An automated spam detection and location-based monitoring system

Abstract

Spam is often considered as the most troublesome aspect in digital era with security and privacy concern. It is essential to develop effective solutions for spam issues. This project Automated spam detection and location-based monitoring system, provides a new detection system of spam attack in calls, messages and emails. It also provides location-based monitoring of these attacks. It relies on machine learning algorithms trained with updated datasets to accurately classify calls, messages and emails into spam. Through various sophisticated natural language processing techniques, it detects message and email spam content and patterns in call logs for identifying known spam numbers. It provides an interface through which user can enter a phone number or email address to detect spam. As soon as it detects a spam, the details are displayed with timestamp, and an alert is sent to user through email or SMS. The system also integrates location-based tracking to determine the geographic source of spam details. Leveraging geolocation data gathered from calls and account information, this feature aims for fraud prevention and situational awareness. Map visualization keep the insights actionable and transparent. The spam and location together form a single solution for real-time data processing / spam detection /location tracking that can be both seen as an application on its own or integrated into other platforms, making a very powerful weapon in fighting digital fraud while enhancing secured communication. This project provides practical applications for all users to facilitate a safer communication environment with greater accountability.