# Secure Remote Storage of Logs with Search Capabilities
## 2 Secure Remote Storage and Searchable Encryption  
The migration of services from on-premises to cloud-based services is becoming a more frequent one. Such service migration implies that data, even if only a subset, must also move to remote storage. This as lead researchers to propose novel solutions for the secure and remote storage of data [5, 6]. New research issues appear in this new context, examples being: assuring data confidentiality, maintaining data access, enforcing access control, enabling data sharing, and enabling confidential searching of remotely stored data. In Reference [7], the authors propose a novel secure cloud storage that makes use of proxy re-encryption to transform remotely stored ciphertexts so that a delegated user can then access them. Similar work, using proxy re-encryption data sharing by means of ciphertext transformation, is presented in Reference [8], this time focusing on IoT. In Reference [9], the authors try to solve the key escrow problem of using a secure remote storage that requires that trusted central authorities be capable of decrypting ciphertexts when needed. In the same line of research, [PERSON] et al. proposed a novel use of Attribute Based Encryption (ABE) to impose fine grained access control to remotely stored data [10]. Other authors pursued the same goal with similar use of ABE [11, 12]. The previously described secure remote storage systems focus mainly on protecting remotely stored data, imposing access control or enabling the controlled sharing of the data. These do not support secure remote searching over the remotely stored data. Secure remote searching over encrypted data can then be seen as a different, more specific, research line. In a clear text remote search operation, the knowledge of both the keywords and the matching data are known to the server. SE arises as a technique that preserves data confidentially while enabling server-side searching [3]. Over the years, various types of constructions have been proposed. In some of them, researchers have focused on the efficiency of SE techniques, while others focused on the security and privacy [13]. Alongside efficiency and security, the expressiveness of queries is the third main challenge within this field of research. In an SE scheme, efficiency can be typically measured by its computational and communication costs. Although there is no common security model, typically, an SE scheme is considered secure if it can assure that the server learns nothing about the queries or the matching results. The query expressiveness defines the types of supported searches, and typically implies some trade-offs, since it generally is achieved at the expense of some efficiency or security. SE schemes usually operate based on one of two techniques. Some schemes use an encryption algorithm over the clear text data that allows search operations to be performed directly and sequentially on the ciphertext. Thus, the search time is linear to the size of the data stored on the server. Other schemes generate a searchable encrypted index, based on the existing keywords. These indexes can significantly increase the search performance since they allow queries to be performed by the use of trapdoor functions. A trapdoor function consists of a function that is straightforward to compute in one way, but very inefficient to inverse without the knowledge of a secret value. In an SE scheme, these functions are used to generate the search tokens, commonly known as trapdoors, that allow the search to be securely performed. A searchable index can either be a forward index or an inverted index. A forward index builds an index of keywords per document. An inverted index builds an index of documents per keyword [2]. Symmetric Searchable Encryption (SSE) uses symmetric key cryptography and enables only the secret key owner to produce ciphertexts and search queries. Examples of SSE can be found in Reference [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41].