Detection of Spam and Fraudulent calls Using Natural Language Processing Model

The main problem is the amount of spam calls and SMS messages that are sent out, which can be bothersome, invasive, and even dangerous for the recipients. These could be unsolicited marketing messages, phishing efforts, or frauds. A lot of call and SMS blocking programs would need to access a user’s call history or personal information, which raises privacy and data security issues. It uses natural language processing (NLP) to catch spam and fraudulent calls and SMS messages in real time. This implies that consumers will receive instant security since it can recognize and react to such stuff as it is received. Call-E places a great emphasis on its dedication to user privacy. It makes sure that discussions stay totally anonymous by not collecting, storing, or recording any user data. This solves the privacy issues that many call and SMS filtering programs have. Call-E has special permissions to run in the background without interfering with calls or messages since it is a system app. It guards the user’s mobile experience like a silent sentinel, ready to act at any moment. Users can get real-time security from Call-E’s NLP-based technology, which is successful in detecting and blocking spam and deceptive information. Call-E stands apart from the competition by protecting user privacy. Conversations are private and anonymous because it doesn’t capture or store any user data. Call-E functions in the background without interfering with calls or messages, as it is a system app with privileged permissions that keeps the user’s mobile experience safe.