Originally K-anonymity principle was first used in relational databases to tackle the problem of data anonymity. In earlier protection techniques K threshold is used as personalization factor for mobile users. In case, K users are not present around needy client mobile user, query can be delayed and thus it will not help to achieve the Quality of service parameter. Moreover, authors have adopted methodology that if K-1 additional travelling users or queries are not seen by needy users, dummies are populated in the environment to improve the quality of service. Earlier architectures shows poor usage of K-principle, cryptography and cloaking space, which leads to threat during communication, more communication cost, more computation cost. We present here enhanced privacy model in a trustworthy third party privacy context that employs the notion of K-anonymity. In this work, enhanced algorithms are introduced, that guarantees a success of Location Based Services (LBS) query replies coming back to mobile client. Client sends the query to the anonymization server (AS), where this server cloaks the users with other at least K users. Our novelty in the experiment is that we have introduced cryptography from client to AS, modified earlier algorithms for Ring-Band approach, smart location updates and simulated the scaled experiment in populated cities environment. The AS add the dummies but creates ring-band cloaking area and sends it to LBS server. Cryptography adds some time however ring-band approach reduces communication overhead. We have studied the performance with variation of different parameters. The response from LBS comes to AS with Point of Interests (POIs) along the ring-band. After which AS filters for precise POIs and sends reply to mobile client. With ring-band approach we may also skip the AS and have client to LBS approach directly but without identity protection.