Spyware: Background and Policy Issues for Congress
Bibliographic record
Abstract
The term "spyware" is not well defined.Generally it is used to refer to any software that is downloaded onto a person's computer without their knowledge.Spyware may collect information about a computer user's activities and transmit that information to someone else.It may change computer settings, or cause "pop-up" advertisements to appear (in that context, it is called "adware").Spyware may redirect a Web browser to a site different from what the user intended to visit, or change the user's home page.A type of spyware called "keylogging" software records individual keystrokes, even if the author modifies or deletes what was written, or if the characters do not appear on the monitor.Thus, passwords, credit card numbers, and other personally identifiable information may be captured and relayed to unauthorized recipients.Some of these software programs have legitimate applications the computer user wants.They obtain the moniker "spyware" when they are installed surreptitiously, or perform additional functions of which the user is unaware.Users typically do not realize that spyware is on their computer.They may have unknowingly downloaded it from the Internet by clicking within a website, or it might have been included in an attachment to an electronic mail message or embedded in other software.According to a survey and tests conducted by America Online and the National Cyber Security Alliance, 80% of computers in the test group were infected by spyware or adware, and 89% of the users of those computers were unaware of it.The Federal Trade Commission (FTC) issued a consumer alert on spyware in October 2004.It provided a list of warning signs that might indicate that a computer is infected with spyware, and advice on what to do if it is.Utah and California have passed spyware laws, but there is no specific federal law regarding spyware.In the 108 th Congress, the House passed two bills (H.R. 2929 and H.R. 4661) and the Senate Commerce Committee reported S. 2145.There was no further action.Debate is likely to resume in the 109 th Congress.A central point of the debate is whether new laws are needed, or if industry selfregulation, coupled with enforcement actions under existing laws such as the Federal Trade Commission Act, is sufficient.The lack of a precise definition for spyware is cited as a fundamental problem in attempting to write new laws.FTC representatives and others caution that new legislation could have unintended consequences, barring current or future technologies that might, in fact, have beneficial uses.They further insist that, if legal action is necessary, existing laws provide sufficient authority.Consumer concern about control of their computers being taken over by spyware leads others to conclude that legislative action is needed.This report will be updated as warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.031 | 0.023 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.061 | 0.027 |
| Insufficient payload (model declined to judge) | 0.081 | 0.027 |
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 source (direct Gemma or distilled Codex), 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".