Name
Abstract | ||
|---|---|---|
The major contribution of this paper is a hybrid GA-PSO fuzzy user identification system, UGuard, for smart phones. Our system gets 3 phone usage features as input to identify a user or an imposter. We show that these phone usage features for different users are diffused; therefore, we justify the need of a front end fuzzy classifier for them. We further show that the fuzzy classifier must be optimized using a back end online dynamic optimizer. The dynamic optimizer is a hybrid of Particle Swarm Optimizer (PSO) and Genetic Algorithm (GA). We have collected phone usage data of 10 real users having Symbian smart phones for 8 days. We evaluate our UGuard system on this dataset. The results of our experiments show that UGuard provides on the average an error rate of 2% or less. We also compared our system with four classical classifiers -- Na¨1ve Bayes, Back Propagation Neural Networks, J48 Decision Tree, and Fuzzy System -- and three evolutionary schemes -- fuzzy system optimized by ACO, PSO, and GA. To the best of our knowledge, the current work is the first system that has achieved such a small error rate. Moreover, the system is simple and efficient; therefore, it can be deployed on real world smart phones. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1569901.1570117 | GECCO |
Keywords | Field | DocType |
fuzzy system,user identification,phone usage feature,classical classifier,identification system,fuzzy classifier,uguard system,phone usage data,hybrid ga-pso fuzzy system,smart phone,symbian smart phone,hybrid ga-pso fuzzy user,error rate,front end,design,authentication,decision tree,neural network | Front and back ends,Decision tree,Data mining,Neuro-fuzzy,Computer science,Fuzzy logic,Word error rate,C4.5 algorithm,Artificial intelligence,Fuzzy control system,Genetic algorithm,Machine learning | Conference |
Citations | PageRank | References |
7 | 0.69 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muhammad Shahzad | 1 | 728 | 44.77 |
| Saira Zahid | 2 | 54 | 3.45 |
| Muddassar Farooq | 3 | 1221 | 83.47 |