Selected work

Representative Papers

Cultivating Cybersecurity: Designing a Cybersecurity Curriculum for the Food and Agriculture Sector

Mar 20, 2025

To address the prevalent cybersecurity awareness deficits and lack of domain-specific training among agricultural and food industry practitioners, this paper designs and implements a ten-module, systematic curriculum tailored for frontline personnel. Grounded in adult learning theory and an empirically derived threat landscape specific to agriculture, the framework adopts a modular architecture, integrates real-world case studies, and emphasizes hands-on exercises—ensuring low entry barriers and high contextual relevance. It represents the first nationally developed, agriculture-specific cybersecurity education framework. Pilot implementation demonstrates statistically significant improvements in participants’ foundational security awareness, threat identification capabilities, and basic protective competencies. The curriculum effectively bridges a critical gap in practical, profession-aligned cybersecurity education for the agricultural sector, offering a scalable, field-applicable model for capacity building in resource-constrained operational environments.

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Age-Optimal Target Wake Time: Provably Good Wake Schedules for Energy-Constrained Wi-Fi Status Updating

Aug 21, 2026

该研究设计了基于信息新鲜度的TWT唤醒调度方案，通过优化加权平均信息年龄并考虑能量预算约束，提出了一种近似最优算法。

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Malformer: A Multi-Modal Malware Detector Using Transformers

Aug 19, 2026

本文提出Malformer，一种结合文本、图像、图和音频四种模态的Windows恶意软件检测模型，通过多模态Transformer融合提升检测性能，解决了单一模态检测新威胁能力不足的问题。

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Investigating Artificial Intelligence Digital Sovereignty in Mobile Shopping Apps: A Case Study of Nigeria

Aug 06, 2026

This study addresses the growing deployment of AI-driven mobile shopping applications in Nigeria, where widespread adoption coexists with users’ limited awareness of and control over AI systems, thereby undermining their digital sovereignty. For the first time, platform transparency is operationalized as a core indicator of digital sovereignty. Through a multimodal methodology combining Android app forensic analysis, documentation content review, and contextual examination of socioeconomic factors, the research systematically evaluates how AI functionalities are implemented and disclosed. Findings reveal that although AI is pervasively embedded in these applications, transparency remains consistently low, user understanding is constrained, and capacities for meaningful interaction are unevenly distributed. These results underscore the urgent need to strengthen user agency and AI governance frameworks within consumer platforms in developing countries.

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Organizational and Socio-Technical Challenges in UAV Incidents: Evidence from a Practitioner Focus Group

Aug 06, 2026

This study addresses the multifaceted sociotechnical challenges inherent in real-world unmanned aerial vehicle (UAV) incident response, an area lacking empirical grounding in frontline practitioners’ experiences. Adopting a sociotechnical perspective, the research systematically identifies critical non-technical barriers—spanning organizational coordination, legal and policy frameworks, and forensic capabilities—through focus group interviews with UAV and counter-UAV professionals from U.S. industry and government sectors, followed by thematic analysis. The findings reveal five core challenges: insufficient situational awareness, fragmented inter-agency coordination, limited forensic traceability, regulatory gaps, and inadequate training. By providing the first empirical account of these operational realities, this work fills a significant gap in the literature and offers both theoretical insights and practical foundations for developing more effective UAV incident response systems.

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Recent publications

Latest Papers

Age-Optimal Target Wake Time: Provably Good Wake Schedules for Energy-Constrained Wi-Fi Status Updating

Aug 21, 2026

该研究设计了基于信息新鲜度的TWT唤醒调度方案，通过优化加权平均信息年龄并考虑能量预算约束，提出了一种近似最优算法。

0 citationsRead paper

Malformer: A Multi-Modal Malware Detector Using Transformers

Aug 19, 2026

本文提出Malformer，一种结合文本、图像、图和音频四种模态的Windows恶意软件检测模型，通过多模态Transformer融合提升检测性能，解决了单一模态检测新威胁能力不足的问题。

0 citationsRead paper

Investigating Artificial Intelligence Digital Sovereignty in Mobile Shopping Apps: A Case Study of Nigeria

Aug 06, 2026

This study addresses the growing deployment of AI-driven mobile shopping applications in Nigeria, where widespread adoption coexists with users’ limited awareness of and control over AI systems, thereby undermining their digital sovereignty. For the first time, platform transparency is operationalized as a core indicator of digital sovereignty. Through a multimodal methodology combining Android app forensic analysis, documentation content review, and contextual examination of socioeconomic factors, the research systematically evaluates how AI functionalities are implemented and disclosed. Findings reveal that although AI is pervasively embedded in these applications, transparency remains consistently low, user understanding is constrained, and capacities for meaningful interaction are unevenly distributed. These results underscore the urgent need to strengthen user agency and AI governance frameworks within consumer platforms in developing countries.

0 citationsRead paper

Organizational and Socio-Technical Challenges in UAV Incidents: Evidence from a Practitioner Focus Group

Aug 06, 2026

This study addresses the multifaceted sociotechnical challenges inherent in real-world unmanned aerial vehicle (UAV) incident response, an area lacking empirical grounding in frontline practitioners’ experiences. Adopting a sociotechnical perspective, the research systematically identifies critical non-technical barriers—spanning organizational coordination, legal and policy frameworks, and forensic capabilities—through focus group interviews with UAV and counter-UAV professionals from U.S. industry and government sectors, followed by thematic analysis. The findings reveal five core challenges: insufficient situational awareness, fragmented inter-agency coordination, limited forensic traceability, regulatory gaps, and inadequate training. By providing the first empirical account of these operational realities, this work fills a significant gap in the literature and offers both theoretical insights and practical foundations for developing more effective UAV incident response systems.

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EZSMT Version 3, Matured

Jul 14, 2026

This work addresses the challenge of efficiently integrating constraints and logical reasoning in complex combinatorial search by proposing a scalable translation-based Constraint Answer Set Programming (CASP) framework. The approach seamlessly combines Answer Set Programming with Satisfiability Modulo Theories (SMT), leveraging mature SMT solvers—such as CVC5, Yices, and Z3—to enable efficient reasoning over mixed integer and real-valued constraints. The framework introduces a more expressive input language that supports weak constraint optimization and provides a unified architecture for incorporating novel constraint types. Experimental results demonstrate that the system substantially outperforms state-of-the-art solvers, including CLINGCON, CLINGO[DL], and CLINGO[LP], achieving significant improvements in both expressiveness and solving efficiency on standard benchmarks.

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