficient Microservice Interaction

Fnu Yashu, Shubham Malhotra, Muhammad Saqib

In modern cloud-native applications, microservices are commonly deployed in containerized environments to ensure scalability and flexibility. However, inter-process communication (…

cs.DC2025★ 2 cited

Deep Reinforcement Learning for Dynamic Resource Allocation in Wireless Networks

Shubham Malhotra, Fnu Yashu, Muhammad Saqib +3

This report investigates the application of deep reinforcement learning (DRL) algorithms for dynamic resource allocation in wireless communication systems. An environment that incl…

cs.CR2025★ 6 cited

Optimizing Spot Instance Reliability and Security Using Cloud-Native Data and Tools

Muhammad Saqib, Shubham Malhotra, Dipkumar Mehta +3

This paper represents "Cloudlab", a comprehensive, cloud - native laboratory designed to support network security research and training. Built on Google Cloud and adhering to GitOp…

cs.DC2025

Evaluating Fault Tolerance and Scalability in Distributed File Systems: A Case Study of GFS, HDFS, and MinIO

Shubham Malhotra, Fnu Yashu, Muhammad Saqib +3

Distributed File Systems (DFS) are essential for managing vast datasets across multiple servers, offering benefits in scalability, fault tolerance, and data accessibility. This pap…