Table 3. Computational efficiency of protection scenarios against a multistage re-identification attack averaged across 100 runs of the experiments.
Scenarios include (1) no protection, (2) demographics only, (3) random opt-in, (4) random masking, (5) opt-in game, (6) masking game, (7) no-attack masking game, and (8) one-stage masking game. BIAP, backward induction algorithm with pruning; GAP, greedy algorithm with pruning.
| Scenario | |||||||||||
| Baseline | Game | ||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ||||
| BIAP | GAP | BIAP | GAP | BIAP | GAP | ||||||
| Running time (seconds) | 7.00 | 6.96 | 7.01 | 9.87 | 6.93 | 7935.28 | 93.63 | 7286.98 | 84.39 | 7.88 | 66.13 |