相关论文: The SFS Summer Research Study at UMBC: Project-Bas…

In recent years, insider threats and attacks have been increasing in terms of frequency and cost to the corporate business. The utilization of end-to-end encrypted instant messaging applications (WhatsApp, Telegram, VPN) by malicious…

Despite federated learning (FL)'s potential in collaborative learning, its performance has deteriorated due to the data heterogeneity of distributed users. Recently, clustered federated learning (CFL) has emerged to address this challenge…

Insider threat detection presents unique challenges due to the authorized status of malicious actors and the subtlety of anomalous behaviors. Existing machine learning methods often treat user activity as isolated events, thereby failing to…

The advent of Artificial Intelligence (AI), particularly large language models (LLMs), has revolutionized software development by enabling developers to specify tasks in natural language and receive corresponding code, boosting…

According to a recent survey with more than 4000 software developers, less than half of developers can spot security holes. As a result, software products present a low-security quality expressed by vulnerabilities that can be exploited by…

This research full paper investigates the factors influencing computing educators' adoption of project-based learning (PjBL) in software engineering and computing curricula. Recognized as a student-centered pedagogical approach, PjBL has…

Debugging, finding and fixing bugs in code, is a heterogeneous process that shapes novice learners' self-beliefs and motivation in computing. Our Debugging by Design intervention (DbD) provocatively puts students in control over bugs by…

The QUBES platform was conceived as a "science education gateway" and designed to accelerate innovation in undergraduate STEM education. The technical infrastructure was purpose built to provide more equitable access to professional…

This paper aims to bring together the disciplines of social science (SS) and computer science (CS) in the design and implementation of a novel multidisciplinary framework for systematic, transparent, ethically-informed, and bias-aware…

With the improvements in computing technologies, edge devices in the Internet-of-Things have become more complex. The enabler technology for these complex systems are powerful application core processors with operating system support, such…

Federated learning has been widely studied and applied to various scenarios. In mobile computing scenarios, federated learning protects users from exposing their private data, while cooperatively training the global model for a variety of…

Collaborative and distributed learning techniques, such as Federated Learning (FL) and Split Learning (SL), hold significant promise for leveraging sensitive data in privacy-critical domains. However, FL and SL suffer from key limitations…

As the role of information and communication technologies gradually increases in our lives, source code security becomes a significant issue to protect against malicious attempts Furthermore with the advent of data-driven techniques, there…

Curricula recommendation for undergraduate Software Engineering courses underscore the importance of transcending from traditional lecture format to actively involving students in time-limited, iterative development practices. This paper…

Split Learning (SL) offers a framework for collaborative model training that respects data privacy by allowing participants to share the same dataset while maintaining distinct feature sets. However, SL is susceptible to backdoor attacks,…

When security bugs are detected, they should be (a)~discussed privately by security software engineers; and (b)~not mentioned to the general public until security patches are available. Software engineers usually report bugs to bug tracking…

University education play a critical role in shaping intellectual and professional development of the individuals and contribute significantly to the advancement of knowledge and society. Generally, university authority has a direct control…

The idea of applying machine learning(ML) to solve problems in security domains is almost 3 decades old. As information and communications grow more ubiquitous and more data become available, many security risks arise as well as appetite to…

In this paper we describe our experience in designing and evaluating our graduate level computer security seminar course. In particular, our seminar is designed with two goals in mind. First, to instil critical thinking by teaching graduate…

Security-constrained unit commitment (SCUC) is a computationally complex process utilized in power system day-ahead scheduling and market clearing. SCUC is run daily and requires state-of-the-art algorithms to speed up the process. The…