Deer Herd Management Using the Internet: A Comparative Study of California Targeted By Data Mining the Internet

An ongoing project to investigate the use of the internet as an information source for decision support identified the decline of the California deer population as a significant issue. Using Google Alerts, an automated keyword search tool, text and numerical data were collected from a daily internet search and categorized by region and topic to allow for identification of information trends. This simple data mining approach determined that California is one of only four states that do not currently report total, finalized deer harvest (kill) data online and that it is the only state that has reduced the amount of information made available over the internet in recent years. Contradictory information identified by the internet data mining prompted the analysis described in this paper indicating that the graphical information presented on the California Fish and Wildlife website significantly understates the severity of the deer population decline over the past 50 years. This paper presents a survey of how states use the internet in their deer management programs and an estimate of the California deer population over the last 100 years. It demonstrates how any organization can use the internet for data collection and discovery

Web Tracking: Mechanisms, Implications, and Defenses

This articles surveys the existing literature on the methods currently used by web services to track the user online as well as their purposes, implications, and possible user's defenses. A significant majority of reviewed articles and web resources are from years 2012-2014. Privacy seems to be the Achilles' heel of today's web. Web services make continuous efforts to obtain as much information as they can about the things we search, the sites we visit, the people with who we contact, and the products we buy. Tracking is usually performed for commercial purposes. We present 5 main groups of methods used for user tracking, which are based on sessions, client storage, client cache, fingerprinting, or yet other approaches. A special focus is placed on mechanisms that use web caches, operational caches, and fingerprinting, as they are usually very rich in terms of using various creative methodologies. We also show how the users can be identified on the web and associated with their real names, e-mail addresses, phone numbers, or even street addresses. We show why tracking is being used and its possible implications for the users (price discrimination, assessing financial credibility, determining insurance coverage, government surveillance, and identity theft). For each of the tracking methods, we present possible defenses. Apart from describing the methods and tools used for keeping the personal data away from being tracked, we also present several tools that were used for research purposes - their main goal is to discover how and by which entity the users are being tracked on their desktop computers or smartphones, provide this information to the users, and visualize it in an accessible and easy to follow way. Finally, we present the currently proposed future approaches to track the user and show that they can potentially pose significant threats to the users' privacy.Comment: 29 pages, 212 reference