Anonymous and untraceable communications : location privacy in mobile internetworking
Bibliographic record
Abstract
Data protection and privacy is rapidly becoming one of themost important issues on the Internet today. Larger number ofInternet sites are collecting personal information from usersthrough forms, cookies, online registrations, or surveys thanever before. New commercial services are springing up that canexploit the ability of mobile communication service providersto determine the geographic location of their users. The newwireless technologies offer mobility; at the same time theyofferlocation informationthat is being used to provide newlocation-aware services. This licentiate thesis concerns our experience building anew innovative network environment at the IT-University (RoyalInstitute of Technology). It explains how we present the newsecurity challenges that a wireless network raises togetherwith how we confronte and investigate a new form of problemthis type of network presents, namely location privacy. The focus of this work has been on trying to provideunlinkability between the location of wireless users and theiractivities in the Internet. The thesis includes a protocolextension to a pseudonymous IP network architecture developedby the Canadian company Zero Knowledge Systems Inc. called theFreedom System. The proposed extension to Freedom Systempermits a mobile client to seamlessly roam among IP subnetworksand media types whilst being untraceable. By untraceable in thecontext of this thesis we mean the capability of a mobile nodeto concealthe relation between location and personal identifiableinformationfrom third parties whilst the user is on themove. This thesis is composed of four published papers wherethe main results are presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".