Bibliographic record
Abstract
Carnivore is a surveillance technology, a software program housed in a computer unit, which is installed by properly authorized Federal Bureau of Investigation (FBI) agents on a particular Internet Service Provider’s (ISP) network. The Carnivore software system is used together with a tap on the ISP’s network to “intercept, filter, seize and decipher digital communications on the Internet”. The system is described as a “specialized network analyzer” that works by “sniffing” a network and copying and storing a warranted subset of its traffic. In the FBI’s own words “Carnivore chews on all data on the network, but it only actually eats the information authorized by a court order.” This paper will provide an overview of the FBI’s Carnivore electronic surveillance system. The Carnivore software’s evolution, its “prey” and the system’s relationship with Internet Service Providers will be the focus of the study. (Although the FBI’s Carnivore surveillance system is now officially called DCS1000, as the surveillance system is more commonly referred to as “Carnivore,” that term will be used throughout.) Also addressed in the paper are misconceptions about Carnivore, publicly available sniffer programs, Carnivore’s functionality, methods to counter Carnivore as well as the software’s limitations. In a forthcoming paper, the pertinent American law allowing for wiretapping and electronic surveillance as well as programs and policies outside the United States regarding electronic surveillance are surveyed, and an overview of ECHELON, the global interception and relay system, is provided. These papers aim to provide readers with a better understanding of these surveillance systems: only through an in-depth knowledge can the benefits and dangers they present for public (government), private (individual telecommunications users) and the technical industry (ISPs) be achieved.(author note 2013: It additionally discusses the global surveillance network Echelon, which seems to have morphed recently into the 'PRISM' platform that everyone seems surprised about.)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".