The UMBC Cyber Defense Lab presents

Analysis of the Security Design, Engineering, and Implementation of the SecureDNA System

Alan T. Sherman, Enis Golszewski, and Jeremy J. Romanik Romano
UMBC CSEE Department

Joint work with Edward Zieglar, Jonathan D. Fuchs, and William E. Byrd

12:00 noon–1pm Friday, December 12, 2025 via WebEx

We analyze security aspects of the SecureDNA system regarding its system design, engineering, and implementation. This system enables DNA synthesizers to screen order requests against a database of hazards.  By applying novel cryptography involving distributed oblivious pseudorandom functions, the system aims to keep order requests and the database of hazards secret. Discerning the detailed operation of the system in part from source code (Version 1.0.8), our analysis examines key management, certificate infrastructure, authentication, and rate-limiting mechanisms. We also perform the first formal-methods analysis of the mutual authentication, basic request, and exemption-handling protocols.

Without breaking the cryptography, our main finding is that SecureDNA's custom mutual authentication protocol SCEP achieves only one-way authentication: the hazards database and keyservers never learn with whom they communicate. This structural weakness violates the principle of defense in depth and enables an adversary to circumvent rate limits that protect the secrecy of the hazards database, if the synthesizer connects with a malicious or corrupted keyserver or hashed database. We point out an additional structural weakness that also violates the principle of defense in depth: inadequate cryptographic bindings prevent the system from detecting if responses, within a TLS channel, from the hazards database were modified. Consequently, if a synthesizer were to reconnect with the database over the same TLS session, an adversary could replay and swap responses from the database without breaking TLS. Although the SecureDNA implementation does not allow such reconnections, it would be stronger security engineering to avoid the underlying structural weakness. We identify these vulnerabilities and suggest and verify mitigations, including adding strong bindings. Software Version 1.1.0 fixes SCEP with our proposed SCEP+ protocol.

Our work illustrates that a secure system needs more than sound mathematical cryptography; it also requires formal specifications, sound key management, proper binding of protocol message components, and careful attention to engineering and implementation details.

Dr. Alan T. Sherman is a professor of computer science at UMBC in the CSEE Department, associate director of UMBC's Cybersecurity Institute, and director of the Cyber Defense Lab.  His main research interest is high-integrity voting systems. He has carried out research in election systems, protocol analysis, algorithm design, cryptanalysis, theoretical foundations for cryptography, applications of cryptography, cloud forensics, and cybersecurity education. Dr. Sherman is also a private consultant performing security analyses and serving as an expert witness.  Sherman earned the PhD degree in computer science at MIT in 1987, studying under Ronald L. Rivest.  His research accomplishments include contributions to the Scantegrity and VoteXX election systems and development and validation of the Cybersecurity Concept Inventory (CCI) and Cybersecurity Curriculum Assessment (CCA). This work has been presented at USENIX Security 2010 and E-VOTE-ID 2025, and won best research paper at SIGSCE 2023. Sherman received approximately $15 million in funding from NSF, NSA, and IBM. 

Dr. Enis Golaszewski is a teaching assistant professor of computer science at UMBC in the CSEE Department.  He holds weekly workshops in formal-methods analyses of cryptographic protocols using the Cryptographic Protocol Shapes Analyzer (CPSA). His current research projects include analysis of the Coalition for Content Provenance and Authenticity (C2PA) protocol. Golaszewski earned the PhD under Sherman. His dissertation includes the design and development of a tool---ProtoBindGuard---that automatically binds protocol messages to context to prevent protocol-interaction attacks.  Golaszewski is a former SFS scholar at UMBC. https://www.csee.umbc.edu/enis-golaszewski/

Jeremy J. Romanik Romano is an MS student in computer science at UMBC.  His research interests include cybersecurity, software security, and protocol analysis.  His involvement in this project began through being a student in Sherman's INSuRE and cryptology research courses.  Romano is a member of the UMBC Protocol Analysis Lab and system administration and cybersecurity clubs on campus.

UMBC Cyber Defense Lab presents

Usable String Matching by Humans through Overlaid Presentation: Turning Syntactic Tasks into Perceptual Tasks

12:00–1pm, Friday, October 31, 2025 via WebEx

Alan T. Sherman, CSEE Department, UMBC

Joint work with Enka Blanchard, Ted Selker, Ryan Robucci, Levi Gabasova, and Mehdi Bouhamidi

Comparing two strings of characters is a basic activity that occurs in innocuous contexts (checking that an email address was entered correctly) and critical ones (from bank wire transfers to nuclear codes), where it is not always possible to trust a machine to perform the task. Because human performance on this task has received limited attention, we explore the limits and capabilities of humans to compare strings when presented in various formats. I am especially motivated by the important application of checking audit data in end-to-end voting systems including Scantegrity.

We present results from two online experiments with a total of 178 human subjects who compared pairs of text strings to determine for each pair whether the two strings are identical. Each subject was asked to complete 20 trials, which presented strings of 5, 10, or 15 characters or short nonsense sentences. For each pair, the strings were either identical or differed by one character (randomly changed or changed to be difficult to detect).

Our main insight was to check the difference between strings shown side by side, or overlaid in two colors.  Our hypothesis is that, by turning complex syntactic tasks into simple perceptual tasks, such overlay formats can offer advantages in speed and accuracy in comparison with simple side-by-side presentations. Results show that, in comparison with side-by-side comparison, overlay offers a substantially faster method, with substantially improved accuracy for long strings, which has many applications including comparing fingerprints of cryptographic keys and establishing authenticity of authorization tickets.

Our work lays a foundation on which other new perceptual string-comparison strategies can be explored, such as using reflection to compare a string presented on a smartphone with one on a computer display monitor.

Dr. Alan T. Sherman is a professor of computer science at UMBC in the CSEE Department, associate director of UMBC's Cybersecurity Institute, and director of the Cyber Defense Lab.  His main research interest is high-integrity voting systems. He has carried out research in election systems, protocol analysis, algorithm design, cryptanalysis, theoretical foundations for cryptography, applications of cryptography, cloud forensics, and cybersecurity education. Dr. Sherman is also a private consultant performing security analyses and serving as an expert witness. Sherman earned the PhD degree in computer science at MIT in 1987 studying under Ronald L. Rivest.  His research accomplishments include contributions to the Scantegrity and VoteXX election systems and development and validation of the Cybersecurity Concept Inventory (CCI) and Cybersecurity Curriculum Assessment (CCA). This work has been presented at USENIX Security 2010 and E-VOTE-ID 2025, and won best research paper at SIGSCE 2023. Sherman received approximately $15 million in funding from NSF, NSA, and IBM.

Support for this event was provided in part by the NSF under SFS grants DGE-1753681 and 2438185. The UMBC Cyber Defense Lab meets biweekly Fridays 12-1pm.  All meetings are open to the public.

Applications of Quantum Computing and Optimization in Cybersecurity

Mohammadhossein Mohammadisiahroudi

Math/Stat Department, UMBC

The International Cyber Security Center of Excellence (INCS-CoE), of which UMBC is a charter member, will hold an online seminar on Security Challenges for Immersive Technologies from 7:00 to 8:30 am EDT on Thursday, October 9 via Zoom. The seminar will consist of two talks. 

Enhancing Security and Privacy in Augmented Reality - Through the Lens of Eye Tracking, Bo Ji, Virginia Tech

Augmented Reality (AR) devices distinguish themselves from other mobile devices by providing an immersive and interactive experience. The ability of these devices to collect information presents challenges and opportunities to improve existing security and privacy techniques in this domain. In this talk, I will discuss how readily available eye-tracking sensor data can be used to improve existing methods for assuring security and protecting the privacy of those near the device. Our research has presented three new systems, BystandAR, ShouldAR, and GazePair, leveraging the user's eye gaze to improve security and privacy expectations in or with AR. As these devices grow in power and number, such solutions are necessary to prevent perception and privacy failures that hindered earlier devices. This work is presented in the hope that these solutions can improve and expedite the adoption of these powerful and useful AR devices.

Shaping the Metaverse: Policy engagement with immersive technologies in the UK, Jesus Martinez del Rincon, Queen's University Belfast

Queen's University Belfast completed a two-phase Metaverse technologies horizon scanning project in July 2023 and 2025. This talk will cover a summary of the most relevant findings and outcomes. In the first phase, we presented a broad landscaping report of UK interests and activities in related technical areas. Building on areas where the UK might benefit from the emerging Metaverse, the second phase, deepens the analysis in three main areas: a) interoperability standards: where we highlighted current metaverse standards development organisations and identified the strategic aims of such participation; b) privacy, security and regulations: investigating two complementary aspects: (1) the evolving regulatory and legal landscape related to data collection by metaverse service operators; (2) a thread analysis of the metaverse and a technical analysis of the privacy preserving technologies that could enable metaverse data platforms; c) a horizon-scanning of Distributed Ledger Technology (DLT) and their application to the Metaverse.

Join the seminar via Zoom.

The UMBC Cyber Defense Lab presents

Self-Defending Ledgers: Automating Distributed Ledger Security Using Multi-Agent Reinforcement Learning and Game Theory

Md Tariqul Islam 'Pavel'
Assistant Professor of Cybersecurity
UMBC Department of Information Systems

12–1pm EDT, Friday, October 3, 2025 via Webex

Distributed ledger technologies (DLTs) continue to face significant security challenges. While attackers constantly adapt their strategies, governance mechanisms often remain static. Our work addresses this critical gap by introducing a framework for self-defending ledgers, where nodes enforce ledger security through adaptive governance driven by multi-agent reinforcement learning (MARL) grounded in game-theoretic principles. We model DLT consensus as a repeated Bayesian game, in which participants hold probabilistic beliefs about peer behavior, allowing agents to make strategic decisions under partial observability of adversarial actions. Our framework enables nodes to model, detect, and respond to a wide range of malicious behaviors, including bribery, selfish mining, equivocation, Sybil attacks, and collusive voting, by continuously updating Bayesian trust beliefs and governance policies based on network observations. We formally prove that networks with an honest majority reach stable equilibria and provide bounds on adversarial influence. Experiments across five major protocols show that agents effectively identify attacks with high accuracy while substantially reducing adversarial success. This work demonstrates the potential of game-theoretic MARL to provide robust, self-adaptive security in varied DLT environments, paving the way for resilient and autonomous ledger governance.

Md Tariqul Islam 'Pavel' is an assistant professor of cybersecurity in UMBC's Department of Information Systems. His research centers on the security, efficiency, and fault-tolerance of distributed computing systems, with a strong emphasis on blockchain, cloud, and vehicular networks. He develops formal models, algorithms, and protocols that address critical vulnerabilities in decentralized ecosystems, spanning inter-blockchain communication, smart contract migration, and trustworthy governance. His work combines cryptography, game theory, and system design to build scalable, resilient infrastructures. He earned his PhD and MS from the University of Kentucky and BS from the University of Dhaka, Bangladesh.