| Idea Name: |
Email Analyzer |
| Slogan: |
Email Controls and Detection Engine |
| Supervisor Name: |
Waleed Bin Shahid |
| Supervisor Designation: |
Assistant Professor |
| Supervisor School: |
MCS |
| Supervisor Department: |
Department of Information Security |
| Contact number: |
03333305533 |
| Email ID: |
[email protected] |
| Abstract: |
| Our project, entitled Email Analyzer, is a comprehensive solution for detecting spam, phishing, and other malicious emails and attachments. Utilizing advanced machine learning algorithms and natural language processing techniques, Email Analyzer can accurately identify and flag suspicious emails and attachments. |
| What is the unmet need in society that your idea will fulfill ? |
| With the increasing prevalence of spam and phishing attacks, as well as the increasing sophistication of these threats, there is a growing need for tools and technologies that can help protect individuals and organizations from these types of attacks. |
| Who needs it ? How many would benefit ? |
| Email Analyzer would be useful for anyone who uses email, as it provides a way to protect against spam, phishing, and other malicious emails and attachments regardless of the email service provider. This includes individuals, businesses, and organizations of all sizes and types. |
| How will the solution works |
| The user will use a plugin to send the email to the backend server. This server is the core system that will do all the analysis work and generate a report. Analysis work include checking the headers of the email and apply relevant ML and NLP techniques on body part of the email, also it will check the URLs in the email and the attachments attached, scan them using Virus Total APIs to check if they are malicious or safe. It will then send a report back to the user. |
| Who are your competitors ? How is your solution different |
| Our competitors include traditional spam filters, which are often included as part of email clients, as well as other advanced spam and phishing detection solutions.
Also, it uses advanced ML algorithms and NLP techniques. These technologies allow it to accurately identify spam and phishing attempts |
| Status: |
new |
| Entry Date & Time: |
2022-12-15 (1812) |
