My Account | Careers | Downloads | Blog

PROJECT TITLE :

TargetVue: Visual Analysis of Anomalous User Behaviors in Online Communication Systems

ABSTRACT:

Users with anomalous behaviors in on-line Communication systems (e.g. email and social medial platforms) are potential threats to society. Automated anomaly detection based mostly on advanced Machine Learning techniques has been developed to combat this issue; challenges remain, though, because of the difficulty of obtaining proper ground truth for model training and analysis. So, substantial human judgment on the automated analysis results is typically required to better change the performance of anomaly detection. Unfortunately, techniques that enable users to understand the analysis results additional efficiently, to create a assured judgment regarding anomalies, and to explore information in their context, are still lacking. During this paper, we tend to propose a completely unique visual analysis system, TargetVue, which detects anomalous users via an unsupervised learning model and visualizes the behaviors of suspicious users in behavior-rich context through novel visualization designs and multiple coordinated contextual views. Particularly, TargetVue incorporates 3 new ego-centric glyphs to visually summarize a user's behaviors that effectively present the user's Communication activities, features, and social interactions. An efficient layout technique is proposed to put these glyphs on a triangle grid, which captures similarities among users and facilitates comparisons of behaviors of different users. We demonstrate the ability of TargetVue through its application in an exceedingly social bot detection challenge using Twitter information, a case study primarily based on email records, and an interview with professional users. Our evaluation shows that TargetVue is beneficial to the detection of users with anomalous Communication behaviors.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : LibRoad: Rapid, Online, and Accurate Detection of TPLs on Android ABSTRACT: The detection of third-party libraries, also known as TPLs, is an extremely important part of Android malware analysis. The signature-based
PROJECT TITLE : Attention in Reasoning Dataset, Analysis, and Modeling ABSTRACT: Although attention has become an increasingly popular component in deep neural networks for the purpose of both interpreting data and improving
PROJECT TITLE :Cost-Optimal Caching for D2D Networks With User Mobility: Modeling, Analysis, and Computational Approaches - 2018ABSTRACT:Caching well-liked files at the user equipments (UEs) provides an efficient way to alleviate
PROJECT TITLE :Design, Analysis, and Implementation of ARPKI: An Attack-Resilient Public-Key Infrastructure - 2018ABSTRACT:This Transport Layer Security (TLS) Public-Key Infrastructure (PKI) is based on a weakest-link security
PROJECT TITLE :Modeling, Analysis, and Scheduling of Cluster Tools With Two Independent ArmsABSTRACT:Twin-armed cluster tools for semiconductor manufacturing sometimes have had two arms fixed in opposite directions. Recently,

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry