• Non-Intrusive Malware Detection based on Hardware Root-of-Trust
    MoMA Lab, NYU
    • Proposed an out-of-the-device non-intrusive malware detection methodology utilizing high and low-level information collected by JTAG using Lauterbach PowerDebug PRO.
    • Demonstrated an accuracy increase to 99.75% by utilizing semantic and microarchitectural information with an SVM model for malware detection.
    • Utilized integrity verification of critical static Linux kernel data structures for rootkit detection and OCSVM trained on static analysis information of shared libraries for user-level rootkits, achieving an accuracy of 96.3%.
  • Platform Agnostic Remote Static Analysis Malware Detection for ICS
    MoMA Lab, NYU
    • Implemented external non-intrusive static analysis malware detection leveraging out-of-the-device virtual to physical address translation with JTAG.
    • Performed static analysis of process text section for extracting entropy values for a 32-byte sliding window, string, and syscall histograms, to be utilized as platform-agnostic features.
    • Achieved 98%, 95% malware detection accuracy for ARM and x86_64 architecture, respectively, with an SVM model.
      [Code] [Poster] [Video]
  • Process-Aware Cyberattacks for Thermal Desalination Plants
    Center for Cyber Security, NYUAD
    • Performed process-aware security assessment of desalination plants to identify attack entry points, categorize the attacks, estimate the corresponding financial loss, and mechanical damage.
    • Computed the resultant thermal shocks and pressure surges during water hammer in the piping system on sudden valve closure in MATLAB.
    • Quantified the detrimental effects of water hammering during such attacks in terms of Maximum induced von Mises stresses (340 MPa) and maximum displacement (19.94mm) with ANSYS.
      [Code] [Paper] [Presentation]


  • Phish Muzzle
    • Proposed and developed a metadata based approach for defending against email spear phishing attack.
    • Extended Levenshtein Distance and MySQL queries for identifying suspicious emails.
    • Optimized the solution by reducing search space using additional MySQL query.
      [Code] [Thesis]
  • Automated NFV Deployment
    Wireless Networking Group (WiNG)
    • Developed a command line tool to automatically deploy OAI components using OpenStack.
    • Implemented automated scripts for OAI configuration based on user specified modular SLA files.
    • Introduced simple interactive functionality to deploy, delete and check status of the spawned VMs.
  • ASCII Transliteration Format (ATF) Parser
    • Developed a parser to validate ATF texts using PLY in Python.
    • Enhanced and adopted the parser for online use by connecting PHP front with Python backend.
    • Implemented rules for automatically detecting structural and semantic defects in the texts.
  • Secure Code Analysis
    Software Evolution and Analysis Laboratory
    • Proposed a novel technique to detect violations of secure coding techniques using abstract symbol tree in Java.
    • Extended Google’s Error Prone to analyse the code for security vulnerabilities during compile time.
    • Detected vulnerabilities such as weak random number generation and return value ignored in open source projects.
  • Machine Learning for Cancer Treatment Prediction
    Center for Smart Health
    • Proposed a novel technique using clinical data for predicting best treatment option for cancer patients.
    • Implemented multiple machine learning techniques using TensorFlow and scikit library in Python.
    • Modified the algorithm to obtain an accuracy of upto 85%.
      [Code] [Presentation]
  • Software Development for Personal Cloud File Sync
    Wireless Networking Group (WiNG)
    • Implemented automated personal cloud system using Python.
    • Improved the software to incorporate SSL protocol for secure transfer of data.
    • Achieved significantly less meta data transfer by using delta based approach.
    • Shifted from master based architecture to semi-master based approach, where data is transferred peer-to-peer and master is used only for meta data transfer.
      [Code] [Report]
  • Breaking Location Stream Privacy
    Network Research Lab
    • Studied different neural network configurations for understanding its effect on location stream data.
    • Applied feed forward neural network for mobility pattern classification on location stream data.
    • Extended the solution to recurrent neural network for minimizing error to a maximum of 1.

Open Source Projects

  • Lauterbach Python Library [Code]
  • Development of Android Application for CDLI Lab [Code]