talk: Hardware Security Kernel for Managing Memory and Instruction Execution, 12pm Fri 2/28

The UMBC Cyber Defense Lab presents

Hardware Security Kernel for Managing Memory and Instruction Execution

 Patrick Jungwirth, PhD

Computational and Information Sciences Directorate
Army Research Lab, Aberdeen Proving Ground, USA

12–1 pm Friday, 28 February 2020, ITE 227, UMBC

The cybersecurity world faces multiple attack vectors from hardware-level exploits, including cache bank malicious operations, rowhammer, Spectre, Meltdown, and Foreshadow attacks, and software-based attacks including buffer-overflows, et al.  Hardware-level exploits bypass protections provided by software-based separation kernels.  Current microprocessor execution pipelines are not designed to understand security:  they treat malicious instructions, software bugs, and harmless code the same. This presentation explores adding a hardware-level security monitor below the execution pipeline [1,2,3].

[1] P. Jungwirth, et al.:  “Hardware security kernel for cyber-defense,” Proc. SPIE 11013, Disruptive Technologies in Information Sciences II, 110130J, Baltimore 10 May 2019);
[2] P. Jungwirth, and J. Ross:  “Security Tag Fields and Control Flow Management,” IEEE SouthEastCon 2019, Huntsville, AL, April 2019.
[3] P. Jungwirth and D. Hahs:  “Transfer Entropy Quantifies Information Leakage,” IEEE SouthEastCon 2019, Huntsville, AL, April 2019.

About the SpeakerDr. Jungwirth is a computer architecture researcher at the Army Research Lab.  Previously he worked for the Aviation and Missile, RDEC in Huntsville, AL.  Currently, he is researching hardware state machines to provide simple operating system support (monitor) and control flow integrity in hardware.  Dr. Jungwirth is co-inventor of the OS Friendly Microprocessor Architecture, US Patent 9122610.  The OS Friendly Microprocessor Architecture includes hardware security features for an operating system and supports near single-cycle context switches in hardware. Email: 

Host: Alan T. Sherman, 

Support for this event was provided in part by the National Science Foundation under SFS grant DGE-1753681.

The UMBC Cyber Defense Lab meets biweekly Fridays.  All meetings are open to the public.

Upcoming CDL Meetings:

Mar 13, Hasan Cam, autonomous agents
Mar 27, Dan Yaroslaski, cybercommand
Apr 10, Russ Fink (APL), ransomware
Apr 24, TBA
May 8, Jason Wells, law enforcement
May 22, Spring SFS Meeting at UMBC, 9:30am-2pm, ITE 456

talk: Ian Blumenfeld on Interactive Proof Assistants for Verification, Fri 1/31

The UMBC Cyber Defense Lab presents

Interactive Proof Assistants for Verification

Ian Blumenfeld
Principal Research Mathematician
Two Six Labs

12:00-1:00 pm Friday,  31 January 2020, ITE 227

Many advances have been made in software and hardware assurance using automated tooling.  Constraint-based solving tools like SAT and SMT solvers have proved very useful proving functional correctness in the world of software, while the hardware world relies heavily on the use of industrial-strength model checkers to provide formal verification of important properties like liveness and non-interference.  Sometimes, however, push-button tools are simply not enough. In this talk, we will discuss formal mathematical reasoning using interactive proof assistants, particularly Isabelle. While Isabelle is often thought of as a tool for checking the work of mathematicians, it is, in fact, a powerful engine for reasoning about software and hardware security.  We will work through an example of the verification of a multi-precision arithmetic software library using Isabelle. This talk is aimed at total beginners in the realm of automated theorem proving, and seeks to provide an overview of the fundamental techniques and ideas. 

Ian Blumenfeld is a Principal Research Mathematician at Two Six Labs.  He currently is the principal investigator of TwoSix’s efforts on the DARPA SafeDocs program, attempting to help do type-theoretic reasoning about document specification formats.  He is a former employee of Apple where he worked on the formal verification team, ensuring the security of the iPhone SEP chip. He has done extensive work verifying cyber-physical systems at Johns Hopkins APL.  Mr. Blumenfeld’s interest in formal methods began with his time working as an Applied Research Mathematician in NSA’s Research Directorate. He’s also a pretty good swing dancer.

Host: Alan T. Sherman, 

Support for this event was provided in part by the National Science Foundation under SFS grant DGE-1753681. 

The UMBC Cyber Defense Lab meets biweekly Fridays.  All meetings are open to the public.

TALK: Reasoning About Time in a Crypto Protocol Analysis Tool

The UMBC Cyber Defense Lab presents

Reasoning About Time in a Crypto Protocol Analysis Tool

Dr. Catherine Meadows, Naval Research Laboratory

12:00–1:00pm Friday, 15 November 2019, ITE 227

The ability to guarantee timing properties, and in turn to use assumption about time to guarantee the security of protocols, is important to many of the applications we rely upon. For example, to compute locations, GPS depends on time synchronization between entities. Blockchain protocols require loose time synchronization to guarantee agreement on block timestamps. Distance-bounding protocols use the roundtrip time of an RF signal to enforce constraints on location. To analyze these types protocols formally, it is necessary to reason about time. This talk describes recent research in extending the Maude-NPA cryptographic protocol analysis tool to reason about cryptographic protocols that rely on or enforce timing properties. We describe the timing model we have created for the tool. We show how we we represent timing properties as constraints, whose solution is outsourced to an SMT solver. We also discuss our experimental results.

Catherine Meadows is a senior researcher in computer security at the Center for High Assurance Systems at the Naval Research Laboratory and heads that group’s Formal Methods Section. She was the principal developer of the NRL Protocol Analyzer (NPA), which was one of the first software tools to find previously undiscovered flaws in cryptographic protocols, and was used successfully in the analysis of a number of protocol standards. She is also leading, or has recently led, a number of projects related to the design and analysis of cryptographic protocols, including one focused the development of an analysis tool, Maude-NPA, that takes into account the the complex algebraic properties of cryptosystems, another that is focusing on the automatic generation of secure cryptosystems, and another devoted to formal methods for the design of cyber-physical systems with legacy components.

This work was supported by ONR 321 ()

Host: Alan T. Sherman, Support for this event was provided in part by the National Science Foundation under SFS grant 175368. The UMBC Cyber Defense Lab meets biweekly Fridays. All meetings are open to the public. Upcoming CDL Events:

  • December 6, Karl Henderson, Verisign
  • 9am—5pm daily, January 13-17, UMBC SFS/CySP Research Study, ITE 456
  • January 31, 2020, TBA, biweekly CDL talks resume

Talk: Dr.Rosenbloom on Three Related Takes on Investigating Human-Like Intelligence

On October 11th, 2019, Dr. Paul Roosenbloom, distinguished speaker from Lockheed Martin delivered a talk on ” Three Related takes on investigating Human-like intelligence”. This talk explored a trio of related takes on how to investigate the nature of human-like intelligence. The first concerns cognitive architectures – implemented models of the fixed structure and processes that yield natural and artificial minds – with a drill down to Sigma, an attempt at a deep synthesis across what has been learned over the past four decades on (what started as) high-level symbolic cognitive architectures versus the low-level graphical/network technologies of probabilistic graphical models (such as Bayesian networks) and neural networks. The second concerns a more abstract attempt at specifying a Common Model of Cognition that yields an evolving community consensus over what must be part of any cognitive architecture for human-like intelligence. The final take concerns an even more abstract (and speculative) attempt at understanding more deeply the space of approaches to intelligence – framed as maps resulting from cross products among core cognitive dichotomies – along with how such maps may help to understand and structure the capabilities required for (human-like) intelligence.

This event was attended by more than 100 members spilling out into the hallway.

Science Unscripted: Conversations with AI Experts, 5-8:00pm 29&30 Oct 2019, UMBC

On October 29 and 30 the National Science and Technology Medals Foundation will host Science Unscripted: Conversations with AI Experts, two early evening events at UMBC from 5:00 to 8:00pm that bring together AI experts to discuss how AI will impact our lives. The events will be held in the Fine Arts Recital Hall with doors open at 5:00 prior to the 5:30 start and will conclude with a reception starting at 7:00pm with food and drinks. Both events are free, but registration is requested.

These events are a part of the NSTMF’s Science Unscripted program. Through the SU program, the Foundation is building an inclusive coalition of inspired STEM students. By highlighting voices often left unheard in the STEM community, we show audiences that there is no “right” way to be a trailblazer in science and technology. Each evening, attendees will have the chance to hear about the lives and experiences of the women and men dedicated to creating smart, socially conscious AI.

Tuesday, Oct. 29: Code-ifying AI is a a discussion about AI policy. A panel including UMBC Professor Cynthia Matuszek, Dr. José-Marie Griffiths and moderated by Rosario Robinson will examine what it will take to govern AI as well as the implications of incorporating AI into our everyday lives. Register on Eventbright.

Wednesday, Oct. 30: Decoding Bias in AI is a panel discussion about implicit bias and how we can create more socially conscious AI with UMBC Professor James Foulds, Loretta Cheeks, Emmanuel Johnson and moderator Deborah Kariuki. Implicit bias remains one of the most prevalent concerns about incorporating AI into the mainstream, and our panel is poised to deliberate the ethics and possible solutions to this issue. Register on Eventbright.

The events will be webcast live with closed-captions on Facebook, and the full event videos will be available on our YouTube channel afterward. Webcast audiences are encouraged to participate in the conversation using #ScienceUnscripted on Twitter, Facebook and Instagram.

Both events are no-cost, equal access (ADA compliant), and open to the public. Save your seat on Eventbrite for day one at Code-ifying AI and for day two at Decoding Bias in AI.

National Science Foundation Graduate Research Fellowship Program Workshop

On October 3, 2019, Dr. Francis Ferraro presented a workshop for the National Science Foundation Graduate Research Fellowship Program (NSF GRFP).  During the workshop, Dr. Ferraro covered many topics including scholarship eligibility, funding, and the application process. He also provided a detailed application checklist as well as suggestions for developing personal and research statements. In addition to giving information about the NSF GRFP, Dr. Ferraro provided an overview of the graduate school experience.

Application deadline for the NSF GRFP is October 22, 2019.

The purpose of the NSF Graduate Research Fellowship Program (GRFP) is to help ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing full-time research-based master’s and doctoral degrees in science, technology, engineering, and mathematics (STEM) or in STEM education. The GRFP provides three years of support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM or STEM education. NSF especially encourages women, members of underrepresented minority groups, persons with disabilities, veterans, and undergraduate seniors to apply.

  • Three years of funding to use across five years (in 12 month blocks). Stipend: $34,000 per year. Tuition/education expenses: $12,000 per year.
  • Applicants must be US citizens, national or permanent residents. Applicants must be an undergraduate senior, or first or second year graduate student.
  • Registration information can be found here:
  • All registration materials should be submitted here:
  • TALK: Computer Aided Assessment of Computed Tomography Screenings

    UMBC ACM Chapter Talk

    Computer Aided Assessment of Pulmonary Nodule Malignancy in from Low Dose Computed Tomography Screenings

    Professor David Chapman, CSEE, UMBC

    11:30–12:30, Friday 11 October 2019, ITE 346, UMBC

    We propose to develop a novel quantitative algorithm to estimate the probability of malignancy of pulmonary nodules from a time series of successive LDCT screenings in patients with a high risk of developing lung cancer. Lung cancer kills approximately 200,000 Americans annually and is responsible for 25% of all cancer-related deaths. Imaging with Low Dose Computed Tomography (LDCT) has been proven to reduce Non-Small Cell Lung Cancer (NSCLC) mortality by 20% and has become standard guidelines (NLST 2011a,b). These new clinical guidelines have led to hospitals, including Mercy Medical Center in Baltimore, to collect an abundance of LDCT images of high risk individuals since 2014. These LDCT images along with additional CT/biopsy and PET/CT images collected by Mercy hospital in Baltimore have now been organized into an IRB exempt clinical research dataset to use anonymous radiology imagery for the purpose of training and evaluation of improved Computer Aided Diagnosis (CAD) algorithms. Imaging biomarkers including cross-sectional diameter, calcification patterns, irregular margins, wall thickness all of which are known to have discriminating power to differentiate benign and malignant pulmonary nodules. Furthermore, temporal changes in the size and biomarker characteristics of pulmonary nodules over multiple images are also highly informative and yield greater ability to differentiate malignancy. The proposed CAD algorithm will be capable of detecting and quantifying temporal changes of imaging biomakers in order to estimate malignancy probability. The algorithm will make use of convolutional neural networks for feature extraction as well as recurrent neural networks to analyze the temporal changes in extracted features. The Mercy hospital dataset contains approximately 30,000 chest CT images. Training of the algorithm will incorporate semi-supervised learning using chest CT images from Mercy as well as the public portion of the NLST dataset. A fraction of the Mercy images will be designated for evaluation of the sensitivity and specificity of the proposed algorithm for determining nodule malignancy. Pulmonary nodules remain a challenging area for clinical management decision-making, and improved analysis of malignancy including temporal changes of imaging biomarkers have the potential to reduce patient morbidity and mortality through earlier and more accurate diagnosis.

    Talk: Localization of Brain Activations Based on EEG Recordings and Sparse Signal Recovery Theory

    Lockheed Martin Distinguished Speaker Series

    Localization of Brain Activations Based on
    EEG Recordings and Sparse Signal Recovery Theory

    Professor Athina Petropulu

    Electrical and Computer Engineering Rutgers University

    1:00-2:00pm Friday, 1 November 2019

    Room 104, ITE Building, UMBC

    Sparse signal recovery is often formulated as an l1-norm minimization problem. However, unless certain conditions are satisfied, there is no guarantee that the least l1-norm solution will also be a sparsest solution. In this talk, we show that by appropriately weighting the sensing matrix, we can formulate an l1-norm minimization problem whose solution is guaranteed to be one of the sparsest solutions. The weights can be obtained based on a low resolution estimate of the sparse signal, obtained for example via a method that does not encourage sparsity.

    The proposed weighting approach is a good candidate for Electroencephalography (EEG) sparse source localization, where measurements of sensors, placed on a subject’s head are used to localize activations inside the brain. In many cases, the locations of these activations are related to the subject’s reactions or intensions, and estimating them via a non-invasive and inexpensive modality like EEG can find applications in several domains, including cognitive and clinical neuroscience as well as brain-computer interfaces (BCIs). In response to simple tasks, the brain activations are sparse, and thus, their localization based on the EEG recordings can be formulated as a sparse signal recovery problem. In this case, the corresponding basis matrix, referred to as lead field matrix, has high mutual coherence, which means that the least l1-norm solution will not necessarily lead to the brain sources. In spite of the high coherence of the lead field matrix, the proposed weighting approach can still estimate the sources inside the brain. In this talk, this is demonstrated by localizing active sources in the brain corresponding to an auditory task from EEG recordings of human subjects.

    Athina P. Petropulu received her undergraduate degree from the National Technical University of Athens, Greece, and the M.Sc. and Ph.D. degrees from Northeastern University, Boston MA, all in Electrical and Computer Engineering. She is Distinguished Professor at the Electrical and Computer Engineering (ECE) Department at Rutgers, having served as chair of the department during 2010-2016. Before joining Rutgers in 2010, she was faculty at Drexel University. She held Visiting Scholar appointments at SUPELEC, Universite’ Paris Sud, Princeton University and University of Southern California. Dr. Petropulu’s research interests span the area of statistical signal processing, wireless communications, signal processing in networking, physical layer security, and radar signal processing. Her research has been funded by various government industry sponsors including the National Science Foundation (NSF), the Office of Naval research, the US Army, the National Institute of Health, the Whitaker Foundation, Lockheed Martin and Raytheon.

    Talk: how algorithms are shaping our lives, 1pm Thr Oct. 17, ITE 104

    Lockheed Martin Distinguished Speaker Series

    How Algorithms Are Shaping Our Lives

    Dr. Alfred V. Aho

    Lawrence Gussman Professor Emeritus of Computer Science, Columbia University

    1:00-2:00pm Thursday, 17 October 2019, ITE 104, UMBC

    Dr. Aho will explain what algorithms are and how they have evolved over several millennia. Algorithms are now shaping all aspects of our lives from healthcare to jobs to entertainment. Good algorithms can enrich our lives and unfortunately, bad algorithms can wreak havoc. An important societal question concerning algorithms arises. Should we regulate algorithms so they don’t totally distort our lives, and if so, how should we do it? The fundamental nature of algorithms makes this an unusually difficult challenge.

    Alfred Aho joined the Department of Computer Science at Columbia in 1995 and served as Chair of the department from 1995 to 1997, and again in the spring of 2003. He has a B.A.Sc. in Engineering Physics from the University of Toronto and a Ph.D. in Electrical Engineering/Computer Science from Princeton University.

    Professor Aho won the Great Teacher Award for 2003 from the Society of Columbia Graduates. In 2014 he was again recognized for teaching excellence by winning the Distinguished Faculty Teaching Award from the Columbia Engineering Alumni Association. He has received the IEEE John von Neumann Medal and is a Member of the U.S. National Academy of Engineering and of the American Academy of Arts and Sciences. He is a Fellow of the Royal Society of Canada. He shared the 2017 C&C prize with John Hopcroft and Jeff Ullman. He has received honorary doctorates from the Universities of Helsinki, Toronto and Waterloo, and is a Fellow of the American Association for the Advancement of Science, ACM, Bell Labs, and IEEE.

    Professor Aho is a co-inventor of AWK, a widely used pattern-matching language. He also wrote the initial versions of the UNIX string pattern-matching utilities egrep and fgrep; fgrep was the first widely used implementation of what is now called the Aho-Corasick algorithm. His research interests include programming languages, compilers, algorithms, software engineering, and quantum computation.

    Talk: Impacting healthcare through collaborative technology innovations, 1:30pm Mon 7 Oct

    Impacting healthcare through collaborative technology innovations

    Mohanasankar Sivaprakasam
    Indian Institute of Technology, Madra

    1:30-3:00pm Monday, 7 October 2019, ITE325, UMBC

    India’s healthcare scenario presents a set of unique challenges to ensure effective delivery of care to the large population suffering from various communicable and non communicable diseases. The medical devices market in India is largely catered by imports, most of which were not designed to handle the constraints and requirements of country’s care delivery system and market. While this presents a significant challenge to established players, it is an exciting opportunity for innovators and entrepreneurs to create and scale indigenous technology solutions tailored to local needs. However, development of affordable technology solutions which create large impact, and can achieve scale in India requires a deep understanding of the care delivery system and strong partnerships with various stakeholders of the ecosystem.

    Healthcare Technology Innovation Centre of IIT Madras focuses on developing and commercializing affordable healthcare technologies through its team of over 200 engineers, doctors, researchers, students and entrepreneurs working with more than 30 medical institutions, industries, government agencies. The talk will highlight some of its technology successes and the use of AI and machine learning in tackling the healthcare challenges. The potential of these technologies beyond Indian market will be discussed.

    Mohanasankar Sivaprakasam is a faculty of Electrical Engineering at IIT Madras and Director of the Healthcare Technology Innovation Centre (HTIC), a R&D centre of IIT Madras. After his PhD and postdoctoral research in US in implantable medical devices for 8 years, he returned to India with goal of developing affordable medical technologies in the country. Since 2009, he has successfully built an ecosystem of technologists, clinicians and industry, culminating in setting up of Healthcare Technology Innovation Centre (HTIC) in 2011. Over the years, HTIC has grown into a unique and leading med-tech innovation ecosystem in the country bringing together more than 20 medical institutions, industry, government agencies, collaborating with HTIC in developing affordable medical technologies for unmet healthcare needs. He has more than 70 peer reviewed publications in journals and conferences.

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