Leakage-Resilient Inner-Product Functional Encryption in the Bounded-Retrieval Model

We propose a leakage-resilient inner-product functional encryption scheme (IPFE) in the bounded-retrieval model (BRM). This is the first leakage-resilient functional encryption scheme in the BRM. In our leakage model, an adversary is allowed to obtain at most $l$-bit knowledge from each secret key. And our scheme can flexibly tolerate arbitrarily leakage bound $l$, by only increasing the size of secret keys, while keeping all other parts small and independent of $l$. Technically, we develop a new notion: Inner-product hash proof system (IP-HPS). IP-HPS is a variant of traditional hash proof systems. Its output of decapsulation is an inner-product value, instead of the encapsulated key. We propose an IP-HPS scheme under DDH-assumption. Then we show how to make an IP-HPS scheme to tolerate $l\u27$-bit leakage, and we can achieve arbitrary large $l\u27$ by only increasing the size of secret keys. Finally, we show how to build a leakage-resilient IPFE in the BRM with leakage bound $l=\frac{l\u27}{n}$ from our IP-HPS scheme

Updatable Public Key Encryption in the Standard Model

Forward security (FS) ensures that corrupting the current secret key in the system preserves the privacy or integrity of the prior usages of the system. Achieving forward security is especially hard in the setting of public-key encryption (PKE), where time is divided into periods, and in each period the receiver derives the next-period secret key from their current secret key, while the public key stays constant. Indeed, all current constructions of FS-PKE are built from hierarchical identity-based encryption (HIBE) and are rather complicated. Motivated by applications to secure messaging, recent works of Jost et al. (Eurocrypt’19) and Alwen et al. (CRYPTO’20) consider a natural relaxation of FS-PKE, which they term updatable PKE (UPKE). In this setting, the transition to the next period can be initiated by any sender, who can compute a special update ciphertext. This ciphertext directly produces the next-period public key and can be processed by the receiver to compute the next-period secret key. If done honestly, future (regular) ciphertexts produced with the new public key can be decrypted with the new secret key, but past such ciphertexts cannot be decrypted with the new secret key. Moreover, this is true even if all other previous-period updates were initiated by untrusted senders. Both papers also constructed a very simple UPKE scheme based on the CDH assumption in the random oracle model. However, they left open the question of building such schemes in the standard model, or based on other (e.g., post-quantum) assumptions, without using the heavy HIBE techniques. In this work, we construct two efficient UPKE schemes in the standard model, based on the DDH and LWE assumptions, respectively. Somewhat interestingly, our constructions gain their efficiency (compared to prior FS-PKE schemes) by using tools from the area of circular-secure and leakage resilient public-key encryption schemes (rather than HIBE)

Attribute-based encryption for cloud computing access control: A survey

National Research Foundation (NRF) Singapore; AXA Research Fun

Fully Secure Cipertext-Policy Hiding CP-ABE

Lecture Notes in Computer Science, 2011, Volume 6672/2011, 24-39</p

Trustworthy Federated Learning: A Survey

Federated Learning (FL) has emerged as a significant advancement in the field of Artificial Intelligence (AI), enabling collaborative model training across distributed devices while maintaining data privacy. As the importance of FL increases, addressing trustworthiness issues in its various aspects becomes crucial. In this survey, we provide an extensive overview of the current state of Trustworthy FL, exploring existing solutions and well-defined pillars relevant to Trustworthy . Despite the growth in literature on trustworthy centralized Machine Learning (ML)/Deep Learning (DL), further efforts are necessary to identify trustworthiness pillars and evaluation metrics specific to FL models, as well as to develop solutions for computing trustworthiness levels. We propose a taxonomy that encompasses three main pillars: Interpretability, Fairness, and Security & Privacy. Each pillar represents a dimension of trust, further broken down into different notions. Our survey covers trustworthiness challenges at every level in FL settings. We present a comprehensive architecture of Trustworthy FL, addressing the fundamental principles underlying the concept, and offer an in-depth analysis of trust assessment mechanisms. In conclusion, we identify key research challenges related to every aspect of Trustworthy FL and suggest future research directions. This comprehensive survey serves as a valuable resource for researchers and practitioners working on the development and implementation of Trustworthy FL systems, contributing to a more secure and reliable AI landscape.Comment: 45 Pages, 8 Figures, 9 Table

Toward unified security and privacy protection for smart meter networks

The management of security and privacy protection mechanisms is one fundamental issue of future smart grid and metering networks. Designing effective and economic measures is a non-trivial task due to a) the large number of system requirements and b) the uncertainty over how the system functionalities are going to be specified and evolve. The paper explores a unified approach for addressing security and privacy of smart metering systems. In the process, we present a unified framework that entails the analysis and synthesis of security solutions associated with closely interrelated components of a typical smart metering system. Ultimately, the proposed framework can be used as a guideline for embedding cross-domain security and privacy solutions into smart grid communication systems

KDM Security for Identity-Based Encryption: Constructions and Separations

For encryption schemes, key dependent message (KDM) security requires that ciphertexts preserve secrecy even when the messages to be encrypted depend on the secret keys. While KDM security has been extensively studied for public-key encryption (PKE), it receives much less attention in the setting of identity-based encryption (IBE). In this work, we focus on the KDM security for IBE. Our results are threefold. We first propose a generic approach to transfer the KDM security results (both positive and negative) from PKE to IBE. At the heart of our approach is a neat structure-mirroring PKE-to-IBE transformation based on indistinguishability obfuscation and puncturable PRFs, which establishes a connection between PKE and IBE in general. However, the obtained results are restricted to selective-identity sense. We then concentrate on results in adaptive-identity sense. On the positive side, we present two constructions that achieve KDM security in the adaptive-identity sense for the first time. One is built from identity-based hash proof system (IB-HPS) with homomorphic property, which indicates that the IBE schemes of Gentry (Eurocrypt 2006), Coron (DCC 2009), Chow et al. (CCS 2010) are actually KDM-secure in the single-key setting. The other is built from indistinguishability obfuscation and a new notion named puncturable unique signature, which is bounded KDM-secure in the single-key setting. On the negative side, we separate CPA/CCA security from $n$-circular security (which is a prototypical case of KDM security) for IBE by giving a counterexample based on differing-inputs obfuscation and a new notion named puncturable IBE. We further propose a general framework for generating $n$-circular security counterexamples in identity-based setting, which might be of independent interest

Droplet: Decentralized Authorization for IoT Data Streams

This paper presents Droplet, a decentralized data access control service, which operates without intermediate trust entities. Droplet enables data owners to securely and selectively share their encrypted data while guaranteeing data confidentiality against unauthorized parties. Droplet's contribution lies in coupling two key ideas: (i) a new cryptographically-enforced access control scheme for encrypted data streams that enables users to define fine-grained stream-specific access policies, and (ii) a decentralized authorization service that handles user-defined access policies. In this paper, we present Droplet's design, the reference implementation of Droplet, and experimental results of three case-study apps atop of Droplet: Fitbit activity tracker, Ava health tracker, and ECOviz smart meter dashboard