Paper Key : IRJ************041
Author: Mayank Raj,Kartavya Raj,Abhi Jain
Date Published: 03 Apr 2025
Abstract
URL shorteners have become essential components of modern web infrastructure, facilitating the sharing of links across space-constrained platforms. However, as their usage has grown, so have concerns regarding their performance, scalability, and security implications. This research paper presents a comprehensive analysis of current URL shortening technologies, with a particular focus on hashing algorithms and their impact on system performance and scalability. We also examine emerging security threats associated with shortened URLs and evaluate the effectiveness of various AI-based detection systems in identifying malicious links. Through empirical testing and comparative analysis, we demonstrate that hybrid hashing approaches combined with machine learning-based threat detection offer superior performance characteristics while maintaining robust security protections. Our findings provide valuable insights for developers and security professionals seeking to implement or enhance URL shortening services in high-traffic environments.Keywords: URL shorteners, hashing algorithms, scalability, performance optimization, cybersecurity, machine learning, malicious link detection. URL shortening services transform lengthy web addresses into compact, manageable links that redirect users to the original destination. Initially conceived to address character limitations on platforms like Twitter, these services now play a crucial role in web analytics, marketing campaigns, and content distribution. As the volume of shortened URLs has grown exponentially, so has the importance of designing systems that can handle massive traffic loads while maintaining performance and security.This paper addresses three critical challenges facing modern URL shortening services:1.Performance optimization: Ensuring rapid generation and resolution of shortened URLs, minimizing latency even under heavy load.2.Scalability: Designing systems capable of handling exponentially growing traffic volumes without degradation.3.Security: Detecting and mitigating threats posed by malicious actors who leverage shortened URLs to obscure phishing, malware distribution, and other attacks.We begin by examining the architectural foundations of URL shortening services, followed by a detailed analysis of various hashing techniques and their performance characteristics. The paper then explores how artificial intelligence and machine learning approaches can enhance security through malicious link detection. Through extensive testing and evaluation, we provide practical recommendations for implementing high-performance, secure URL shortening services suitable for deployment in enterprise environments.