PrivHome: Privacy-preserving authenticated communication in smart home environment

A smart home enables users to access devices such as lighting, HVAC, temperature sensors, and surveillance camera. It provides a more convenient and safe living environment for users. Security and privacy, however, is a key concern since information collected from these devices are normally communicated to the user through an open network (i. e. Internet) or system provided by the service provider. The service provider may store and have access to these information. Emerging smart home hubs such as Samsung SmartThings and Google Home are also capable of collecting and storing these information. Leakage and unauthorized access to the information can have serious consequences. For example, the mere timing of switching on/off of an HVAC unit may reveal the presence or absence of the home owner. Similarly, leakage or tampering of critical medical information collected from wearable body sensors can have serious consequences. Encrypting these information will address the issues, but it also reduces utility since queries is no longer straightforward. Therefore, we propose a privacy-preserving scheme, PrivHome. It supports authentication, secure data storage and query for smart home systems. PrivHome provides data confidentiality as well as entity and data authentication to prevent an outsider from learning or modifying the data communicated between the devices, service provider, gateway, and the user. It further provides privacy-preserving queries in such a way that the service provider, and the gateway does not learn content of the data. To the best of our knowledge, privacy-preserving queries for smart home systems has not been considered before. Under our scheme is a new, lightweight entity and key-exchange protocol, and an efficient searchable encryption protocol. Our scheme is practical as both protocols are based solely on symmetric cryptographic techniques. We demonstrate efficiency and effectiveness of our scheme based on experimental and simulation results, as well as comparisons to existing smart home security protocols

Privacy-preserving efficient searchable encryption

Data storage and computation outsourcing to third-party managed data centers, in environments such as Cloud Computing, is increasingly being adopted by individuals, organizations, and governments. However, as cloud-based outsourcing models expand to society-critical data and services, the lack of effective and independent control over security and privacy conditions in such settings presents significant challenges. An interesting solution to these issues is to perform computations on encrypted data, directly in the outsourcing servers. Such an approach benefits from not requiring major data transfers and decryptions, increasing performance and scalability of operations. Searching operations, an important application case when cloud-backed repositories increase in number and size, are good examples where security, efficiency, and precision are relevant requisites. Yet existing proposals for searching encrypted data are still limited from multiple perspectives, including usability, query expressiveness, and client-side performance and scalability. This thesis focuses on the design and evaluation of mechanisms for searching encrypted data with improved efficiency, scalability, and usability. There are two particular concerns addressed in the thesis: on one hand, the thesis aims at supporting multiple media formats, especially text, images, and multimodal data (i.e. data with multiple media formats simultaneously); on the other hand the thesis addresses client-side overhead, and how it can be minimized in order to support client applications executing in both high-performance desktop devices and resource-constrained mobile devices. From the research performed to address these issues, three core contributions were developed and are presented in the thesis: (i) CloudCryptoSearch, a middleware system for storing and searching text documents with privacy guarantees, while supporting multiple modes of deployment (user device, local proxy, or computational cloud) and exploring different tradeoffs between security, usability, and performance; (ii) a novel framework for efficiently searching encrypted images based on IES-CBIR, an Image Encryption Scheme with Content-Based Image Retrieval properties that we also propose and evaluate; (iii) MIE, a Multimodal Indexable Encryption distributed middleware that allows storing, sharing, and searching encrypted multimodal data while minimizing client-side overhead and supporting both desktop and mobile devices

M-SSE: an effective searchable symmetric encryption with enhanced security for mobile devices

Searchable Encryption (SE) allows mobile devices with limited computing and storage resources to outsource data to an untrusted cloud server. Users are able to search and retrieve the outsourced, however, it suffers from information and privacy leakage. The reason is that most of the previous works rely on the single cloud model, which allows that the cloud server get all the search information from users. In this paper, we present a new scheme M-SSE that achieves both forward and backward security based on a multi-cloud technique. The new scheme is secure against both adaptive file injection attack and size pattern attack by utilizing multiple cloud servers. Experiment results show that our scheme is effective compared with the other existing schemes

Encrypted Shared Data Spaces

The deployment of Share Data Spaces in open, possibly hostile, environments arises the need of protecting the confidentiality of the data space content. Existing approaches focus on access control mechanisms that protect the data space from untrusted agents. The basic assumption is that the hosts (and their administrators) where the data space is deployed have to be trusted. Encryption schemes can be used to protect the data space content from malicious hosts. However, these schemes do not allow searching on encrypted data. In this paper we present a novel encryption scheme that allows tuple matching on completely encrypted tuples. Since the data space does not need to decrypt tuples to perform the search, tuple confidentiality can be guaranteed even when the data space is deployed on malicious hosts (or an adversary gains access to the host). Our scheme does not require authorised agents to share keys for inserting and retrieving tuples. Each authorised agent can encrypt, decrypt, and search encrypted tuples without having to know other agents’ keys. This is beneficial inasmuch as it simplifies the task of key management. An implementation of an encrypted data space based on this scheme is described and some preliminary performance results are given