Internet of Things (IoT) is expanding across a number of industries, including the medical field. Such a scenario might easily reveal sensitive information, such as private digital medical records, presenting potential security issues. Symmetric Searchable Encryption has been widely considered due to its promise to allow well-organized search on encoded data. Nevertheless, most SSE techniques ignore malicious cloud servers and need the data owner to provide the entire key in order to query users. In this paper, a novel technique has been proposed to solve these restrictions. Normalization, tokenization, word removal and stemming are used for preprocessing the data from the data owner and preprocessed data is divided into k-number of clusters using k-means clustering algorithm. The clustered data is encrypted using a Damgard-Jurik encryption algorithm. The efficiency of the proposed P2ADS technique has been determined using assessment metrics such as accuracy, encryption time, and decryption time. The proposed method's decryption time is 7.56%, 5.01%, 4.41%, and 3.50% quicker than that of the existing VPSL, ABKS, PERT, and PP-DSA methods respectively.