An Android malware detection system based on machine learning
Description: The Android smartphone, with its open source character and excellent performance, has attracted many users. However, the convenience of the Android platform also has motivated the development of malware. The traditional method which detects the malware based on the signature is unable to detect unknown applications. The article proposes a machine learning-based lightweight system that is capable of identifying malware on Android devices. In this system we extract features based on the static analysis and the dynamitic analysis, then a new feature selection approach based on principle component analysis (PCA) and relief are presented in the article to decrease the dimensions of the features. After that, a model will be constructed with support vector machine (SVM) for classification. Experimental results show that our system provides an effective method in Android malware detection.
Music Recommendation System ML Project
In this project, we use the dataset from Asia's leading music streaming service to build a better music recommendation system. We will try to determine which new song or which new artist a listener might like based on their previous choices. The primary task is to predict the chances of a user listening to a song repetitively within a time frame. In the dataset, the prediction is marked as 1 if the user has listened to the same song within a month. The dataset consists of which song has been heard by which user and at what time. Use classification machine learning algorithms to solve this classification problem and as a challenge, try using deep learning algorithms like neural network.
Extra-curricular activities
- Participated in many seminars on various topics including Ethical Hacking, Robotics, Game Development, Embedded Systems, Web Development and Deep Web
- Was a finalist in the Smart Cities Hackathon held at IIIT Hyderabad where we demonstrated how to create a system for monitoring the pollution in the air.
- Won the Inter-College Cricket tournament held at Triti 2k17.
Skills
Languages
C, Javascript, Python
Frameworks
ASP.NET, Bootstrap
Web Services
EC2, IAM, Elastic Beanstalk, S3, Glacier, Firebase
Programs and Other Technologies
Visual Studio, WebStorm, DataGrip, jQuery, SQL, NoSqlDatabase, IntelliJ IDEA