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On the Effectiveness of Large Language Models for Classifying Malicious URLs
No full textIn this paper, we consider the effectiveness of specific Large Language Models (LLMs) for detecting malicious URL in a phishing URL dataset. Specifically, we investigate whether multiple classification attempts made with an LLM can improve the classification accuracy. This research aims to analyze the inconsistency in LLMs when used to classify malicious and non-malicious URLs. We find that the accuracy of most LLMs is little better than a random classifier, and multiple classification attempts only provide a marginal improvement
Onkvisit, Sak
No full textUniversity of Kentucky, Business Administration, 1976 DBA
University of Arkansas, 1972 MBAhttps://scholarworks.sjsu.edu/erfa_bios/1356/thumbnail.jp
Spartan Daily, April 8, 2025
Get PDFVolume 164, Issue 29https://scholarworks.sjsu.edu/spartan_daily_2025/1028/thumbnail.jp
Minimizing spread of misinformation in social networks: a network topology based approach
Get PDFIn the emerging landscape of online social networks (OSNs), the rapid dissemination of misinformation poses a significant challenge to the integrity of information shared among users. Hence, misinformation containment problem in OSNs has drawn significant attention nowadays. In this paper, given a fixed budget, the problem is formulated as minimizing misinformation spread (MMS) problem, which is shown to be an NP-hard problem. With the objective to combat the misinformation in real time, this paper explores a new direction to leverage the network topology to minimize the search space drastically. Based on the community structure of the OSN along with the trust relationship among nodes, a novel linear-time seed node selection algorithm is proposed here that is independent of the positions of the misinformed nodes. Once the set of seed nodes is selected, it can combat any situation of misinformation spread in the OSN, provided the community structure of the network does not change significantly. To the best of our knowledge, this work is the first where trust relationship among users is considered along with the community structure of the network, to control the spread of misinformation in real time. To analyze the diffusion dynamics pertaining to both true information and misinformation, competitive linear threshold model (LTM) with provision for belief switching is followed to provide a more realistic and comprehensive understanding of information diffusion dynamics. Extensive experimental studies on large scale OSNs demonstrate that in comparison to earlier works, the proposed technique obtains 47–74% improvements in performance parameters. Not only that, its parallel implementations also achieve around 51× speedup compared to the earlier algorithms, revealing that the proposed technique is scalable on large scale OSNs for real-time restraint of misinformation
What Tackles Vehicle GHG Emissions in California: Regional Plan Adoption or Local Leadership?
Get PDFThe California Senate Bill No. 375 (SB 375) serves as a model policy for reducing greenhouse gas (GHG) emissions by integrating transportation and land-use planning through regional and local policies. The 18 California Metropolitan Planning Organizations (MPOs) are tasked with developing Sustainable Communities Strategies (SCS) to guide emissions reductions, often implemented locally through Climate Action Plans (CAPs). However, CAPs are voluntary, and misalignment with SCS objectives can undermine their effectiveness. This study examined 25 California cities using content analysis and regression modeling to explore whether independent local actions, supported by community engagement, activist strategies, and leadership, are more effective than regional alignment in reducing vehicle trips. The findings show that while aligning regional and local plans is important for equity and resource distribution, local activist leadership in addressing specific issues, such as parking and public education, achieves significant reductions in vehicle trips. These efforts lead to a 20% increase in non-auto commuting, even without a mandated regional alignment. Additionally, regional strategies such as climate-friendly infrastructure and mass transit are crucial for addressing resource disparities between lower-income communities with limited volunteer capacity and wealthier communities that benefit from robust regional plans and strong local leadership. This study provides critical evidence of the effectiveness of regional and local approaches, emphasizing the need for a balanced, multi-scalar framework to enhance transportation emission reductions and climate resilience
Self-Directed Learning in the Elementary Library
Get PDFThis article examines the implementation of the My Time self-directed learning framework in elementary school libraries, focusing on its impact on student autonomy, critical thinking, and engagement. My Time integrates structured choices with flexible guidance, enabling students to take ownership of their learning. The author reflects on practical experiences and connects them to theoretical foundations, including Glasser’s Choice Theory, Knowles\u27 self-directed learning model, and constructivist principles. Key findings demonstrate that My Time significantly improves student engagement, autonomy, and behavior through activities such as makerspaces, inquiry-based projects, and reflective goal-setting. The article emphasizes the program\u27s potential to transform school libraries into dynamic hubs for 21st-century learning, fostering lifelong learning and collaboration across educational settings
Characteristics of World Class School Librarians
Get PDFOver 30 school librarians across the U.S. and Canada and who had been nominated by their peers for their excellence were interviewed as a part of the AliveLibrary Project at San Jose State University. The major question was “What are the major characteristics of world class school librarians.” Each was read and rated by three researchers, and in several rounds resulted in eight major characteristics that seem to undergird high impact on teaching and learning across a wide spectrum of locations, affluence, diversity, and communities
Spartan Daily, January 23, 2025
Get PDFVolume 164, Issue 1https://scholarworks.sjsu.edu/spartan_daily_2025/1000/thumbnail.jp
Understanding Mobility-Related Challenges for AAPI Older Adults: A Preliminary Study in Southern California
Get PDFThe Federal Highway Administration (FHWA) and state Departments of Transportation (DOTs) Nationwide, the Asian American Pacific Islander (AAPI) community is projected to constitute 11 percent of people 65 years and older in the United States by 2050 (He et al., 2005). The challenges limiting the transportation and mobility of AAPI older adults include, but are not limited to, language barriers, cultural barriers, anti-Asian hate, accessibility to public transit, traffic safety and public security concerns, and changes to mobility due to the COVID-19 pandemic. This project conducted an extensive literature review and a preliminary multi-language survey in Southern California to better understand mobility-related challenges for Asian American and Pacific Islander older adults. The results of this project can provide government agencies and organizations with recommendations for policy and program changes to benefit AAPI older adults and the broader communities
On Modeling Agent Behavior Change Through Multi-Typed Information Diffusion in Online Social Networks
Get PDFThe rapid spread of information on online social networks (OSNs) has had both beneficial and detrimental societal impacts. Notably, the propagation of misinformation during events such as the COVID-19 pandemic has driven collective behavioral responses, sometimes exacerbating crises such as panic buying and bank runs. The toilet paper shortage in Japan in 2020 caused by people\u27s selfish behavior owing to the diffusion of information to correct misinformation, which is considered a general phenomenon based on three sociological characteristics: a collective action problem, a self-fulfilling prophecy, and pluralistic ignorance. Understanding what kind and how information can inhibit selfish behavior to mitigate the problem under the phenomenon is critical for developing strategies to mitigate it. However, existing models addressing misinformation diffusion often lack the capacity to represent the complex behavioral phenomena driven by multiple information types and do not fully capture the subjective decision-making processes of individuals influenced by information. Therefore, this study introduces a computational model that combines subjective logic to represent opinion changes of individuals using multi-typed information and cumulative prospect theory to simulate individuals\u27 decision-making. This model aims to depict the effectiveness of information in inhibiting selfish behavior (behavior-guiding information) in the phenomenon. The simulation results demonstrate that behavior-guiding information can either inhibit or unintentionally promote selfish behavior, depending on network parameters and information characteristics. These findings suggest that the strategies of behavior-guiding information for this phenomenon should be carefully designed, and that our model could help in these design