Nowadays, cloud data outsourcing provides users and companies with powerful capabilities to store and process their data in third-party data centers. However, the privacy of the outsourced data is not guaranteed by the cloud providers. One solution for protecting the user data against security attacks is to encrypt the data before being sent to the cloud servers. Then, the main problem is to evaluate user queries over the encrypted data. In this paper, we address the problem of top-k query processing over encrypted data, and propose an efficient approach called BuckTop. Our approach uses the bucketization technique to manage the encrypted data in the remote server. It includes a top-k query processing algorithm that works on the encrypted data of the buckets, and returns a set that contains the encrypted top-k results. It also has a filtering algorithm that efficiently eliminates the false positives in the server side. We implemented BuckTop, and compared its response time for processing top-k queries over encrypted data with that of the TA algorithm over original (plaintext) data. Our results show excellent performance gains. They show that the response time of BuckTop over encrypted data is close to TA over plaintext data.