Web-based honeypot for detecting and tracking attackers
Abstract & Details
Research Area
Computer Engineering
Keywords
Web-based Honeypot
SQL Injection
Cross-Site Scripting
LikeJacking
Abstract
Recently due to advancement of new technologies, various types of attacks on websites and webservers have also increased, some of them majorly include cross-site scripting (XSS) and SQL injection attacks which are used to spoil the vulnerability of the system and steal confidential data of the users like their user ID’s and passwords from the server databases. Many methods were proposed to prevent such attacks. Some of them were created to learn about pattern of attacks and behavior of the attacker. That is honeypot. Honeypot is classified into two types based on the simulation that honeypot does, low interaction and high interaction.
In this project a low-interaction honeypot is proposed for emulating vulnerabilities that can be exploited by XSS and SQL injection attacks. This honeypot not only records attacker's request, but it also tries to expose attacker’s identity by using browser exploitation techniques. Some have methods to hide their identity, thus they couldn't be tracked. Hence the proposed honeypot tries to overcome this problem by sending attackers a malicious JavaScript code. This JavaScript code will be run when an attacker opens the honeypot's website. The code steal attackers’ confidential information like social account information by using Like Jacking technique, their IP and MAC addresses although even if they have used proxy or TOR to hide their identity. These information helps us to locate the attacker geographically by using some in-built packages and software that takes IP or MAC addresses as the input and provide its location as an output.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Nisarg N Thakur | College of Engineering, Kopargaon |
| 2 | Prashant Patil | College of Engineering, Kopargaon |
| 3 | Rajat Varade | College of Engineering, Kopargaon |
| 4 | Abhishek Pawar | College of Engineering, Kopargaon |
How to Cite
Use the following formats to cite this article in your research.
APA Style
Thakur, Nisarg N, Patil, Prashant, Varade, Rajat, & Pawar, Abhishek (2016). Web-based honeypot for detecting and tracking attackers. International Journal of Advance Research and Innovative Ideas In Education, 2(3), 3273-3277.
MLA Style
Thakur, Nisarg N, et al. "Web-based honeypot for detecting and tracking attackers." International Journal of Advance Research and Innovative Ideas In Education, vol. 2, no. 3, 2016, pp. 3273-3277.
IEEE Style
Nisarg N Thakur, Prashant Patil, Rajat Varade, and Abhishek Pawar, "Web-based honeypot for detecting and tracking attackers," International Journal of Advance Research and Innovative Ideas In Education, vol. 2, no. 3, pp. 3273-3277, 2016.
Vancouver Style
Thakur Nisarg N, Patil Prashant, Varade Rajat, Pawar Abhishek. Web-based honeypot for detecting and tracking attackers. International Journal of Advance Research and Innovative Ideas In Education. 2016;2(3):3273-3277.
Harvard Style
Thakur, Nisarg N, Patil, Prashant, Varade, Rajat, & Pawar, Abhishek (2016) 'Web-based honeypot for detecting and tracking attackers', International Journal of Advance Research and Innovative Ideas In Education, 2(3), pp. 3273-3277.
Chicago Style
Thakur, Nisarg N, et al. "Web-based honeypot for detecting and tracking attackers." International Journal of Advance Research and Innovative Ideas In Education 2, no. 3 (2016): 3273-3277.
Turabian Style
Thakur, Nisarg N, et al. "Web-based honeypot for detecting and tracking attackers." International Journal of Advance Research and Innovative Ideas In Education 2, no. 3 (2016): 3273-3277.
Related Research
Comprehensive Review of Existing Chatbot Systems for Career Assistance, Resume Support, and ATS-Aware Guidance
PDF Unavailable
Development of an AI-Powered Multimodal Web Assistant with Intelligent Resume Building and ATS Enhancement
PDF Unavailable
A Deep Learning-Based Framework for Mood-Oriented Music Recommendation Using Facial Expression Analysis
PDF Unavailable
Survey On : Intelligent Payroll and Human Resource Management Systems: A Systematic Review of Automation, Security, and Analytics
PDF Unavailable
Civic Engagement & Empowerment Platform
PDF Unavailable
Recent Developments in Microneedle Technology and Its Diverse Biomedical Applications
PDF Unavailable
RAG System Development with Pydantic AI ChromaDB & Groq
PDF Unavailable
Machine Learning Based Early Stage Diabetes Detection System
PDF Unavailable
A Survey on Skillsense:AI Career Analyzer App
PDF Unavailable
Employee Performance Portal
PDF Unavailable