GraphSE2^2: An Encrypted Graph Database for Privacy-Preserving Social Search

In this paper, we propose GraphSE$^2$, an encrypted graph database for online social network services to address massive data breaches. GraphSE$^2$ preserves the functionality of social search, a key enabler for quality social network services, where social search queries are conducted on a large-scale social graph and meanwhile perform set and computational operations on user-generated contents. To enable efficient privacy-preserving social search, GraphSE$^2$ provides an encrypted structural data model to facilitate parallel and encrypted graph data access. It is also designed to decompose complex social search queries into atomic operations and realise them via interchangeable protocols in a fast and scalable manner. We build GraphSE$^2$ with various queries supported in the Facebook graph search engine and implement a full-fledged prototype. Extensive evaluations on Azure Cloud demonstrate that GraphSE$^2$ is practical for querying a social graph with a million of users.Comment: This is the full version of our AsiaCCS paper "GraphSE$^2$: An Encrypted Graph Database for Privacy-Preserving Social Search". It includes the security proof of the proposed scheme. If you want to cite our work, please cite the conference version of i

Lightweight Symmetric-Key Hidden Vector Encryption without Pairings

Hidden vector encryption (HVE), introduced by Boneh and Waters in TCC\u2707, is an expressive sub-class of predicate encryption, that allows conjunctive, subset, range and comparison queries over encrypted data. All existing HVE constructions in the cryptographic literature use bilinear pairings over either composite order or prime order groups. In this paper, we address the open problem of constructing a lightweight symmetric-key HVE scheme that does not use bilinear pairings, but only efficient cryptographic primitives such as pseudo-random functions (PRFs) and block ciphers. The relevance of this problem stems from the implementation and performance overheads for bilinear pairings over composite/prime order groups, which are significantly larger than that for PRFs and block ciphers, in both software and hardware. While lightweight symmetric-key constructions exist for keyword search on encrypted data, we aim to expand the scope of such constructions to support a richer set of query predicates. In this direction, we present the first lightweight symmetric-key HVE construction that does not use bilinear pairings. Our construction only uses a PRF and a PCPA-secure symmetric-key encryption algorithm, making it amenable to both hardware and software implementations in real-life resource-constrained environments. We prove the selective-simulation-security and adaptive-simulation-security of our construction in the standard model and ideal cipher model, respectively, against probabilistic polynomial-time adversaries that can make an unrestricted number of ciphertext generation and secret-key generation queries

Token Based Authentication and Authorization with Zero-Knowledge Proofs for Enhancing Web API Security and Privacy

This design science study showcases an innovative artifact that utilizes Zero-Knowledge Proofs for API Authentication and Authorization. A comprehensive examination of existing literature and technology is conducted to evaluate the effectiveness of this alternative approach. The study reveals that existing APIs are using slower techniques that don’t scale, can’t take advantage of newer hardware, and have been unable to adequately address current security issues. In contrast, the novel technique presented in this study performs better, is more resilient in privacy sensitive and security settings, and is easy to implement and deploy. Additionally, this study identifies potential avenues for further research that could help advance the field of Web API development in terms of security, privacy, and simplicity

Indistinguishability Obfuscation from Simple-to-State Hard Problems: New Assumptions, New Techniques, and Simplification

In this work, we study the question of what set of simple-to-state assumptions suffice for constructing functional encryption and indistinguishability obfuscation ($i\mathcal{O}$), supporting all functions describable by polynomial-size circuits. Our work improves over the state-of-the-art work of Jain, Lin, Matt, and Sahai (Eurocrypt 2019) in multiple dimensions. New Assumption: Previous to our work, all constructions of $i\mathcal{O}$ from simple assumptions required novel pseudorandomness generators involving LWE samples and constant-degree polynomials over the integers, evaluated on the error of the LWE samples. In contrast, Boolean pseudorandom generators (PRGs) computable by constant-degree polynomials have been extensively studied since the work of Goldreich (2000). We show how to replace the novel pseudorandom objects over the integers used in previous works, with appropriate Boolean pseudorandom generators with sufficient stretch, when combined with LWE with binary error over suitable parameters. Both binary error LWE and constant degree Goldreich PRGs have been a subject of extensive cryptanalysis since much before our work and thus we back the plausibility of our assumption with security against algorithms studied in context of cryptanalysis of these objects. New Techniques: We introduce a number of new techniques: - We show how to build partially-hiding \emph{public-key} functional encryption, supporting degree-2 functions in the secret part of the message, and arithmetic $\mathsf{NC}^1$ functions over the public part of the message, assuming only standard assumptions over asymmetric pairing groups. - We construct single-ciphertext and single-secret-key functional encryption for all circuits with long outputs, which has the features of {\em linear} key generation and compact ciphertext, assuming only the LWE assumption. Simplification: Unlike prior works, our new techniques furthermore let us construct {\em public-key} functional encryption for polynomial-sized circuits directly (without invoking any bootstrapping theorem, nor transformation from secret-key to public key FE), and based only on the {\em polynomial hardness} of underlying assumptions. The functional encryption scheme satisfies a strong notion of efficiency where the size of the ciphertext is independent of the size of the circuit to be computed, and grows only sublinearly in the output size of the circuit and polynomially in the input size and the depth of the circuit. Finally, assuming that the underlying assumptions are subexponentially hard, we can bootstrap this construction to achieve $i\mathcal{O}$

Data Service Outsourcing and Privacy Protection in Mobile Internet

Mobile Internet data have the characteristics of large scale, variety of patterns, and complex association. On the one hand, it needs efficient data processing model to provide support for data services, and on the other hand, it needs certain computing resources to provide data security services. Due to the limited resources of mobile terminals, it is impossible to complete large-scale data computation and storage. However, outsourcing to third parties may cause some risks in user privacy protection. This monography focuses on key technologies of data service outsourcing and privacy protection, including the existing methods of data analysis and processing, the fine-grained data access control through effective user privacy protection mechanism, and the data sharing in the mobile Internet

Data Sharing on Untrusted Storage with Attribute-Based Encryption

Storing data on untrusted storage makes secure data sharing a challenge issue. On one hand, data access policies should be enforced on these storage servers; on the other hand, confidentiality of sensitive data should be well protected against them. Cryptographic methods are usually applied to address this issue -- only encrypted data are stored on storage servers while retaining secret key(s) to the data owner herself; user access is granted by issuing the corresponding data decryption keys. The main challenges for cryptographic methods include simultaneously achieving system scalability and fine-grained data access control, efficient key/user management, user accountability and etc. To address these challenge issues, this dissertation studies and enhances a novel public-key cryptography -- attribute-based encryption (ABE), and applies it for fine-grained data access control on untrusted storage. The first part of this dissertation discusses the necessity of applying ABE to secure data sharing on untrusted storage and addresses several security issues for ABE. More specifically, we propose three enhancement schemes for ABE: In the first enhancement scheme, we focus on how to revoke users in ABE with the help of untrusted servers. In this work, we enable the data owner to delegate most computation-intensive tasks pertained to user revocation to untrusted servers without disclosing data content to them. In the second enhancement scheme, we address key abuse attacks in ABE, in which authorized but malicious users abuse their access privileges by sharing their decryption keys with unauthorized users. Our proposed scheme makes it possible for the data owner to efficiently disclose the original key owner\u27s identity merely by checking the input and output of a suspicious user\u27s decryption device. Our third enhancement schemes study the issue of privacy preservation in ABE. Specifically, our proposed schemes hide the data owner\u27s access policy not only to the untrusted servers but also to all the users. The second part presents our ABE-based secure data sharing solutions for two specific applications -- Cloud Computing and Wireless Sensor Networks (WSNs). In Cloud Computing cloud servers are usually operated by third-party providers, which are almost certain to be outside the trust domain of cloud users. To secure data storage and sharing for cloud users, our proposed scheme lets the data owner (also a cloud user) generate her own ABE keys for data encryption and take the full control on key distribution/revocation. The main challenge in this work is to make the computation load affordable to the data owner and data consumers (both are cloud users). We address this challenge by uniquely combining various computation delegation techniques with ABE and allow both the data owner and data consumers to securely mitigate most computation-intensive tasks to cloud servers which are envisaged to have unlimited resources. In WSNs, wireless sensor nodes are often unattendedly deployed in the field and vulnerable to strong attacks such as memory breach. For securing storage and sharing of data on distributed storage sensor nodes while retaining data confidentiality, sensor nodes encrypt their collected data using ABE public keys and store encrypted data on storage nodes. Authorized users are given corresponding decryption keys to read data. The main challenge in this case is that sensor nodes are extremely resource-constrained and can just afford limited computation/communication load. Taking this into account we divide the lifetime of sensor nodes into phases and distribute the computation tasks into each phase. We also revised the original ABE scheme to make the overhead pertained to user revocation minimal for sensor nodes. Feasibility of the scheme is demonstrated by experiments on real sensor platforms

Security and Privacy Preservation in Mobile Advertising

Mobile advertising is emerging as a promising advertising strategy, which leverages prescriptive analytics, location-based distribution, and feedback-driven marketing to engage consumers with timely and targeted advertisements. In the current mobile advertising system, a third-party ad broker collects and manages advertisements for merchants who would like to promote their business to mobile users. Based on its large-scale database of user profiles, the ad broker can help the merchants to better reach out to customers with related interests and charges the merchants for ad dissemination services. Recently, mobile advertising technology has dominated the digital advertising industry and has become the main source of income for IT giants. However, there are many security and privacy challenges that may hinder the continuous success of the mobile advertising industry. First, there is a lack of advertising transparency in the current mobile advertising system. For example, mobile users are concerned about the reliability and trustworthiness of the ad dissemination process and advertising review system. Without proper countermeasures, mobile users can install ad-blocking software to filter out irrelevant or even misleading advertisements, which may lower the advertising investments from merchants. Second, as more strict privacy regulations (e.g. European General Data Privacy Regulations) take effect, it is critical to protect mobile users’ personal profiles from illegal sharing and exposure in the mobile advertising system. In this thesis, three security and privacy challenges for the mobile advertising system are identified and addressed with the designs, implementations, and evaluations of a blockchain-based architecture. First, we study the anonymous review system for the mobile advertising industry. When receiving advertisements from a specific merchant (e.g. a nearby restaurant), mobile users are more likely to browse the previous reviews about the merchant for quality-of-service assessments. However, current review systems are known for the lack of system transparency and are subject to many attacks, such as double reviews and deletions of negative reviews. We exploit the tamper-proof nature and the distributed consensus mechanism of the blockchain technology, to design a blockchain-based review system for mobile advertising, where review accumulations are transparent and verifiable to the public. To preserve user review privacy, we further design an anonymous review token generation scheme, where users are encouraged to leave reviews anonymously while still ensuring the review authenticity. We also explore the implementation challenges of the blockchain-based system on an Ethereum testing network and the experimental results demonstrate the application feasibility of the proposed anonymous review system. Second, we investigate the transparency issues for the targeted ad dissemination process. Specifically, we focus on a specific mobile advertising application: vehicular local advertising, where vehicular users send spatial-keyword queries to ad brokers to receive location-aware advertisements. To build a transparent advertising system, the ad brokers are required to provide mobile users with explanations on the ad dissemination process, e.g., why a specific ad is disseminated to a mobile user. However, such transparency explanations are often found incomplete and sometimes even misleading, which may lower the user trust on the advertising system if without proper countermeasures. Therefore, we design an advertising smart contract to efficiently realize a publicly verifiable spatial-keyword query scheme. Instead of directly implementing the spatial-keyword query scheme on the smart contract with prohibitive storage and computation cost, we exploit the on/off-chain computation models to trade the expensive on-chain cost for cheap off-chain cost. With two design strategies: digest-and-verify and divide-then-assemble, the on-chain cost for a single spatial keyword query is reduced to constant regardless of the scale of the spatial-keyword database. Extensive experiments are conducted to provide both on-chain and off-chain benchmarks with a verifiable computation framework. Third, we explore another critical requirement of the mobile advertising system: public accountability enforcement against advertising misconducts, if (1) mobile users receive irrelevant ads, or (2) advertising policies of merchants are not correctly computed in the ad dissemination process. This requires the design of a composite Succinct Non-interactive ARGument (SNARG) system, that can be tailored for different advertising transparency requirements and is efficient for the blockchain implementations. Moreover, pursuing public accountability should also achieve a strict privacy guarantee for the user profile. We also propose an accountability contract which can receive explanation requirements from both mobile users and merchants. To promote prompt on-chain responses, we design an incentive mechanism based on the pre-deposits of involved parties, i.e., ad brokers, mobile users, and merchants. If any advertising misconduct is identified, public accountability can be enforced by confiscating the pre-deposits of the misbehaving party. Comprehensive experiments and analyses are conducted to demonstrate the versatile functionalities and feasibility of the accountability contract. In summary, we have designed, implemented, and evaluated a blockchain-based architecture for security and privacy preservations in the mobile advertising. The designed architecture can not only enhance the transparency and accountability for the mobile advertising system, but has also achieved notably on-chain efficiency and privacy for real-world implementations. The results from the thesis may shed light on the future research and practice of a blockchain-based architecture for the privacy regulation compliance in the mobile advertising