PrivGenDB: Efficient and privacy-preserving query executions over encrypted SNP-Phenotype database

Searchable symmetric encryption (SSE) has been used to protect the confidentiality of genomic data while providing substring search and range queries on a sequence of genomic data, but it has not been studied for protecting single nucleotide polymorphism (SNP)-phenotype data. In this article, we propose a novel model, PrivGenDB, for securely storing and efficiently conducting different queries on genomic data outsourced to an honest-but-curious cloud server. To instantiate PrivGenDB, we use SSE to ensure confidentiality while conducting different types of queries on encrypted genomic data, phenotype and other information of individuals to help analysts/clinicians in their analysis/care. To the best of our knowledge, PrivGenDB construction is the first SSE-based approach ensuring the confidentiality of shared SNP-phenotype data through encryption while making the computation/query process efficient and scalable for biomedical research and care. Furthermore, it supports a variety of query types on genomic data, including count queries, Boolean queries, and k'-out-of-k match queries. Finally, the PrivGenDB model handles the dataset containing both genotype and phenotype, and it also supports storing and managing other metadata like gender and ethnicity privately. Computer evaluations on a dataset with 5,000 records and 1,000 SNPs demonstrate that a count/Boolean query and a k'-out-of-k match query over 40 SNPs take approximately 4.3s and 86.4{\mu}s, respectively, that outperforms the existing schemes

Searchable Encryption for Conjunctive Queries with Extended Forward and Backward Privacy

Recent developments in the field of Dynamic Searchable Symmetric Encryption (DSSE) with forward and backward privacy have attracted much attention from both research and industrial communities. However, most forward and backward private DSSE schemes support single keyword queries only, which impedes its prevalence in practice. Until recently, Patranabis et al. (NDSS 2021) introduced a forward and backward private DSSE for conjunctive queries (named ODXT) based on the Oblivious Cross-Tags (OXT) framework. Unfortunately, its security is not comprehensive for conjunctive queries, and it deploys “lazy deletion”, which incurs more communication cost. Besides, it cannot delete a file in certain circumstances. To address these problems, we introduce two forward and backward private DSSE schemes with conjunctive queries (named SDSSE-CQ and SDSSE-CQ-S). To analysis their security, we present two new levels of backward privacy (named Type-O and Type-O$^-$, where Type-O$^-$ is more secure than Type-O), which describe the leakages of conjunctive queries with OXT framework more accurately. Finally, the security and experimental evaluation demonstrate that our proposed schemes achieve better security with comparable computation and communication increase in comparison with ODXT

A Privacy-Preserving, Accountable and Spam-Resilient Geo-Marketplace

Mobile devices with rich features can record videos, traffic parameters or air quality readings along user trajectories. Although such data may be valuable, users are seldom rewarded for collecting them. Emerging digital marketplaces allow owners to advertise their data to interested buyers. We focus on geo-marketplaces, where buyers search data based on geo-tags. Such marketplaces present significant challenges. First, if owners upload data with revealed geo-tags, they expose themselves to serious privacy risks. Second, owners must be accountable for advertised data, and must not be allowed to subsequently alter geo-tags. Third, such a system may be vulnerable to intensive spam activities, where dishonest owners flood the system with fake advertisements. We propose a geo-marketplace that addresses all these concerns. We employ searchable encryption, digital commitments, and blockchain to protect the location privacy of owners while at the same time incorporating accountability and spam-resilience mechanisms. We implement a prototype with two alternative designs that obtain distinct trade-offs between trust assumptions and performance. Our experiments on real location data show that one can achieve the above design goals with practical performance and reasonable financial overhead.Comment: SIGSPATIAL'19, 10 page

Practical Encrypted Network Traffic Pattern Matching for Secure Middleboxes

Network Function Virtualisation (NFV) advances the adoption of composable software middleboxes. Accordingly, cloud data centres become major NFV vendors for enterprise traffic processing. Due to the privacy concern of traffic redirection to the cloud, secure middlebox systems (e.g., BlindBox) draw much attention; they can process encrypted packets against encrypted rules directly. However, most of the existing systems supporting pattern matching based network functions require the enterprise gateway to tokenise packet payloads via sliding windows. Such tokenisation induces a considerable communication overhead, which can be over 100$\times$ to the packet size. To overcome this bottleneck, in this paper, we propose the first bandwidth-efficient encrypted pattern matching protocol for secure middleboxes. We resort to a primitive called symmetric hidden vector encryption (SHVE), and propose a variant of it, aka SHVE+, to achieve constant and moderate communication cost. To speed up, we devise encrypted filters to reduce the number of accesses to SHVE+ during matching highly. We formalise the security of our proposed protocol and conduct comprehensive evaluations over real-world rulesets and traffic dumps. The results show that our design can inspect a packet over 20k rules within 100 $\mu$s. Compared to prior work, it brings a saving of 94$\%$ in bandwidth consumption

Result Pattern Hiding Searchable Encryption for Conjunctive Queries

The recently proposed Oblivious Cross-Tags (OXT) protocol (CRYPTO 2013) has broken new ground in designing efficient searchable symmetric encryption (SSE) protocol with support for conjunctive keyword search in a single-writer single-reader framework. While the OXT protocol offers high performance by adopting a number of specialised data-structures, it also trades-off security by leaking ‘partial’ database information to the server. Recent attacks have exploited similar partial information leakage to breach database confidentiality. Consequently, it is an open problem to design SSE protocols that plug such leakages while retaining similar efficiency. In this paper, we propose a new SSE protocol, called Hidden Cross-Tags (HXT), that removes ‘Keyword Pair Result Pattern’ (KPRP) leakage for conjunctive keyword search. We avoid this leakage by adopting two additional cryptographic primitives - Hidden Vector Encryption (HVE) and probabilistic (Bloom filter) indexing into the HXT protocol. We propose a ‘lightweight’ HVE scheme that only uses efficient symmetric-key building blocks, and entirely avoids elliptic curve-based operations. At the same time, it affords selective simulation-security against an unbounded number of secret-key queries. Adopting this efficient HVE scheme, the overall practical storage and computational overheads of HXT over OXT are relatively small (no more than 10% for two keywords query, and 21% for six keywords query), while providing a higher level of security

Secret Picture: An Efficient Tool for Mitigating Deletion Delay on OSN

With the increasing popularity of online social networks (OSNs) and the ability to access and exchange sensitive user information, user privacy concerns become an important issue which have attracted the attention of researchers and policymakers. For example, deleted pictures or pictures in deleted posts may not be deleted from the OSN server immediately, and hence accessible to another unauthorized user. In this paper, we highlight the deletion delay issue in seven popular OSNs, namely: Facebook, Instagram, MySpace, Tumblr, Flickr, Google+ and Weibo, which can be exploited by another unauthorized user to gain access to these pictures. To ensure OSN users are able to achieve a higher level of privacy, we propose a conceptual privacy-preserving tool for photo sharing, without compromising on transparency and real-time sharing features. We demonstrate the utility of the tool by prototyping a browser extension, which does not require modification of existing OSN systems

Renal cell carcinoma growing into the renal pelvis and mimicking transitional cell carcinoma: A case report and literature review

Renal cell carcinoma (RCC) originated from parenchyma and the majority of malignancies originating in the renal pelvis are transitional cell carcinoma (TCC). In the present study, a rare case of RCC growing into the renal pelvis and mimicking TCC in medical imaging is reported. The preoperative differentiation between RCC and TCC is important in order to identify the type of surgical treatment required: Nephrectomy or ureteronephrectomy. The role of ureteroscopy and biopsy is emphasized in the accurate preoperative diagnosis of a renal pelvic mass. Thus, the present study provided fundamental evidence for the pathogenesis of RCC with pelvic extension and challenged the present tumor node metastasis staging system of RCC