Kurt Rohloff is an associate professor of computer science at NJIT and the co-founder and director of the NJIT Cybersecurity Research Center. His research interests are in encrypted computing, homomorphic encryption, lattice-based cryptography, applied cryptography, cybersecurity, distributed information management, information access delegation, key management, software engineering, high-assurance design, mobile systems and secure communication protocols. Rohloff received his Bachelor of Electrical Engineering degree from the Georgia Institute of Technology in Atlanta, and his Master of Science and doctorate in electrical engineering from the University of Michigan, Ann Arbor.
Areas of Expertise (7)
Cryptography Computer Security and Privacy
DARPA Director's Fellowship
DARPA Young Faculty Award
University of Michigan: Ph.D., Electrical Engineering: Systems 2004
University of Michigan: M.S., Electrical Engineering: Systems 2001
Georgia Institute of Technology: B.E.E., Electrical Engineering 1999
- Duality Technologies
Media Appearances (5)
Safety in Numbers: Computer Scientist Races to Develop Unhackable Code to Protect Everyone’s Data
Tap Into Newark
Kurt Rohloff stands squarely against these invisible forces. Co-founder of the cybersecurity start-up, Duality Technologies, and director of the NJIT Cybersecurity Research Center, Rohloff is working full-throttle from his Newark base with the ambitious mission of developing a new worldwide cybersecurity standard that will be unhackable...
Wyden, Rubio, Warner Introduce “Student Right to Know Before You Go Act” to Empower Students as Consumers and Showcase New Privacy-Protecting Technology
Senator Ron Wyden Official Website
"Insight into the financial benefits of education choices would be invaluable to students trying to navigate the modern marketplace of higher education, allowing them to make much more informed choices. Privacy-preserving technologies that enable computing on data while encrypted is far and away the best way to provide these insights while also protecting the privacy of US citizens."...
After Equifax breach, how worried should you be about your personal information?
Computer Science Professor at the New Jersey Institute of Technology Kurt Rohloff said it’s more than just a small inconvenience. “I would say it definitely pays off in the long run. It’s definitely what I’d be doing if I were in that situation,” he said. Rohloff is also the co-founder and director of NJIT’s Cybersecurity Research Center. When asked if breaches are taking place more often or is it more often that we’re hearing about them, he replied, “Probably both.”...
DARPA Protecting Software From Reverse Engineering Through Obfuscation
Kurt Rohloff, an Associate Professor of Computer Science professor at NJIT, who heads up SafeWare, spoke to Signal Magazine today about the group’s work and insisted that while there are plenty of challenges ahead, the group is still in the early stages and that there is no particular application it was focusing on yet. “I have a particular interest in supporting military-relevant applications, but the challenge that we’re facing right now is that this was just a brand spanking new theoretical innovation and there hasn’t been any real serious effort to get this thing to work in a way that would be practical,” Rohloff told the magazine. “The immediate goal that we’re focusing on is knocking off a couple orders of magnitude to get a handle on how efficient these things can be so we can get a handle on what are the specific operations,” Rohloff said, adding that eventually he hopes SafeWare can eventually develop a sort of “open-source library for lattice crypto technology.”...
OPM breach a failure on encryption, detection
Not all experts agree. Kurt Rohloff, associate professor at the New Jersey Institute of Technology and director of the NJIT Cybersecurity Center questioned the claim that legacy systems can't support encryption. "The statement that legacy systems cannot encrypt may not be completely true," Rohloff said. "It may be very expensive to integrate encryption technologies with legacy systems but it is generally possible."...
Event Appearances (8)
Prototyping and Using Encrypted Computing Technologies to Protect Data
iSense Seminar Florida Atlantic University
Computing on Encrypted Data
Waseda Univeristy Computer Science Seminar Waseda Univeristy, Tokyo, Japan
Approaches to Indistinguishability Obfuscation
Tandon School of Engineering New York University
Everything you Wanted to Know about DARPA but were Afraid to Ask
Computer Science Seminar NJIT
Implementing Homomorphic Encryption to Enable Practical and Secure Computing
University of Tartu Computer Research Seminar University of Tartu
Privacy-Preserving Publish-Subscribe using End-to-End Encryption
Workshop on Surveillance & Technology held with the Privacy Enhancing Technologies Symposium (PETS) Philadelphia, PA
Applying Homomorphic Encryption for Practical Genomic Privacy
Dagstuhl Seminar 15431 Dagstuhl, Germany
Towards Practical Implementations of Fully Homomorphic Encryption
Algebra and Cryptography Seminar City University of New York
System and method for merging encryption data without sharing a private key
Kurt Rohloff April 18, 2017
System and method to merge encrypted signals in distributed communication system
Kurt Rohloff October 4, 2016
System and method for encoding encrypted data for further processing
Kurt Rohloff and David Bruce Cousins April 18, 2017
System and Method for Mixing VoIP Streaming Data for Encrypted Processing
Kurt Rohloff and David Bruce Cousins June 14, 2016
System and method for operating on streaming encrypted data
Kurt Rohloff May 10 2016
System and method for merging encryption data using circular encryption key switching.\
Kurt Rohloff April 26, 2016
System and method to merge encrypted signals in distributed communication system
Kurt Rohloff April 12, 2016
Research Grants (7)
ONR Human-AI Symbiosis for Agile Planning
Offie of Naval Research $523,000
GEARS: GENOMIC ANALYSIS RESEARCH WITH SECURITY
National Institutes of Health $149,500
We propose the GEARS (GEnomic Analysis Research with Security) effort with the broad goal and vision of our proposal is to enable collaboration and joint analysis of medical data, without compromising data owners’ rights and complying with regulation and privacy concerns. This is achieved by introducing novel technologies from the domain of advanced cryptography that enable keeping raw data encrypted even while analyzing and computing on it...
Fully Homomorphic Encryption Research
Alfred P. Sloan Foundation $509,038
2017 Fully Homomorphic Encryption (FHE) allows researchers to analyze encrypted data accurately without decrypting those data. It is an intriguing method for providing access to sensitive datasets while respecting both privacy concerns and licensing agreements and may eventually have significant use in privacy-protecting research protocols. This grant funds a project to demonstrate the usefulness of FHE algorithms in academic research.
Young Faculty Award MARSHAL
I2O Safeware, PALISADE
I2O SafeWare OPERA
International Crisis Early Warning System
Kurt Rohloff, David Bruce Cousins
2014 In this paper we report on our work to design, implement and evaluate a Fully Homomorphic Encryption (FHE) scheme. Our FHE scheme is an NTRU-like cryptosystem, with additional support for efficient key switching and modulus reduction operations to reduce the frequency of bootstrapping operations. Ciphertexts in our scheme are represented as matrices of 64-bit integers. The basis of our design is a layered software services stack to provide high-level FHE operations supported by lower-level lattice-based primitive implementations running on a computing substrate. We implement and evaluate our FHE scheme to run on a commodity CPU-based computing environment. We implemented our FHE scheme to run in a compiled C environment and use parallelism to take advantage of multi-core processors. We provide experimental results which show that our FHE implementation provides at least an order of magnitude improvement in runtime as compared to recent publicly known evaluation results of other FHE software implementations.
David Bruce Cousins, Kurt Rohloff, Chris Peikert, Rick Schantz
2012 Accelerating the development of a practical Fully Homomorphic Encryption (FHE) scheme is the goal of the DARPA PROCEED program. For the past year, this program has had as its focus the acceleration of various aspects of the FHE concept toward practical implementation and use. FHE would be a game-changing technology to enable secure, general computation on encrypted data, e.g., on untrusted off-site hardware. However, FHE will still require several orders of magnitude improvement in computation before it will be practical for widespread use. Recent theoretical breakthroughs demonstrated the existence of FHE schemes, and to date much progress has been made in both algorithmic and implementation improvements. Specifically our contribution to the Proceed program has been the development of FPGA based hardware primitives to accelerate the computation on encrypted data using FHE based on lattice techniques. Our project, SIPHER, has been using a state of the art tool-chain developed by Mathworks to implement VHDL code for FPGA circuits directly from Simulink models. Our baseline Homomorphic Encryption prototypes are developed directly in Matlab using the fixed point toolbox to perform the required integer arithmetic. Constant improvements in algorithms require us to be able to quickly implement them in a high level language such as Matlab. We reported on our initial results at HPEC 2011. In the past year, increases in algorithm complexity have introduced several new design requirements for our FPGA implementation. This report presents new Simulink primitives that had to be developed to deal with these new requirements.
Kurt Rohloff, Richard E Schantz
2011 Graph data processing is an emerging application area for cloud computing because there are few other information infrastructures that cost-effectively permit scalable graph data processing. We present a scalable cloud-based approach to process queries on graph data utilizing the MapReduce model. We call this approach the Clause-Iteration approach. We present algorithms that, when used in conjunction with a MapReduce framework, respond to SPARQL queries over RDF data. Our innovation in the Clause-Iteration approach comes from 1) the iterative construction of query responses by incrementally growing the number of query clauses considered in a response, and 2) our use of flagged keys to join the results of these incremental responses. The Clause-Iteration algorithms form the basis of our scalable, SHARD graph-store built on the Hadoop implementation of MapReduce. SHARD performs favorably when compared to existing "industrial" graph-stores on a standard benchmark graph with 800 million edges. We discuss design considerations and alternatives associated with constructing scalable graph processing technologies.
Kurt Rohloff, Richard E Schantz
2010 In this paper we discuss the use of the MapReduce software framework to address the challenge of constructing high-performance, massively-scalable distributed systems. We discuss several design considerations associated with constructing complex distributed systems using the MapReduce software framework, including the difficulty of scalably building indexes. We focus on Hadoop, the most popular MapReduce implementation. Our discussion and analysis are motivated by our construction of SHARD, a massively scalable, high-performance and robust triple-store technology on top of Hadoop. We provide a general approach to construct an information system from the MapReduce software framework that responds to data queries. We provide experimental results generated of an early version of SHARD. We close with a discussion of hypothetical MapReduce alternatives that can be used for the construction of more scalable distributed computing systems.
Kurt Rohloff, Mike Dean, Ian Emmons, Dorene Ryder, John Sumner
2007 This paper presents a comparison of performance of various triple-store technologies currently in either production release or beta test. Our comparison of triple-store technologies is biased toward a deployment scenario where the triple-store needs to load data and respond to queries over a very large knowledge base (on the order of hundreds of millions of triples.) The comparisons in this paper are based on the Lehigh University Benchmark (LUBM) software tools. We used the LUBM university ontology, datasets, and standard queries to perform our comparisons. We find that over our test regimen, the triple-stores based on the DAML DB and BigOWLIM technologies exhibit the best performance among the triple-stores tested.