Back close

Backdoor Analysis of Enterprise Applications

Backdoor Analysis of Enterprise Applications

Malware forms the basis of most cyber-criminal operations causing significant financial loss and posing a huge threat to the security of an organization. Enterprise applications form the backbone of any organization. They have scaled and matured over the years providing more and more services to users. However, the threats that have plagued it has also abounded.The goal of this research is to exhaustively study the problem of backdoors as is seen in software today, to identify the various possible attack vectors, and to develop a scalable and modular framework to detect backdoors in Common Off the Shelf (COTS) software and enterprise applications alike. The framework applies known program analysis techniques such as static and dynamic analysis and uses standard data flow and control flow constructs to study the flow of information in a program to conclude for backdoors.

Related Projects

Screening, Identification and Characterisation of Bacteriocins Isolated from Wine Microflora
Screening, Identification and Characterisation of Bacteriocins Isolated from Wine Microflora
Towards Precision Dosing: AI – Enhanced Model Predictive Control Closed Loop Infusion Pump for ICUs 
Towards Precision Dosing: AI – Enhanced Model Predictive Control Closed Loop Infusion Pump for ICUs 
Development of a Real-time, Process Control Method Based on Neural Network Model Using Feedback of Weld Pool Geometric Parameters Measured by a Vision-based Technique and Experimental Verification for Automated Arc Welding Processes
Development of a Real-time, Process Control Method Based on Neural Network Model Using Feedback of Weld Pool Geometric Parameters Measured by a Vision-based Technique and Experimental Verification for Automated Arc Welding Processes
Modelling and Analysis of Connectivity Reliability in 6G IoT Networks using k –out of- n Replenishment Policies 
Modelling and Analysis of Connectivity Reliability in 6G IoT Networks using k –out of- n Replenishment Policies 
Malware detection using FPGA, Sandboxing and Machine Learning
Malware detection using FPGA, Sandboxing and Machine Learning
Admissions Apply Now