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Recent advancements in artificial intelligence (AI) systems, including large language models like ChatGPT, offer promise and peril for scholarly peer review. On the one hand, AI can enhance efficiency by addressing issues like long publication delays. On the other hand, it brings ethical and social concerns that could compromise the integrity of the peer review process and outcomes. However, human peer review systems are also fraught with related problems, such as biases, abuses, and a lack of transparency, which already diminish credibility. While there is increasing attention to the use of AI in peer review, discussions revolve mainly around plagiarism and authorship in academic journal publishing, ignoring the broader epistemic, social, cultural, and societal epistemic in which peer review is positioned. The legitimacy of AI-driven peer review hinges on the alignment with the scientific ethos, encompassing moral and epistemic norms that define appropriate conduct in the scholarly community. In this regard, there is a "norm-counternorm continuum," where the acceptability of AI in peer review is shaped by institutional logics, ethical practices, and internal regulatory mechanisms. The discussion here emphasizes the need to critically assess the legitimacy of AI-driven peer review, addressing the benefits and downsides relative to the broader epistemic, social, ethical, and regulatory factors that sculpt its implementation and impact., Comment: 21 pages, 1 figure

In light of the rise of malicious attacks on the Internet, and the various networks and applications attached to it, new approaches towards modeling predatory activity in networks could be useful. Past research has simulated networks assuming that all vertices are homogenously susceptible to attack or infection. Often times in real world networks only subsets of vertices are susceptible to attack or infection in a heterogeneous population of vertices. One approach to examining a heterogeneous network susceptible to attack is modeling a network as a predator prey landscape. If each type of vulnerable device is considered a heterogeneous species what level of species diversification is needed to keep a malicious attack from a causing a catastrophic failure to the entire network. This paper explores the predator prey analogy for the Internet and presents findings on how different levels of species diversification effects network resilience. The paper will also discuss the connection between diversification, competition, anti-trust, and national security., Comment: 11 pages, 7 figures, WISICT 2004

The events of 9/11 brought an increased focus on security in the United States and specifically the protection of critical infrastructure. Critical infrastructure encompasses a wide array of critical assets such as the electric power grid, telecommunications, oil and gas pipelines, and transportation networks. This paper will focus on telecommunication networks and the spatial implications of their susceptibility to targeted attack. Utilizing a database of national data carriers, simulations will be run to determine the repercussions of targeted attacks and what the relative merits of different methods of identifying critical nodes are. The analysis will include comparison of current methods employed in vulnerability analysis with spatially constructed methods incorporating regional and distance variables. In addition to the vulnerability analysis a method will be proposed to analyze the fusion of physical and logical networks, and will discuss what new avenues this approach reveals. The results of the analysis will be placed in the context of national and regional security and economic impact., Comment: 48 pages, 9 figures

Cybersecurity is an issue of increasing concern since the events of September 11th. Many questions have been raised concerning the security of the Internet and the rest of the US's information infrastructure. This paper begins to examine the issue by analyzing the Internet's autonomous system (AS) map. Using the AS map, malicious infections are simulated and different defense strategies are considered in a cost benefit framework. The results show that protecting the most connected nodes provides significant gains in security and that after the small minority of most connected nodes are protected there are diminishing returns for further protection. Although if parts of the small minority are not protected, such as non-US networks, protection levels are significantly decreased., Comment: 15 pages, 6 figures