We sat down with UMBC M.P.S. Data Science graduate student, Spandan Gupta, to talk about her journey from India to America to study. She shares candid insights about her experiences.

“The data science industry has been growing, and I felt the U.S. was the best place to begin my search for graduate work because it’s the hub. So I read every news article I could find on universities for data science in the U.S. I found ten universities having a data science master’s focus. From there, I landed on UMBC’s website. Not only did UMBC offer a master’s program, but they offered a master’s in professional studies (MPS). In addition to analytics, machine learning, and algorithms, this program also included management and ethical concentrations, which is why I shortlisted UMBC and eventually decided it was the place I wanted to study.” Spandan Gupta

WHEN:

Friday, June 5, 2020 · 3 PM - 3:30 PM

The Career Center is inviting you to the Northrop Grumman FTL Information Session. This event will be held ONLINE at the following link: https://umbc.webex.com/umbc/onstage/g.php?MTID=e7d0d534d1846a81bdd54a408b814d3b2.

Event number: 471 716 279

Event password: qhUXj53Drh4

Northrop Grumman Future Technical Leaders (FTL) Program

WHO: 
Master's and Ph.D. candidates in science, technology, engineering & math

U.S. Citizenship is Required

At Northrop Grumman, we’ve developed the Future Technical Leaders (FTL) Program - a professional development opportunity aimed at identifying and investing in Northrop Grumman’s next generation of technologists, engineers, architects and leaders. 

The FTL Program is seeking talented STEM MS and PhD 2020-2021 graduates interested in learning more about our exclusive three-year professional development program aimed at identifying and investing in Northrop Grumman’s next generation of technologists, engineers, architects and leaders. U.S. citizenship required.

If you qualify, please see job ID # 9316554 in UMBCworks.

Interviews for selected candidates will be held in September.

Please visit ftlprogram@ngc.com for more information.

May 15, 2020
Megan Hanks

Naghmeh Karimi is the most recent UMBC faculty member to receive a prestigious CAREER Award from the National Science Foundation (NSF). The grant, totaling approximately $500,000 over five years, will support her work to investigate how device-aging related risks compromise the security of cryptographic devices.

Karimi explains that cryptographic chips offer continued advances in authenticating messages and devices as well as preserving the integrity and confidentiality of sensitive information. They do so by implementing cryptographic algorithms in hardware. These chips combine the benefits of cryptographic applications with the speed and power advantage of hardware implementations. 

Despite their significant benefits, cryptographic chips can be compromised by adversaries who have gained physical access to the chips. Current protections against such attacks do not consider the aging of devices, which can shift device parameters over time.

Addressing security vulnerabilities 

Aging makes cryptographic chips operate slower and, ultimately, results in their malfunction, says Karimi. She explains that the typical lifetime of integrated circuits is 7 to 8 years. As the devices age, their performance decreases. Karimi is exploring the specific security vulnerabilities of aged devices and how they can be protected.

“We want to preserve the security of devices over their lifetime,” Karimi says.

Karimi and her research team will study whether the success of the side-channel analysis and fault-injection attacks increase in older devices. Karimi will create and test several countermeasures to protect devices against such attacks.

Connecting students with opportunities in tech security

The CAREER Award funding will support several UMBC undergraduate and graduate student researchers working with Karimi to develop long-lasting security solutions for hardware platforms. 

At the same time, Karimi will also develop and launch a new course in UMBC’s computer science and electrical engineering department on cryptography, hardware security, and testing. She will also work with the UMBC Cyber Scholars Program to connect students with internship opportunities focused on hardware security, to give them additional hands-on experience in the field. 

“The success of this project will enable us to develop long-lasting security for trusted hardware platforms,” Karimi says. “This will result in aging-resistant security solutions that benefit society through devices that remain secure over their lifetime.”

Image: UMBC’s ITE building. Photo by Marlayna Demond ’11 for UMBC.

The rise in popularity of Internet of Things (IoT) devices has opened doors for privacy and security breaches in Cyber-Physical systems like smart homes, smart vehicles, and smart grids that affect our daily existence. IoT systems are also a source of big data that gets shared via the cloud. IoT systems in a smart home environment have sensitive access control issues since they are deployed in a personal space. The collected data can also be of a highly personal nature. Therefore, it is critical to building access control models that govern who, under what circumstances, can access which sensed data or actuate a physical system. Traditional access control mechanisms are not expressive enough to handle such complex access control needs, warranting the incorporation of new methodologies for privacy and security. In this paper, we propose the creation of the PALS system, that builds upon existing work in an attribute-based access control model, captures physical context collected from sensed data (attributes) and performs dynamic reasoning over these attributes and context-driven policies using Semantic Web technologies to execute access control decisions. Reasoning over user context, details of the information collected by the cloud service provider, and device type our mechanism generates as a consequent access control decisions. Our system’s access control decisions are supplemented by another sub-system that detects intrusions into smart home systems based on both network and behavioral data. The combined approach serves to determine indicators that a smart home system is under attack, as well as limit what data breach such attacks can achieve.

The post paper: Context Sensitive Access Control in Smart Home Environments appeared first on UMBC ebiquity.

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