TEDx Explores Harmonic Tectonics
TEDx Explores Harmonic Tectonics
NYIT Students Surpass the $1 Million Mark in Combined Earnings from Internships
TEDxNYIT: Creating Harmony in a World Experiencing Tectonic Shifts
Dynamic, Radical Solutions Needed: 2014 Cybersecurity Conference Highlights
NYIT Engineering Professor Wins NIH Grant for Robotics Research
Interdisciplinary Studies Career Panel
Dig Lavender: Volleyball vs. Queens (N.Y.)
“The Year of Turkey 2014” - The Heritage of Turkish Art: Opening Reception
“The Year of Turkey 2014” - The Heritage of Turkish Art: Exhibition
Relay for Life Interest Meeting
Faculty Mentor: Dr. Kiran Balagani
Objective: Explore the performance of authentication technologies in touch-based mobile devices under forgery and morphing attacks.
Implementation: Students will develop strategies and codes to inject attacks into state-of-the-art touch-based authentication algorithms and gain hands on research experience by designing and implementing adversarial attacks on these touch authentication algorithms.
Faculty Mentor: Dr. Xiaohui (Sean) Cui
Objective: Study the impact of smartphone botnets and find countermeasures by studying malware spreading on a botnet simulation platform.
Implementation: Students will contribute in creating adversarial smartphone-based malware and botnet software on smartphone emulation platforms, experimenting on the existing test bed, and collecting and analyzing experiment data. Students will also learn how to use botnet simulation tools, write script to collect experiment data and analyze data.
Faculty Mentor: Dr. Farshid Delgosha
Objective: Investigate efficient software implementation of arithmetic over small-size finite fields for implementing algebraic cryptosystems for mobile devices.
Implementation: Students will implement finite-field arithmetic cryptography for use on tablets.
Faculty Mentor: Dr. Wei Ding
Objective: Investigate methodologies to detect physical capture attack against smartphones.
Implementation: Students will help design a test phone, test circuits, and implement detection algorithms using Java or Python on smartphones.
Faculty Mentor: Dr. Ziqian (Cecilia) Dong
Objective: Investigate effective smartphone geolocation techniques in metropolitan areas when GPS does not function well due to lack of line of sight and interference.
Implementation: Students will help collecting network measurements (network delay, bandwidth, data transmission rate, received signal strength and geographical location) using applications on smartphones, in both cellular and wireless networks.
Faculty Mentor: Dr. Huanying (Helen) Gu
Objective: Raise the awareness of students to privacy and anonymity issues related to the collection and manipulation of medical data and design a framework that manipulates health-related information and provides strong privacy guarantees.
Implementation: Students will develop a tool to automatically extract and de-identify collected medical data. Furthermore, they will identify the critical privacy problems in the existing system, and architect a more privacy-friendly system for automated medical data collection.
Faculty Mentor: Dr. Chung Hyuk Park
Objective: Develop a methodology for robotic system for tele-medicine that can enhance privacy in personal data and physical safety during interaction with a tele-operated robot.
Implementation: Students willl develop and integrate different modules (i.e. depth-based visual perception, gesture recognition, and teleoperative robot control) that can run synchronously in a Linux system with a physical robot.
Faculty Mentor: Dr. Tao Zhang
Objective: Study the tradeoffs between topology control performance metrics such as throughput and power drainage and network security and to investigate traffic patterns, network metrics when wireless networks are under botnet attack.
Implementation: Students will study tradeoffs between topology control performance metrics in wireless mesh networks and network security. They will design and build simulation test beds using open source software such as OMNET, measure and model power drainage and throughput deterioration due to botnet attacks.