Georgia Tech News | The Contracting Education Academy

August 17, 2018 By cs

Georgia Tech researchers help close security hole in popular encryption software

Cybersecurity researchers at the Georgia Institute of Technology have helped close a security vulnerability that could have allowed hackers to steal encryption keys from a popular security package by briefly listening in on unintended “side channel” signals from smartphones.

The attack, which was reported to software developers before it was publicized, took advantage of programming that was, ironically, designed to provide better security. The attack used intercepted electromagnetic signals from the phones that could have been analyzed using a small portable device costing less than a thousand dollars. Unlike earlier intercept attempts that required analyzing many logins, the “One & Done” attack was carried out by eavesdropping on just one decryption cycle.

“This is something that could be done at an airport to steal people’s information without arousing suspicion and makes the so-called ‘coffee shop attack’ much more realistic,” said Milos Prvulovic, associate chair of Georgia Tech’s School of Computer Science. “The designers of encryption software now have another issue that they need to take into account because continuous snooping over long periods of time would no longer be required to steal this information.”

The side channel attack is believed to be the first to retrieve the secret exponent of an encryption key in a modern version of OpenSSL without relying on the cache organization and/or timing. OpenSSL is a popular encryption program used for secure interactions on websites and for signature authentication. The attack showed that a single recording of a cryptography key trace was sufficient to break 2048 bits of a private RSA key.

Results of the research, which was supported in part by the National Science Foundation, the Defense Advanced Research Projects Agency (DARPA), and the Air Force Research Laboratory (AFRL) will be presented at the 27th USENIX Security Symposium August 16th in Baltimore.

After successfully attacking the phones and an embedded system board – which all used ARM processors – the researchers proposed a fix for the vulnerability, which was adopted in versions of the software made available in May.

Side channel attacks extract sensitive information from signals created by electronic activity within computing devices during normal operation. The signals include electromagnetic emanations created by current flows within the devices computational and power-delivery circuitry, variation in power consumption, and also sound, temperature and chassis potential variation. These emanations are very different from communications signals the devices are designed to produce.

In their demonstration, Prvulovic and collaborator Alenka Zajic listened in on two different Android phones using probes located near, but not touching the devices. In a real attack, signals could be received from phones or other mobile devices by antennas located beneath tables or hidden in nearby furniture.

The “One & Done” attack analyzed signals in a relatively narrow (40 MHz wide) band around the phones’ processor clock frequencies, which are close to 1 GHz (1,000 MHz). The researchers took advantage of a uniformity in programming that had been designed to overcome earlier vulnerabilities involving variations in how the programs operate.

“Any variation is essentially leaking information about what the program is doing, but the constancy allowed us to pinpoint where we needed to look,” said Prvulovic. “Once we got the attack to work, we were able to suggest a fix for it fairly quickly. Programmers need to understand that portions of the code that are working on secret bits need to be written in a very particular way to avoid having them leak.”

The researchers are now looking at other software that may have similar vulnerabilities, and expect to develop a program that would allow automated analysis of security vulnerabilities.

“Our goal is to automate this process so it can be used on any code,” said Zajic, an associate professor in Georgia Tech’s School of Electrical and Computer Engineering. “We’d like to be able to identify portions of code that could be leaky and require a fix. Right now, finding these portions requires considerable expertise and manual examination.”

Side channel attacks are still relatively rare, but Prvulovic says the success of “One & Done” demonstrates an unexpected vulnerability. The availability of low-cost signal processing devices small enough to use in coffee shops or airports could make the attacks more practical.

“We now have relatively cheap and compact devices – smaller than a USB drive – that are capable of analyzing these signals,” said Prvulovic. “Ten years ago, the analysis of this signal would have taken days. Now it takes just seconds, and can be done anywhere – not just in a lab setting.”

Producers of mobile devices are becoming more aware of the need to protect electromagnetic signals of phones, tablets and laptops from interception by shielding their side channel emissions. Improving the software running on the devices is also important, but Prvulovic suggests that users of mobile devices must also play a security role.

“This is something that needs to be addressed at all levels,” he said. “A combination of factors – better hardware, better software and cautious computer hygiene – make you safer. You should not be paranoid about using your devices in public locations, but you should be cautious about accessing banking systems or plugging your device into unprotected USB chargers.”

In addition to those already mentioned, the research involved Monjur M. Alam, Haider A. Khan, Moumita Dey, Nishith Sinha and Robert Callen, all of Georgia Tech.

This work has been supported, in part, by the National Science Foundation under grant 1563991 and by the Air Force Research Laboratory and DARPA LADS under contract FA8650-16-C-7620. The views and findings in this paper are those of the authors and do not necessarily reflect the official views of NSF, DARPA or the AFRL.

Source: https://www.news.gatech.edu/2018/08/09/researchers-help-close-security-hole-popular-encryption-software

August 3, 2018 By cs

Georgia Tech receives $1.6 million for nuclear energy projects

The Department of Energy (DOE) recently awarded the Georgia Institute of Technology $1.6 million in two grants for testing materials used in producing nuclear energy.

DOE is awarding $47 million through its Nuclear Energy University Program (NEUP) to support 63 university-led nuclear energy research and development projects in 29 states. NEUP seeks to maintain U.S. leadership in nuclear research across the country by providing top science and engineering faculty and their students opportunities to develop innovative technologies and solutions for civil nuclear capabilities.

“Because nuclear energy is such a vital part of our nation’s energy portfolio, these investments are necessary to ensuring that future generations of Americans will continue to benefit from safe, clean, reliable, and resilient nuclear energy,” said Ed McGinnis, DOE’s principal deputy assistant secretary for nuclear energy. “Our commitment to providing researchers with access to the fundamental infrastructure and capabilities needed to develop advanced nuclear technologies is critical.”

The awards are dispersed under three DOE nuclear energy programs: the Nuclear Energy University Program (NEUP), the Nuclear Energy Enabling Technologies (NEET) program, and the Nuclear Science User Facilities (NSUF) program.

Georgia Tech’s projects are funded by the NEUP. The first is for corrosion testing of new alloys and accompanying on-line reduction oxidation measurements in the flow loops of Oak Ridge National Laboratory (ORNL) eutectic alkaline metal fluoride salt mixture, specifically the molten salts lithium fluoride, sodium fluoride, and potassium fluoride (also called FLiNaK) as well as lithium fluoride and beryllium fluoride (or FLiBe.)

“The structural alloys in fluoride salt-cooled high-temperature reactors (FHR) will be exposed to molten fluoride salt mixtures at high temperatures, which can be very corrosive depending on the alloy composition and the presence of impurities in the molten salt. It is very important to test the candidate alloys under potential FHR conditions and understand the corrosion mechanisms in order to select the right alloys to use in building the structure of a reactor,” said Preet M. Singh, principal investigator on the project from Georgia Tech’s School of Materials Science and Engineering.

In the second project, a modeling and simulation tool will be developed to perform highly accurate and efficient transient calculations in the FHRs.

“Accurate and efficient modeling and simulation tools are needed to support design optimization, analysis, licensing, and eventual deployment of any reactor,” said Farzad Rahnema, the project’s principal investigator and Georgia Power Company Distinguished Professor of Nuclear Engineering in Georgia Tech’s George W. Woodruff School of Mechanical Engineering. “The current tools are inadequate for modeling advanced reactors such as the FHRs because of their complex geometry and high heterogeneity. The capability to perform transient calculations with high fidelity is an important component of licensing first-of-a-kind reactors, where experimental data are lacking or scarce.”

The DOE awards are for three years.

Learn more at the DOE’s Office of Nuclear Energy website.

Source: http://www.news.gatech.edu/2018/07/12/georgia-tech-receives-16-million-nuclear-energy-projects

July 9, 2018 By cs

Georgia Tech team receives DARPA grant to apply neuroscience to machine learning

Siri knows where you live, but she couldn’t drive you there.

Despite their name, artificial neural networks are very different from the brain. Yet machine learning performance could be improved if informed by state-of-the-art neuroscience.

A team of researchers from Georgia Tech and other local universities would study this problem with a grant up to $2 million, dependent on successful completion of milestones, from the Defense Advanced Research Projects Agency’s (DARPA) Lifelong Learning Machines (L2M) program managed by Dr. Hava Siegelmann. DARPA’s goal would be to develop new machine learning approaches that enable systems to learn continually while they operate and apply prior knowledge to new situations.

School of Computer Science Professor Constantine Dovrolis, Georgia Tech Research Institute Senior Research Scientist Zsolt Kira, Georgia State University neuroscience Professor Sarah Pallas, and Emory biology Associate Professor Astrid Prinz are collaborating on the two-year project.

Bringing Neural Networks to the 21st Century

The concept of modeling a computational neural network based on the brain first arose in the 1950s, but it hasn’t evolved much since.

“Obviously, since the ‘50s there’s been a lot of progress in neuroscience, but not a lot of it has translated to machine learning,” Kira said. “Supervised machine learning through neural networks is fundamentally a computer scientist’s translation of a high-level understanding of the brain from the past. But I think there’s a lot we can learn from contemporary neuroscience.”

One of the fundamental problems of machine learning that neuroscience could alleviate is what Dovrolis calls “catastrophic forgetting.” When the artificial neural network learns a new task, it often forgets the previous one.

“Deep learning networks are very different from the brain, both in terms of structure (architecture) and function (dynamics),” Dovrolis said.

Take the brain of a baby. Within the first few years of life, it not only has the ability to learn but also to generalize with very little supervision. Dovrolis believes that machine learning can achieve the same goal but only through a major departure from the currently established machine learning paradigms.

“The brain is really the only example of general intelligence we have,” Dovrolis said. “It makes sense to take that example, identify its fundamental principles, and transfer them to the computational domain.”

Bridging the Gap between Neuro and Computer Science

It may make sense, but it’s also controversial. Many computer scientists see the brain as mere hardware, and they prefer to focus instead on more statistical machine learning approaches. This is why this project is so unique: It brings together different ideas from network science, machine learning, evolutionary computing, computational neuroscience, and systems neuroscience — fields that should’ve been working together from the start.

“It’s easier for each field to work by themselves because it’s very comfortable,” Kira said. “But there’s a lot of potential if you actually make the effort to bring people together.”

Yet working with neuroscientists doesn’t just benefit computer scientists. Many neuroscientists believe computing could help with better modeling of biological networks, and ultimately, a deeper understanding of how the brain works.

“Neuroscience can, in turn, be guided by results from machine learning research that can inform new experiments to deepen our understanding of the brain,” Prinz said.

One of these examples is the flexibility of the brain.

“Neural circuits in the developing brain are highly flexible and adaptable to environmental changes, which endows them with an ability to learn rapidly and to self-repair after damage,” Pallas said.

Adult brains are much less plastic, so one of the neuroscientists’ goals is to uncover the neuronal mechanism that regulates the level of plasticity versus stability in brain circuits. With this, they can harness the mechanism for medical purposes and design machines that can continue learning without forgetting.

Approaching the Research

The project should attempt to address five goals of the L2M program:

• Continual learning: The building block of the cortex is a largely invariant structure referred to as a “cortical column.” The function of cortical columns is not known yet, but it seems that they act as associative memories and predictors. The structure of cortical columns suggests that recurrent neural networks could learn incrementally and in an unsupervised manner simply by interacting with the environment.

• Adaptation to new tasks/environments: These cortical columns could interconnect through deep brain-wide hierarchies and nested feedback loops that interact and inform each other, enabling the brain to adapt to different environments with minimal need for retraining.

• Goal-driven perception: At any time, the brain is receiving data from many sensory sources. Hierarchical neural networks could use task-driven inputs to adjust low-level sensory processing and integration dynamically, depending on top-down goal-related signals.

• Selective plasticity: The project should be investigating how the connections and weights between (artificial) neurons could be adjusted when a new task is encountered, without catastrophically forgetting previous tasks. Neuromodulator-driven plasticity and homeostatic plasticity are two biological mechanisms that could be transferred in machine learning to address this problem.

• Monitoring and safety: Researchers would also investigate how to ensure stability and safety, based on the organization of the brain’s autonomic nervous system. Additionally, the safety concern could be further addressed through an “artificial impulse control” system, operating on the same prediction principles as the corresponding cortical system.

This research could allow machine learning to become increasingly adaptive and continually learn, which could have vast applications. A self-driving car could be programmed in the summer, but with these principles, it could learn how to drive in previously untested winter conditions. Siri could be next.

Source: https://www.gtri.gatech.edu/newsroom/georgia-tech-team-receives-darpa-grant-apply-neuroscience-machine-learning

June 18, 2018 By cs

FBI: Reset your router or face Russian malware

It’s not every day that the Federal Bureau of Investigation gives you an order.

On May 25 the FBI asked members of the public to turn off and turn back on their routers because of the spread of malware called “VPNFilter” created and distributed by the Russian hacker network Sofacy.

Georgia Tech Senior Research Scientist Charles “Chaz” Lever explained the damage this malware can do:

“This malware will affect the average user by using one of the capabilities in the malware to passively collect traffic. This can be used to harvest banking credentials or other sensitive password information that is going over the home network. Additionally, your home network could be hijacked to be part of an attack on a remote entity, masking the identity of the original user and potentially putting you in the crosshairs of law enforcement.”

In addition to just a simple reboot, Lever recommended following the manufacturer’s instructions on resetting the software in the device, also known as “firmware.”

Source: http://www.news.gatech.edu/2018/06/06/fbi-reset-your-router-or-face-russian-malware

Learn more about cybersecurity research at Georgia Tech by visiting the Institute for Information Security and Privacy.

Watch a YouTube video on this subject by clicking on the image below:

Recently the Federal Bureau of Investigation (FBI) issued a critical warning for all Americans to reset their routers for homes and small businesses in an effort to disrupt a potential cyber attack. We sat down with Georgia Tech’s senior research scientist, Charles “Chaz” Lever, to find out just what this threat contains and how serious it can potentially be.

June 11, 2018 By cs

Cybersecurity training program at Georgia Tech prepares ROTC students for service

Cybersecurity has become one of the most serious economic and national security challenges that the U.S. faces today, but it’s one that the government is not adequately prepared to counter.

The global cybersecurity workforce is expected to be short 1.8 million workers by 2022, leaving an enormous gap that begs to be filled. For the Department of Defense (DoD) and armed services, this means a greater focus on attracting top cyber talent who can defend the nation against the threat of cyber warfare.

Georgia Tech and other top universities across the nation are taking part in a program that enables Reserve Officer Training Corps (ROTC) cadets and midshipmen to become cyber security experts. The Cyber Spectrum Collaborative Research Environment (C-SCoRE) program helps cadets develop operational skills that will be instrumental in combatting cyber and electronic warfare in the interest of national security. Dr. Bill Melvin, director of Georgia Tech Research Institute’s Sensors and Intelligent Systems Division and adjunct electrical and computer engineering professor, had the original vision for the program. Melvin is also a former Air Force officer and ROTC cadet himself.

Georgia Tech’s School of Electrical and Computer Engineering (ECE) received joint funding from the Air Force and Navy this year to hire ROTC students into the program. Dr. Vincent Mooney, associate professor in ECE, leads one of the teams, focusing on Bluetooth and Near Field Communication threats, secure boot for microprocessors, and vulnerabilities in power grid electronics and their effect on security.

“It’s critically important for cadets to learn these cyber skills,” said Mooney. “The military wants to learn from the Internet of Things – for strategic benefits like improved communication – but existing security weaknesses can leave the nation open to being manipulated by our adversaries.”

Mooney goes on to explain that when students participate in the C-SCoRE program, they gain the operational skills and perspective on how to defend against cyber attacks. Even learning the basics – such as authentication, encryption and technology for true random number generation – can help protect systems from being hacked.

“It’s been really interesting for me to go into this field of study that’s going to have such an impact on my life in the fleet,” said Belle Lehmann, Navy cadet and ISyE major at Georgia Tech. “Cybersecurity is going to be really important in the future. C-SCoRE has broadened my horizons and my understanding of so many things.”

“I’m a computer science major, and cybersecurity has been a passion of mine since high school,” said Alexander Hennie-Roed, Navy cadet and computer science major at Georgia Tech. “Right now, I’m working with power grids, and I’m hoping the Navy will want to utilize those skills.”

Chris Smith, principal research engineer at the Georgia Tech Research Institute, is one of the project directors of the C-SCoRE program. He agrees that there is a real need for cybersecurity officers who are knowledgeable and trained in cyber warfare.

“Often, cadets graduate from ROTC without having any operational experience,” said Smith. “The hands-on, experiential learning from C-SCoRE ensures they are savvier about cyber and electronic warfare upon graduation.”

C-SCoRE meets a critical need for the armed services, as they consider how to restructure the departments around hiring cybersecurity talent. Various organizations in the DoD and federal government are very interested in hiring students with C-SCoRE experience. And students are coming out of the program much more well-rounded and ready to address today’s modern challenges.

If interested in participating in the C-SCoRE Program at Georgia Tech, please contact Associate Professor Vincent Mooney and Julie Ridings, assistant director for the Opportunity Research Scholars (ORS) Program, for more information.

Source: https://coe.gatech.edu/news/cyber-security-training-program-georgia-tech-prepares-rotc-students-service