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George Grispos

Publications and source records attributed to George Grispos.

At least 19 recordsLinked to original sources

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

The use of e-commerce mobile applications is expanding in Nigeria, creating both opportunities and risks, including fraud and reduced user control over digital technologies, raising concerns about digital sovereignty. This research examines how Artificial Intelligence (AI) in Nigerian mobile applications affects digital sovereignty, examined through platform transparency as a key indicator of user awareness and control. Using an interpretive approach, the research combines the forensic analysis of selected Android applications with contextual document analysis to identify AI features and evaluate disclosure practices. The findings show that AI is widely implemented in the applications, yet transparency about its use remains limited. A socio-economic analysis of Nigeria further shows an increasing dependence on consumer digital platforms, moderate AI awareness, and uneven patterns of interaction. By providing empirical evidence on AI transparency and platform practices, this study advances understanding of individual digital sovereignty and highlights challenges for protecting user control in AI-driven digital environments.

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

Unmanned Aerial Vehicles are now widely used across business, government, and recreational contexts, creating new challenges for incident response and digital forensics. While previous forensics research has largely focused on the extraction of technical data from UAV systems, minimal empirical work has examined how UAV incidents are handled in real-world settings or what challenges incident handlers face during this response. To address this gap, this paper reports findings from an in-person focus group with UAV and counter-UAV practitioners from industry and government organizations in the United States. Using qualitative analysis, several key challenges are identified, including situational awareness and airspace visibility, fragmented reporting and interorganizational coordination, forensic and attribution limitations, legal and policy gaps, and shortfalls in training and operational capacity. The research extends socio-technical incident response research to the UAV domain by providing practitioner-driven insight into UAV incident response and highlighting opportunities to strengthen incident response in this domain.

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Strengthening Cybersecurity Resilience in Agriculture Through Educational Interventions: A Case Study of the Ponca Tribe of Nebraska

The increasing digitization of agricultural operations has introduced new cybersecurity challenges for the farming community. This paper introduces an educational intervention called Cybersecurity Improvement Initiative for Agriculture (CIIA), which aims to strengthen cybersecurity awareness and resilience among farmers and food producers. Using a case study that focuses on farmers from the Ponca Tribe of Nebraska, the research evaluates pre- and post- intervention survey data to assess participants' cybersecurity knowledge and awareness before and after exposure to the CIIA. The findings reveal a substantial baseline deficiency in cybersecurity education among participants, however, post-intervention assessments demonstrate improvements in the comprehension of cybersecurity concepts, such as password hygiene, multi-factor authentication, and the necessity of routine data backups. These initial findings highlight the need for a continued and sustained, community-specific cybersecurity education effort to help mitigate emerging cyber threats in the agricultural sector.

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Secure Edge Computing Reference Architecture for Data-driven Structural Health Monitoring: Lessons Learned from Implementation and Benchmarking

Structural Health Monitoring (SHM) plays a crucial role in maintaining aging and critical infrastructure, supporting applications such as smart cities and digital twinning. These applications demand machine learning models capable of processing large volumes of real-time sensor data at the network edge. However, existing approaches often neglect the challenges of deploying machine learning models at the edge or are constrained by vendor-specific platforms. This paper introduces a scalable and secure edge-computing reference architecture tailored for data-driven SHM. We share practical insights from deploying this architecture at the Memorial Bridge in New Hampshire, US, referred to as the Living Bridge project. Our solution integrates a commercial data acquisition system with off-the-shelf hardware running an open-source edge-computing platform, remotely managed and scaled through cloud services. To support the development of data-driven SHM systems, we propose a resource consumption benchmarking framework called edgeOps to evaluate the performance of machine learning models on edge devices. We study this framework by collecting resource utilization data for machine learning models typically used in SHM applications on two different edge computing hardware platforms. edgeOps was specifically studied on off-the-shelf Linux and ARM-based edge devices. Our findings demonstrate the impact of platform and model selection on system performance, providing actionable guidance for edge-based SHM system design.

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Investigating The Implications of Cyberattacks Against Precision Agricultural Equipment

As various technologies are integrated and implemented into the food and agricultural industry, it is increasingly important for stakeholders throughout the sector to identify and reduce cybersecurity vulnerabilities and risks associated with these technologies. However, numerous industry and government reports suggest that many farmers and agricultural equipment manufacturers do not fully understand the cyber threats posed by modern agricultural technologies, including CAN bus-driven farming equipment. This paper addresses this knowledge gap by attempting to quantify the cybersecurity risks associated with cyberattacks on farming equipment that utilize CAN bus technology. The contribution of this paper is twofold. First, it presents a hypothetical case study, using real-world data, to illustrate the specific and wider impacts of a cyberattack on a CAN bus-driven fertilizer applicator employed in row-crop farming. Second, it establishes a foundation for future research on quantifying cybersecurity risks related to agricultural machinery.

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

As technology increasingly integrates into farm settings, the food and agriculture sector has become vulnerable to cyberattacks. However, previous research has indicated that many farmers and food producers lack the cybersecurity education they require to identify and mitigate the growing number of threats and risks impacting the industry. This paper presents an ongoing research effort describing a cybersecurity initiative to educate various populations in the farming and agriculture community. The initiative proposes the development and delivery of a ten-module cybersecurity course, to create a more secure workforce, focusing on individuals who, in the past, have received minimal exposure to cybersecurity education initiatives.

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Cyber Pirates Ahoy! An Analysis of Cybersecurity Challenges in the Shipping Industry

Maritime shipping has become a trillion-dollar industry that now impacts the economy of virtually every country around the world. It is therefore no surprise that countries and companies have spent billions of dollars to modernize shipping vessels and ports with various technologies. However, the implementation of these technologies has also caught the attention of cybercriminals. For example, a cyberattack on one shipping company resulted in nearly $300 millions in financial losses. Hence, this paper describes cybersecurity vulnerabilities present in the international shipping business. The contribution of this paper is the identification and dissection of cyber vulnerabilities specific to the shipping industry, along with how and why these potential vulnerabilities exist.

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Towards a Cybersecurity Testbed for Agricultural Vehicles and Environments

In today's modern farm, an increasing number of agricultural systems and vehicles are connected to the Internet. While the benefits of networked agricultural machinery are attractive, this technological shift is also creating an environment that is conducive to cyberattacks. While previous research has focused on general cybersecurity concerns in the farming and agricultural industries, minimal research has focused on techniques for identifying security vulnerabilities within actual agricultural systems that could be exploited by cybercriminals. Hence, this paper presents STAVE - a Security Testbed for Agricultural Vehicles and Environments - as a potential solution to assist with the identification of cybersecurity vulnerabilities within commercially available off-the-shelf components used in certain agricultural systems. This paper reports ongoing research efforts to develop and refine the STAVE testbed, along with describing initial cybersecurity experimentation which aims to identify security vulnerabilities within wireless and Controller Area Network (CAN) Bus agricultural vehicle components.

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A Digital Forensics Investigation of a Smart Scale IoT Ecosystem

The introduction of Internet of Things (IoT) ecosystems into personal homes and businesses prompts the idea that such ecosystems contain residual data, which can be used as digital evidence in court proceedings. However, the forensic examination of IoT ecosystems introduces a number of investigative problems for the digital forensics community. One of these problems is the limited availability of practical processes and techniques to guide the preservation and analysis of residual data from these ecosystems. Focusing on a detailed case study of the iHealth Smart Scale ecosystem, we present an empirical demonstration of practical techniques to recover residual data from different evidence sources within a smart scale ecosystem. We also document the artifacts that can be recovered from a smart scale ecosystem, which could inform a digital (forensic) investigation. The findings in this research provides a foundation for future studies regarding the development of processes and techniques suitable for extracting and examining residual data from IoT ecosystems.

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Investigating Protected Health Information Leakage from Android Medical Applications

As smartphones and smartphone applications are widely used in a healthcare context (e.g., remote healthcare), these devices and applications may need to comply with the Health Insurance Portability and Accountability Act (HIPAA) of 1996. In other words, adequate safeguards to protect the user's sensitive information (e.g., personally identifiable information and/or medical history) are required to be enforced on such devices and applications. In this study, we forensically focus on the potential of recovering residual data from Android medical applications, with the objective of providing an initial risk assessment of such applications. Our findings (e.g., documentation of the artifacts) also contribute to a better understanding of the types and location of evidential artifacts that can, potentially, be recovered from these applications in a digital forensic investigation.

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How Good is Your Data? Investigating the Quality of Data Generated During Security Incident Response Investigations

An increasing number of cybersecurity incidents prompts organizations to explore alternative security solutions, such as threat intelligence programs. For such programs to succeed, data needs to be collected, validated, and recorded in relevant datastores. One potential source supplying these datastores is an organization's security incident response team. However, researchers have argued that these teams focus more on eradication and recovery and less on providing feedback to enhance organizational security. This prompts the idea that data collected during security incident investigations may be of insufficient quality for threat intelligence analysis. While previous discussions focus on data quality issues from threat intelligence sharing perspectives, minimal research examines the data generated during incident response investigations. This paper presents the results of a case study identifying data quality challenges in a Fortune 500 organization's incident response team. Furthermore, the paper provides the foundation for future research regarding data quality concerns in security incident response.

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A Bleeding Digital Heart: Identifying Residual Data Generation from Smartphone Applications Interacting with Medical Devices

The integration of medical devices in everyday life prompts the idea that these devices will increasingly have evidential value in civil and criminal proceedings. However, the investigation of these devices presents new challenges for the digital forensics community. Previous research has shown that mobile devices provide investigators with a wealth of information. Hence, mobile devices that are used within medical environments potentially provide an avenue for investigating and analyzing digital evidence from such devices. The research contribution of this paper is twofold. First, it provides an empirical analysis of the viability of using information from smartphone applications developed to complement a medical device, as digital evidence. Second, it includes documentation on the artifacts that are potentially useful in a digital forensics investigation of smartphone applications that interact with medical devices.

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Digital Blues: An Investigation into the Use of Bluetooth Protocols

The proliferation of Bluetooth mobile device communications into all aspects of modern society raises security questions by both academicians and practitioners. This environment prompted an investigation into the real-world use of Bluetooth protocols along with an analysis of documented security attacks. The experiment discussed in this paper collected data for one week in a local coffee shop. The data collection took about an hour each day and identified 478 distinct devices. The contribution of this research is two-fold. First, it provides insight into real-world Bluetooth protocols that are being utilized by the general public. Second, it provides foundational research that is necessary for future Bluetooth penetration testing research.

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Medical Cyber-Physical Systems Development: A Forensics-Driven Approach

The synthesis of technology and the medical industry has partly contributed to the increasing interest in Medical Cyber-Physical Systems (MCPS). While these systems provide benefits to patients and professionals, they also introduce new attack vectors for malicious actors (e.g. financially-and/or criminally-motivated actors). A successful breach involving a MCPS can impact patient data and system availability. The complexity and operating requirements of a MCPS complicates digital investigations. Coupling this information with the potentially vast amounts of information that a MCPS produces and/or has access to is generating discussions on, not only, how to compromise these systems but, more importantly, how to investigate these systems. The paper proposes the integration of forensics principles and concepts into the design and development of a MCPS to strengthen an organization's investigative posture. The framework sets the foundation for future research in the refinement of specific solutions for MCPS investigations.

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Security Incident Recognition and Reporting (SIRR): An Industrial Perspective

Reports and press releases highlight that security incidents continue to plague organizations. While researchers and practitioners' alike endeavor to identify and implement realistic security solutions to prevent incidents from occurring, the ability to initially identify a security incident is paramount when researching a security incident lifecycle. Hence, this research investigates the ability of employees in a Global Fortune 500 financial organization, through internal electronic surveys, to recognize and report security incidents to pursue a more holistic security posture. The research contribution is an initial insight into security incident perceptions by employees in the financial sector as well as serving as an initial guide for future security incident recognition and reporting initiatives.

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Are You Ready? Towards the Engineering of Forensic-Ready Systems

As security incidents continue to impact organisations, there is a growing demand for systems to be 'forensic ready'- to maximise the potential use of evidence whilst minimising the costs of an investigation. Researchers have supported organisational forensic readiness efforts by proposing the use of policies and processes, aligning systems with forensics objectives and training employees. However, recent work has also proposed an alternative strategy for implementing forensic readiness called forensic-by-design. This is an approach that involves integrating requirements for forensics into relevant phases of the systems development lifecycle with the aim of engineering forensic-ready systems. While this alternative forensic readiness strategy has been discussed in the literature, no previous research has examined the extent to which organisations actually use this approach for implementing forensic readiness. Hence, we investigate the extent to which organisations consider requirements for forensics during systems development. We first assessed existing research to identify the various perspectives of implementing forensic readiness, and then undertook an online survey to investigate the consideration of requirements for forensics during systems development lifecycles. Our findings provide an initial assessment of the extent to which requirements for forensics are considered within organisations. We then use our findings, coupled with the literature, to identify a number of research challenges regarding the engineering of forensic-ready systems.

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Towards Adaptive Compliance

Mission critical software is often required to comply with multiple regulations, standards or policies. Recent paradigms, such as cloud computing, also require software to operate in heterogeneous, highly distributed, and changing environments. In these environments, compliance requirements can vary at runtime and traditional compliance management techniques, which are normally applied at design time, may no longer be sufficient. In this paper, we motivate the need for adaptive compliance by illustrating possible compliance concerns determined by runtime variability. We further motivate our work by means of a cloud computing scenario, and present two main contributions. First, we propose and justify a process to support adaptive compliance that ex- tends the traditional compliance management lifecycle with the activities of the Monitor-Analyse-Plan-Execute (MAPE) loop, and enacts adaptation through re-configuration. Second, we explore the literature on software compliance and classify existing work in terms of the activities and concerns of adaptive compliance. In this way, we determine how the literature can support our proposal and what are the open research challenges that need to be addressed in order to fully support adaptive compliance.

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In The Wild Residual Data Research and Privacy

As the world becomes increasingly dependent on technology, researchers in both industry and academia endeavor to understand how technology is used, the impact it has on everyday life, the artifact life-cycle and overall integrations of digital information. In doing so, researchers are increasingly gathering 'real-world' or 'in-the-wild' residual data, obtained from a variety of sources, without the explicit consent of the original owners. This data gathering raises significant concerns regarding privacy, ethics and legislation, as well as practical considerations concerning investigator training, data storage, overall security and data disposal. This research surveys recent studies of residual data gathered in-the-wild and analyzes the challenges that were confronted. Amalgamating these insights, the research presents a compendium of practices for addressing the issues that can arise in-the-wild when conducting residual data research. The practices identified in this research can be used to critique current projects and assess the feasibility of proposed future research.

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