ReadWriteWeb

This is a follow-up to our earlier post on RFID and rustling. This is the first draft of a blueprint for a grassroots method a rancher could use, free of federal involvement, to employ RFID against rustling. This is not the finished product.

Federal livestock-tagging systems have been tried before, most prominently in the wake of the mad cow disease scare. They have all been disastrous. Ranchers disliked the perceived imperiousness of a top-down implementation and resented the expense. Distrustful of federal authority, which has resulted in high-handed dismissal of ranching concerns at times, the centralized nature of a national data bank was also rejected. Organizations that do not exist on the federal level have also tried to encourage a centralized tagging protocol. The same issues inhered.

To most people, cattle rustling is a crime that happens only in old movies. But to cattlemen and ranchers in the United States, it is has always been part of real life. With an enduring economic recession, and cattle going for about $1,000 a head, rustling has experienced a renaissance.

From Arkansas to Missouri to Oklahoma to Oregon, rustling is on the increase and the criminals involved are rarely caught. Brands can be manipulated and back roads are poorly patrolled by law enforcement. One possible deterrent is tagging.

Forget credit cards and social security numbers, a new lot of identity thieves will soon come after your web profiles, or says security firm Aladdin in their Annual Threat Report. According to the firm, if you don't own and control your online persona, it's relatively easy for a criminal to aggregate the known public information about you in order to create a fake one.

For some, the term "dark web" simply means all the online data that search engine spiders can't reach, crawl, or index, but for the University of Arizona's AI Lab, the "Dark Web" refers to a research project where the social phenomena of terrorism is studied via various techniques including social network analysis, content analysis, link analysis, web metrics, video analysis, data and text mining, sentiment and affect analysis, and authorship analysis. Through the use of sophisticated, mathematical tools, the project aims to collect all web content generated by international terrorist groups, including content found on web sites, forums, chat rooms, blogs, social networking sites, videos, virtual worlds, and more.