The product is developed as a part of the final year project. It is aimed at providing an architecture and open source code to developers so that they can embed this into their applications to enhance the security. The services provided are top notch and cover the broad spectrum of computer and network security. All the features of the product involve the application of Data Mining and Machine Learning techniques onto the domain of Computer Security.
The demand for modern tools and techniques to restrict access to applications and services which contain delicate data is increasing exponentially each year. Traditional methods such as PINs, tokens, or passwords fail to keep up with the challenges presented because they can be lost or stolen, which compromises the system security. But even the most powerful cryptographic systems fail to prevent unauthorized access.
Developers need to adress the issue of security at each module while developing applications involving customer info. The aim of the project is to provide the basic feautures needed to make a system secure. Hence, we have services ranging from Biometric Authentication to Network Intrusion Detection System.
Biometric attributes become the most optimal and ideal candidates for authentication since they cannot be stolen, lost or impersonated. The most promising approach has been Keystroke biometrics which refers to the habitual patterns or rhythms an individual exhibits while typing on a keyboard input device. Compared to other biometric schemas, keystroke has the primary advantages that:
- No external hardware like scanner or detector is needed. All that is wanted is a keyboard.
- The “rhythm” or the pattern of the users is a very reliable statistic.
- It can easily be deployed in conjunction with existing authentication systems.
In the era of information society, computer networks and their related applications are becoming more and more popular, so does the potential threat to the global information infrastructure to increase. Therefore, the role of Intrusion Detection Systems (IDSs), as special-purpose devices to detect anomalies and attacks in the network, is becoming more important. IDSs are impressive since it can detect, prevent and possibly react to attacks in an efficient manner.
Keyloggers are a type of activity-monitoring software that is installed on your computer without your knowledge. The most common ways of doing this are through phishing, social engineering, bundling the keylogger with other software or downloads on file-sharing sites or installing it when you open an email attachment.
- Front end : JavaScript, HTML5, CSS3, Bootstrap, jQuery
- Backend: PHP, AJAX
- Database: MySql
- Data Mining/ ML: R
- Libraries used: caret, ggplot2, randomForest, rpart, rpart.plot, e1071
- Tools used: XAMPP, R Studio, PHPMyAdmin, Git