"Safeguarding Research: A Comprehensive Approach to Researcher Security and Threat Mitigation"

2005

Politically or ideologically motivated speech has been the primary focus of much of the recent political, legal, and academic debate on restrictions on speech imposed as a reaction to perceived threats to national and international security. However, restrictions imposed on informing speech as a response to the threat of terrorism raise equally serious concerns. The development of the body of knowledge relies on the free flow of information, including persuasive speech. Since the terrorist attacks of September 11 and the subsequent anthrax attacks in the US, the issue of censorship of scientific information has been subject of debate in both government and scientific circles. This paper analyses the ways restrictions affect the dissemination of knowledge-based information arising from the censoring of scholarly scientific' journals, and at what point a balance can be found between scientific freedom and national security. Is censorship the most appropriate response to the perceived threat of terrorists utilising published scientific information? Can an objective and rational assessment of the threat of terrorism be made in the current political climate? Consideration is given to alternatives to the implementation of a regime of censorship that could be tailored to limit the burden imposed on research in any trade off between scientific progress and national security concerns.

KJCS, 2024

The integration of Artificial Intelligence (AI) into academic research is transforming the management of intellectual property (IP), cybersecurity, and privacy by enhancing existing frameworks and addressing emerging challenges. This paper explores AI's impact on these critical areas through a synergistic model designed to provide comprehensive research protection. The model encompasses three core components: facets of research protection (IP management, cybersecurity, and privacy protection), central AI integration, and related variables such as ethical AI use and regulatory compliance. It also demonstrates that AI can enhance research protection by integrating and optimizing these components, offering a comprehensive solution for managing IP, ensuring cybersecurity, and protecting privacy. The study found out that AI significantly improves IP management by automating plagiarism detection and IP monitoring, resulting in more efficient and accurate identification of violations. In cybersecurity, AI-driven systems offer advanced threat detection and real-time analysis of network traffic, effectively safeguarding sensitive research data from cyber threats. For privacy protection, AI technologies like differential privacy and federated learning enable data analysis while preserving individual privacy, though they also introduce new ethical concerns and privacy risks. The study underscores the synergistic capabilities of AI, which not only bolster research security but also foster global collaboration and ethical practices. To maximize AI's benefits in research protection, the study recommends establishing comprehensive AI governance frameworks to address ethical and regulatory concerns, promoting international collaboration and standardization for consistent practices, and investing in continuous education and training programs for researchers and staff.

2017

Researchers at Berkeley increasingly work with sensitive and restricted-use research data that needs to be handled securely. Most researchers, however, lack experience in managing sensitive data. They do not have training in protecting data, are unable to locate appropriate campus support for doing so, and, as a result, cobble together makeshift solutions which are often inefficient, vulnerable, or unsustainable. This places their research at risk, places the campus at risk, and threatens the opportunities of other campus researchers. Equally as important, it saps time and effort from their research, and limits the capacity for other campus researchers to leverage their investments. In January 2017, the Research Data Management (RDM) program (a partnership between the Library and Research IT in the Office of the CIO) launched a six-month project with partners in the D-Lab and Information Security and Policy (in the Office of the CIO). The goals of this initial project were to assess the campus sensitive-data landscape from the point of view of researchers and research administrators; gauge the demand for services and guidance; benchmark services at peer institutions; and make a set of recommendations for future work. In carrying out this project, the team created several important products: • This whitepaper, which describes the existing campus landscape, suggests policy and practice guidelines, highlights solutions from peer institutions, and identifies some near-term and long-term strategies and solutions for campus. • An ongoing D-Lab Working Group on Securing Research Data, which pulls together the larger community of stakeholders: researchers, service providers, compliance offices, and others. • A Research Data Classification Guideline that interprets campus Data Classification and Protection Profiles for researchers, service providers, and compliance offices. The publication of this guideline also satisfies one of the findings from a 2016 internal audit of research data management on campus. • Box PL2 assessment is in process. In order to both reduce risks for the campus and facilitate research that uses and produces sensitive data, a comprehensive approach must take into account: consulting and community; policy and governance; and services and tools. The recommendations outline below are discussed in more detail in the body of the whitepaper.

MRS Bulletin

F ederally funded scientific advancements have, in many respects, maintained and strengthened US national security. The role of science in general, and materials science in particular, in bolstering national security is broad-spanning from technology developed specifically to aid US military and protect the country; to research-based improvements across health, energy, and environmental stewardship; to the commercialization of a wide variety of science-enabled products and services that drive the US economy. Policymakers in the United States and other countries recognize the dependence of security on science, and members of Congress often cite "national security" as one reason for sponsoring or supporting science-related legislation. The relationship between science and national security is also evident within the executive branch, where many of the departments and agencies that lead scientific research are tasked with enhancing or protecting US security. But recent concerns, raised by the US intelligence community and a growing number of lawmakers across political parties, question the security of the US

Dual Use Research of Concern in the Life Sciences, 2017

In this working paper for the National Academies of Sciences, Engineering, and Medicine, I outline ways we that might augment our biosecurity governance system with a focus on the often overlooked point that all research is dual use, and most of it is not subject to security oversight. I begin by analyzing the assumptions about science, security, and their relationship to the state that underlie our current governance system, and show how those assumptions can be found in the NSABB’s (2007b) Responsible Communication of Life Science Research with Dual Use Potential. I show the limitations of these assumptions, and then propose an alternative set, that leads to radically different principles upon which we might base a system of constructing security concerns in the life sciences. I end by outlining how these principles can be practically implemented in a range of existing and novel governance mechanisms.

Sandia National Laboratories, 2025

Having studied various vulnerable groups and communities in the Baltics and beyond for decades, the report's authors have come to understand that academia is being targeted and misused by foreign autocratic regimes (i.e. Russia, China, etc.) for various malicious purposes: from espionage to influence operations. The study report aims to present the current state of affairs and to guide stakeholders in Latvia and Estonia in emphasizing the importance of a broader security culture in academia and research. It is conceivable that the topic could be actualized for both communities of practitioners – security and academia – by bridging issues of personal safety, reputational risks as well as institutional, national and regional security. As the report deals with complex issues and relations between different cultures, the authors acknowledge the importance of academic freedom and functional autonomy of universities and research institutions. Therefore, this report could serve as a pioneering reference for Latvian and Estonian stakeholders in the field of research security.

Journal of Medical Internet Research, 2022

Background: A Trusted Research Environment (TRE; also known as a Safe Haven) is an environment supported by trained staff and agreed processes (principles and standards), providing access to data for research while protecting patient confidentiality. Accessing sensitive data without compromising the privacy and security of the data is a complex process. Objective: This paper presents the security measures, administrative procedures, and technical approaches adopted by TREs. Methods: We contacted 73 TRE operators, 22 (30%) of whom, in the United Kingdom and internationally, agreed to be interviewed remotely under a nondisclosure agreement and to complete a questionnaire about their TRE. Results: We observed many similar processes and standards that TREs follow to adhere to the Seven Safes principles. The security processes and TRE capabilities for supporting observational studies using classical statistical methods were mature, and the requirements were well understood. However, we identified limitations in the security measures and capabilities of TREs to support "next-generation" requirements such as wide ranges of data types, ability to develop artificial intelligence algorithms and software within the environment, handling of big data, and timely import and export of data. Conclusions: We found a lack of software or other automation tools to support the community and limited knowledge of how to meet the next-generation requirements from the research community. Disclosure control for exporting artificial intelligence algorithms and software was found to be particularly challenging, and there is a clear need for additional controls to support this capability within TREs.

Cadernos Ibero-Americanos de Direito Sanitário, 2021

COVID-19 promises to reshape every aspect of society, not excluding how science is perceived. However, it is not clear whether the authority of science and scientists will be enhanced or diminished, or whether such changes will affect mainly science as an endeavour or scientists as individuals. The aim of this paper is to analyze how a pandemic like COVID-19 could undermined the confidence in science and scientist and, to underline now, more than ever, the importance of trust in science and in scientists. Two main issues will be analyzed: first, we will analyze how putting science and scientists in the spotlight could impact science and scientists and, secondly, we will go through the history of COVID treatment and research to anticipate how misconduct and breaches on responsible conduct in research could undermine trust in science with serious risks and consequences.