As we enter the holiday season, this is a reminder that departments may not use state funds for holiday parties, celebrations, or related expenses. This includes food, decorations, entertainment, and any other costs associated with holiday events.

Rosetta Butler, Executive Director of Procurement & Strategic Sourcing

Megan Cherry, Director of Management Advisory Services

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 ET, Wednesday, December 3, 2025
UMBC ITE 459 and online 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.

An Arabber Reunion and celebration supported by Baltimore Traces is in the news.

On Saturday, September 20, 2025 we held a celebration of Baltimore's arabber tradition and an arabber reunion–a day for arabbers past and present to come together and share their stories with the public. The event celebrated the 90th birthday of arabber Donald "China" Waugh and all those who have worked to keep the arabber tradition alive in Baltimore. For over a century, the arabbers of Baltimore have been more than just street vendors; they are a vital, living testament to the city's rich cultural tapestry and a powerful symbol of independent entrepreneurship.

Automate routine tasks and increase efficiency using Microsoft's generative AI tool

If your day is spent navigating the Microsoft 365 suite, Microsoft Copilot is a valuable AI resource built using OpenAI's large language model. Thanks to UMBC's enterprise license, the basic features of Microsoft Copilot Chat are available to all users free of charge, with information you type protected for Level 1 data. Once again, data at level 1 is considered non-public information. 

Common Use: Automating Administrative Tasks Copilot integrates directly into your Microsoft 365 environment, making it a critical tool for boosting productivity and saving time on routine, high-volume tasks.

The Storyline: Productivity Multiplier 

• Email Management: A staff member drowning in emails and reports can instantly turn their day around with Copilot. Instead of reading a lengthy thread, they can ask Copilot in Outlook to: "Summarize this long email thread from the Dean's office and list all the outstanding action items".

• Data Analysis (Staff): In Excel, a staff member can ask Copilot to "Analyze the student performance data in this sheet and create a pivot table showing enrollment trends by department over the last three semesters".

Resources:

• Try Copilot: The free version of Microsoft Copilot Chat is accessible on the web at copilot.microsoft.com on Windows, macOS, and iPadOS, though it has some limits during peak business hours.

• Premium Option: For heavy integration into Word, Excel, Teams, or Outlook, the Microsoft Copilot Pro license is available for purchase (approximately $336 a year).

• Cloud Development: UMBC's cloud computing contract with Microsoft Azure (Open AI) provides advanced options for generative AI development.

• Copilot Success Kit

• UMBC Gen AI FAQ

• UMBC Copilot FAQ