ANALYSIS BASED ON SVM FOR UNTRUSTED MOBILE CROWDSENSING- A REVIEW

Now-a-days the trend of Mobile crowdsensing, which collects environmental information from mobile phone users, is need which is growing in popularity.

However, collecting sensing data from other users may violate their privacy. Moreover, the data aggregator and/or the participants of crowdsensing may be untrusted entities. Recent studies have proposed randomized response schemes for anonymized data collection. This kind of data collection can
analyze the sensing data of users statistically without precise information about other users’ sensing results.

In this proposed work, we use SVM classifier for classifying the data can be used by companies for marketing surveys or decision making.