Catch You if You Misbehave: Ranked Keyword Search Results Verification in Cloud Computing

Abstract

This research investigates the challenges of ensuring the accuracy and integrity of ranked keyword search results returned by cloud-based search engines. The objective is to develop a robust verification system that detects manipulation, biases, and inconsistencies in search rankings. The scope includes designing and implementing a system that analyzes search results across multiple search engines, employing statistical methods and anomaly detection techniques. The conclusion demonstrates the efficacy of the proposed system in identifying potential issues and enhancing the trustworthiness of cloud-based search results.

Introduction

The increasing reliance on cloud-based search engines for information access necessitates robust mechanisms to ensure the reliability of returned results. Search engine optimization (SEO) manipulation, algorithmic biases, and potential malicious activities can significantly distort search rankings, leading to misinformation and skewed perceptions. Existing verification methods are often limited in scope and scalability, lacking the ability to efficiently analyze results across diverse platforms. This research addresses this critical gap by developing a comprehensive verification system capable of detecting inconsistencies and anomalies in ranked keyword search results within the complex landscape of cloud computing.

Objectives

• Develop a system for verifying the accuracy and consistency of ranked keyword search results across multiple cloud-based search engines.
• Implement robust anomaly detection and bias detection algorithms to identify irregularities and biases in search rankings.
• Generate comprehensive reports detailing the reliability and trustworthiness of the analyzed search results.