# Lightweight, Secure, Similar-Document Retrieval over Encrypted Data
## 4 Scheme Overview
### Private Similarity Computation and Search Queries Stage
To address this issue, it is recommended that stored, encrypted documents are processed with additional random data padding so that their actual sizes are not easily detected. To prevent random values from being added to the secure searchable index, the padding process should take place after the safe inverted index has been created. This paper believes that the schemes proposed in related works do not offer sufficient protection to the access pattern since private access processes all documents in the entire document set. This can happen by the server and any unauthorized party. As for _[PERSON]_, she is an authorized user; however, she cannot obtain any information except what she obtains through the search query document because there is no link between the repeated search query documents in our work as it will be explained in the next subsection. This paper's researchers suggest that protecting the search pattern is not sufficient without protecting the access pattern, attributing this to the fact that the results of repeated searches will enable the attacker to link search queries immediately. Therefore, this paper's proposed design protects the access pattern since the remote server stores encrypted identifier IDs for the documents and no unsecured plain text. To further increase security, the proposed design uses a cryptographic method to maintain a secure, searchable inverted index. More clearly, the homomorphic property was used to calculate all similarity scores on the encrypted queries on the server, which were then sent to the user side. The server's computing capabilities mean that this is not considered expensive on the server-side; while the similarity scores sent to the user is a small integers in practice. This limited number of similarity scores is because the documents of highest similarity are always performed, which not only reduces the cost \begin{table}
\begin{tabular}{l c c c c c c c c c c c c c} \hline \hline
**Term** & **Vector** & & & & & & & & & & & & & \\ \hline
500 & 1 & 1 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 1 \\
600 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 \\
710 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 \\ Score & **3** & **1** & **1** & **1** & **0** & **1** & **0** & **1** & **0** & **0** & **1** & **2** \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Score calculation. of communication but also reduces the cost of decryption on the client-side, facilitating efficient implementation. To prevent attempted statistical attacks, it is advised that fake hash values are added to hide the actual number of values stored in the search index. The encrypted query is protected by similar means to those used in the secure searchable index. To measure the amount of information that is disclosed to the remote server from the encrypted documents, the dependency between these encrypted documents and their corresponding plain text is quantified. The rationale behind this method is that low dependency translates into low information leakage. The mutual information (MI) entropy [38; 39] is used to quantify the dependency between two entities. During the experiments conducted for this paper, safe documents yielded a low MI value, equal to 0.0014. ### Search Anonymity

Each search query document has a different encryption key in the proposed model. Thus, two search queries have a different encrypted query even if they are from the same query document, which ensures that different search queries cannot be linked. By disabling linking queries, this scheme can provide search pattern confidentiality and privacy. ## 7 System Evaluation

### Setup of Experiment

In this section, the experimental evaluation of the proposed scheme is presented. One thousand text documents were downloaded from the real dataset _Request For Comments_ (RFC) [40]. During the fingerprint generation, 5-g were used, and the guarantee threshold \(T\) set to 10. The results are the average of 100 runs. The document collection was encrypted by an AES algorithm and the counter mode CTR with 128-bit key.