Dr. Rajib Ranjan Maiti is an Assistant Professor at the Department of Computer Science and Information Systems, BITS-Pilani, Hyderabad Campus, Hyderabad, India. He has worked as a Post-Doctoral Research Fellow at iTrust, Singapore University of Technology and Design. He is working on analyzing recent attacks like KRACK on WPA2, BotNet using IoTlike Mirai, Byzantine attack or Sybil attack or malware attack on complex networks. Email id: rajibrm@hyderabad.bits-pilani.ac.in, Website: Link

Current Members


Priyanka is currently working as a Full-Time Research Scholar in BITS Pilani, Hyderabad Campus Telagana. She had total teaching experience of 4.5 years and her interest is detecting cyber attacks and information leakage in Internet of Things (IoT) devices.
Email id : p20180421@hyderabad.bits-pilani.ac.in, priyankasherekar@gmail.com
Anand holds Bachelor and Master in Computer Science and Engineering. His research interest lies in analysing the wifi traffic and to understand the WPA/WPA2 security standard. Currently, he is working as a Full-Time Researcher in BITS Pilani.
Email id: p20200434@hyderabad.bits-pilani.ac.in,Website: Link

Praneeta is currently working as a Full-Time Research Scholar in BITS Pilani, Hyderabad Campus Telangana. She holds a master's degree in Computer Science and Engineering and her research interests include Cyber Security in Data Centers, Cyber Physical Systems and Computer Networks.
Email id: p20210414@hyderabad.bits-pilani.ac.in

Nalanagula Bharath Vamshider Reddy work as a Project Assistant




Past Members


Sanghamitra worked as a Research Assistant in a CRG-SERB, DST funded project. She explored the security vulnerabilities in IoT devices. Her research interest in Cryptography and Cyber Security and she is a PhD aspirant in the similar area.
Email id:sanghamitra.samanta11@gmail.com

Tulika Jha worked as an intern and associated with the Lab in May 2022, now doing MS in Stanford University.

Pavan Srihari Darbha worked as an intern and associated with the Lab in May 2022, now doing MS in Stony Brook University






Btech Students association

Prakhar Gupta was associated with the lab from Jan 2020 to May 2020, he is currently working in Amazon India, he was involved in making a framework to capture packets and extract features for analysis in an IOT network by setting up Raspberry Pi as the access point. He also made a framework for IOT network visualization. Skills gained (some tools or programming language, max of 10 key words): TShark, Raspberry Pi, Linux Networking, D3JS Email Id: prakhar611@gmail.com

Aniket closely worked with the IoT-Edge Simulator and the three provided IoT setups. His primary objective was to analyse and interpret the given examples to serve as a blueprint for creating a new setup of our own. He documented the control flows in the code to model our long term aim of simulating a biogas unit using IoT devices.

Karthik worked on implementing an authentication protocol based on user, gateway node, and deployed IoT devices. This authentication leverages the use of the smart card, biometrics, and password to establish a session between a user and the specified IoT sensor. He was associated with the lab from Jan 2021 to May 2021, currently he is working in Deloitte USI.
Email Id: f20170260@hyderabad.bits-pilani.ac.in, metlap00@gmail.com

Btech Students association

Ashlin Chirakkal looked at the formal analysis of the WPA2 wifi security protocol. The protocol was first modeled on the AVISPA tool using HLPSL, showing that the tool is not capable of tracing the KRACK attack against WPA2. Then, the tamarin prover software was used to show the WPA2 model and the attack traces against it. Further research is being done to come up with a patch to protect against such types of attacks. Skills gained: AVISPA tool using HLPSL, Tamarin Prover tool.

Sathwika worked on analyzing TinyML’s performance on the Arduino Nano for IOT device classification. Her primary task was to use TFLite and Tensorflow to build and train a model for a specific dataset and to accurately predict the classes using the Arduino Nano 33 BLE Sense. A connection for predictive communication between the PC and Arduino was established as well. Various datasets are being explored to enhance the scope of her research.

Worked on examining TinyML's capabilities for classifying Internet of Things devices on the Arduino Nano. She created and trained a model for a dataset using TFLite and Tensorflow, then used the Arduino Nano 33 BLE Sense to predict the classes reliably. The combination of a Python code and an Arduino code allowed for predictive communication using the serial port. She also used the iris dataset for much of my work, although she work with other datasets.