Akansha Singh

Title: "Enhanced Provably Secure Public Key Encryption with Keyword Search Scheme for Secure Cloud-Based Keyword Search"

• Description: This paper was presented at the 15th International Conference on Computing, Communication, and Networking Technologies (ICCCNT 2024) at IIT Mandi. It is SCOPUS-indexed, highlighting advancements in secure cloud-based keyword search encryption.

• Operating System
• Computer Networks
• DBMS
• Computer Organization
• AWS Beginner
• Distributed System
• Discrete Mathematics
• Machine Learning

• Gramiksha NGO: Volunteered to provide education to underprivileged children by teaching students in government schools.
• Finished 2nd in VNIT Coding Marathon.
• Secured a Gold medal in a Inter-College theme-based group dance competition.
• Secured a Bronze medal in Inter-NIT basketball competition

Public Key Encryption with Keyword Search for Data Outsourcing in Cloud Environment

• Secure Cloud Storage: Developed an improved Public Key Encryption with Keyword Search (PEKS) scheme for securing datasets on cloud environments like AWS.
• Attack Prevention: Implemented an encryption scheme that prevents keyword search attacks by ensuring ciphertext and trapdoor indistinguishability.Designed and tested the PEKS scheme on a real testbed to ensure efficiency in searching over encrypted cloud data.

Multi-threaded task scheduler using semaphores in C++

• Concurrency Management: Developed a multi-threaded task scheduling system using POSIX semaphores to control task flow and mutexes to ensure safe access to shared resources in a concurrent producer-consumer model.
• Thread Safety: Achieved 100% thread safety across shared queue and log operations by eliminating race conditions through mutex-based locking in over 1,000 simulated tasks.
• Performance Optimization: Improved task processing throughput by 30% through optimized semaphore limits and reduced thread contention during peak load scenarios.

Line Follower Robot- Robotonics

• Hardware Integration: Designed and built a line follower robot using IR sensors, Arduino, and an L298N motor controller.
• Real-Time Navigation: The robot successfully navigates a path by detecting and following a line, making real-time adjustments to stay on course.