The Rutgers University School of Engineering celebrated the 2017 Faculty Award winners, following a nomination and selection process that included the School’s faculty, alumni, and friends. In recognition of their contributions to the School of Engineering through their achievements in scholarship, teaching, and service Dipanakar Raychaudhuri, Distinguished Professor of Electical and Computer Engineering, has been named Faculty of the Year.
Dipanakar Raychaudhuri is a distinguished professor in the Department of Electrical and Computer Engineering, having played an integral role in the engineering community since he joined Rutgers University-New Brunswick in 2001. Director of the internationally-recognized Wireless Information Network Lab (WINLAB), Raychaudhuri serves as principal investigator for several multi-institutional projects supported by the National Science Foundation (NSF). These include MobilityFirst, which revolves around designing future Internet architecture (FIA), and ORBIT—geared toward developing an open-access wireless network testbed.
Active in technology entrepreneurship, Raychaudhuri is the technical advisor for several government organizations and companies. He has written over 200 journal and conference papers, as well as 10 book chapters, on research areas that include future network architectures and protocols, wireless systems and technology, experimental prototyping and network research testbeds. In addition, Raychaudhuri coauthored Emerging Wireless Technologies and the Future Mobile Internet, published in 2011. He holds 15 patents on topics including broadband wireless networks, MAC protocols, digital video, and VSAT networks.
Saman Zonouz Associate Professor, Electrical and Computer Engineering
Anand Sarwate Assistant Professor, Electrical and Computer Engineering
ECE Sophomore Orientation
Event Title: ECE New Graduate Student Orientation
Event Date: 2017-09-08
Beginning Time: 11:00 am
End Time: 1:00 pm
Event Location: CoRE-Auditorium
Open to all new ECE Graduate Students. Meet the ECE Graduate Director, Dr. Zoran Gajic, and other ECE faculty.
Dr. Shlomo Shamai
The Andrew and Erna Viterbi Department of Electrical Engineering
Technion-Israel Institute of Technology
TITLE: A View of Information-Estimation Relations in Gaussian Networks
Researchers at Rutgers and Georgia Tech develop three methods to defend against sneaky attacks
With cyberattacks on 3D printers likely to threaten health and safety, researchers at Rutgers University-New Brunswick and Georgia Institute of Technology have developed novel methods to combat them, according to a groundbreaking study.
“They will be attractive targets because 3D-printed objects and parts are used in critical infrastructures around the world, and cyberattacks may cause failures in health care, transportation, robotics, aviation and space,” said Saman Aliari Zonouz, an associate professor in the Department of Electrical and Computer Engineering at Rutgers University-New Brunswick.
He co-authored a peer-reviewed study – “See No Evil, Hear No Evil, Feel No Evil, Print No Evil? Malicious Fill Pattern Detection in Additive Manufacturing” – that was published today at the 26th USENIX Security Symposium in Vancouver, Canada. It’s the security community’s flagship event, highlighting the latest advances in protecting computer systems and networks. Among several unique techniques, the Rutgers and Georgia Tech researchers are using cancer imaging techniques to detect intrusions and hacking of 3D printer controllers.
“Imagine outsourcing the manufacturing of an object to a 3D printing facility and you have no access to their printers and no way of verifying whether small defects, invisible to the naked eye, have been inserted into your object,” said Mehdi Javanmard, study co-author and assistant professor in the Department of Electrical and Computer Engineering at Rutgers University-New Brunswick. “The results could be devastating and you would have no way of tracing where the problem came from.”
3D printing, also called additive manufacturing, plays an increasingly important role in industrial manufacturing. But health- and safety-related products such as medical prostheses and aerospace and auto parts are being printed with no standard way to verify them for accuracy, the study says. Even houses and buildings are being manufactured by 3D printers, noted Javanmard.
Instead of spending up to $100,000 or more to buy a 3D printer, many companies and organizations send software-designed products to outside facilities for printing, Zonouz said. But the firmware in printers may be hacked.
For their study, the researchers bought several 3D printers and showed that it’s possible to hack into a computer’s firmware and print defective objects. The defects were undetectable on the outside but the objects had holes or fractures inside them.
Other researchers have shown in a YouTube video how hacking can lead to a defective propeller in a drone, causing it to crash, Zonouz noted.
While anti-hacking software is essential, it’s never 100 percent safe against cyberattacks. So the Rutgers and Georgia Tech researchers looked at the physical aspects of 3D printers.
In 3D printing, the software controls the printer, which fulfills the virtual design of an object. The physical part includes an extruder or “arm” through which filament (plastic, metal wire or other material) is pushed to form an object.
The researchers observed the motion of the extruder, using sensors, and monitored sounds made by the printer via microphones.
“Just looking at the noise and the extruder’s motion, we can figure out if the print process is following the design or a malicious defect is being introduced,” Zonouz said.
A third method they developed is examining an object to see if it was printed correctly. Tiny gold nanoparticles, acting as contrast agents, are injected into the filament and sent with the 3D print design to the printing facility. Once the object is printed and shipped back, high-tech scanning reveals whether the nanoparticles – a few microns in diameter – have shifted in the object or have holes or other defects.
“This idea is kind of similar to the way contrast agents or dyes are used for more accurate imaging of tumors as we see in MRIs or CT scans,” Javanmard said.
The next steps in their research include investigating other possible ways to attack 3D printers, proposing defenses and transferring methods to industry, Zonouz said.
“You’ll see more types of attacks as well as proposed defenses in the 3D printing industry within about five years,” he said.
Story by Todd Bates for Rutgers Today
Photo: Christian Bayens/Georgia Institute of Technology
A team from WINLAB comprising ECE graduate student Bhargav Gokalgandhi, researcher Prasanthi Maddala and Associate Director Ivan Seskar has won the 3rd prize at the RF Network on Chip (RFNoC) and Vivaldo Challenge. This challenge sponsored by Ettus Research and Xilinx Inc. rewards engineers for creating innovative open-source RF Network on Chip (RFNoC) blocks that will add to the library of available open-source blocks for programming FPGAs in Software Defined Radio development and production. The team designed a wide band channel sounder that computes the power delay profile of a multipath channel in a massive multiple antenna system.
Please find more details about the competition here
Congratulations Bhargav, Prasanthi and Ivan!
A team from Rutgers comprising ECE Professors Narayan Mandayam and Janne Lindqvist along with Professor Arnold Glass from Psychology has received an Early Concept Grant for Exploratory Research (EAGER) award from the NSF for a project titled "Simulated and Synthetic Data for Interdependent Communications and Energy Critical Infrastructures." This is a 2 year $200,000 project in collaboration with Florida International University (FIU), with Rutgers' share of the award being $100,000.
As part of this exploratory project, the Rutgers and FIU team will develop new mathematical foundations and computer-based learning theories for generating a wide range of simulated data sets (obtained via down sampling, aggregation of actual data) and fully-synthetic data sets (obtained via emulation and human subject studies) that model interdependence between communications and energy infrastructures. Specifically, the Rutgers team will develop synthetic data for communications critical infrastructure using the ORBIT Testbed as well as human subject studies for prosumer participation in the smart grid under emergencies. The synthetic data generated will be linked to the simulated power system data generated at FIU using transfer learning techniques. These enhanced data sets and associated data building tools will provide large-scale test data related to interdependent critical infrastructures operation.
Congratulations Narayan, Janne and Arnold!