Gait-based Authentication in Smart Aging Care Systems
Bibliographic record
Abstract
A Smart Aging Care System (SACS) allows elderly individuals to age gracefully in their homes through a connected network of heterogeneous sensors, devices, and third-party applications. However, like any Internet of Things (IoT) system, a SACS is susceptible to security threats.Gait-based authentication is a non-invasive and cost-effective biometric modality that enhances user experience (e.g., automatic authentication of a smart pill dispenser) and security. However, gait patterns become more pronounced with age, making it challenging to recognize elderly individuals. Given the limited emphasis on gait identification for the elderly, this work proposes an enhanced gait identification technique.The results show that we could identify 96.20% of gait data pertaining to the correct individual due to properly accounting for intra-subject gait fluctuations. We also propose an intrusion detection system to safeguard gait data against data manipulation attacks, that considers human factors in flagging a behavioral event as anomalous or normal.
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 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 | 0.000 | 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 | 0.000 | 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".