TL;DR
A flexible privacy-preserving framework that combines the scalability of broadcast encryption with the fine-grained access control of Attribute-Based Encryption through a novel pseudo-layer encryption model, and achieves confidentiality, forward and backward secrecy, and collusion resistance.
Smart home platforms predominantly adopt the broker-mediated publish/subscribe model (e.g., MQTT) for seamless device-app coordination. However, this architecture introduces a fundamental privacy-functionality conflict: the broker requires plaintext metadata (topic strings) for message routing, which inadvertently exposes fine-grained user behavioral patterns to semi-trusted service providers. Furthermore, existing systems lack rigorous cryptographic enforcement for app permissions, leaving the ecosystem vulnerable to over-privileged or malicious apps. While conventional Attribute-Based Encryption (ABE) provides fine-grained read-side access control, it cannot enforce writer-bound policies and remains computationally prohibitive for resource-constrained IoT nodes. In this paper, we propose SHERLOC, a practical and privacy-preserving framework that reconciles secure message routing with fine-grained privilege control. SHERLOC introduces two core primitives: (1) Secret Queue Telemetry Transport (SQTT), which leverages a novel trapdoor-based matching mechanism to support multi-level wildcard routing while ensuring topic indistinguishability and resistance against inside keyword-guessing attacks (IKGA); and (2) Outsourced Inner-Product Access Control Encryption (OS-IPACE), an attribute-hiding scheme that enforces dual no-read and no-write security for apps by offloading intensive pairing operations to a local hub without compromising data secrecy. We provide formal security proofs reducing SHERLOC’s privacy guarantees to the SXDH assumption. Experimental results from a full-scale prototype, comprising ESP32-based devices and Android apps, demonstrate that SHERLOC incurs millisecond-level latency and maintains compatibility with legacy MQTT brokers without altering protocol semantics, making it a robust and deployable solution for modern smart home environments.
In cloud computing environments, data sharing serves as a foundational enabler of collaborative operations across heterogeneous terminals. However, such sharing introduces critical challenges–including privacy leakage, inadequate data security, inflexible access control policies, and substantial computational latency. To address these limitations, this paper proposes a privacy-preserving, secure data-sharing framework tailored for edge-cloud collaborative architectures. Relative to conventional approaches, the proposed framework delivers three principal advancements: (1) User Privacy Protection: We design a secure query-matching algorithm that protects plaintext query keywords during data access. The Cloud Server (CS) performs matching over encrypted trapdoors without directly learning the queried keywords. (2) Computational Efficiency Improvement: Edge Servers (ESs) perform outsourced ciphertext transformation using user-specific transformation keys. The terminal only performs a lightweight local operation to recover the resource. This approach minimizes the computational overhead on the terminal side while safeguarding user privacy, and effectively reduces the overhead associated with user joining and revocation within the same group. (3) Fine-Grained, Policy-Driven Access Control: A cryptographically enforced, attribute- and keyword-aware access control mechanism is implemented, supporting precise, context-sensitive authorization decisions via encrypted keyword search and semantic matching–thereby enhancing both the security posture and operational flexibility of data access control.
The consumer Internet of Things (CIoT) enables large-scale sensing and data-driven services by connecting billions of devices. However, the privacy-preserving data aggregation in mobile edge computing (MEC)-enabled CIoT remains challenging when the edge aggregator is malicious, rather than simply honest-but-curious. Specifically, a malicious MEC server can selectively drop user reports or tamper with ciphertexts, undermining data integrity and ownership. To address this, we propose a verifiable and fault-tolerant privacy-preserving aggregation scheme. By substituting computationally intensive homomorphic encryption (HE) with a double-masking mechanism and integrating bilinear pairing-based accumulators, the proposed scheme provides resilience against tampering and deletion attacks while ensuring data privacy. The design supports user dropouts within a single reporting round without requiring interactive recovery, enabling each device to locally audit the inclusion of the corresponding ciphertext via a compact membership witness. Theoretical analysis and experimental results demonstrate that the proposed scheme reduces communication overhead and payload size. It satisfies the security requirements of CIoT ecosystems and offers a practical tradeoff between security and efficiency for latency-sensitive deployments.
Anonymous credentials (ACs) are a crucial cryptographic tool for privacy-preserving authentication in decentralized networks, allowing holders to prove eligibility without revealing their identity. However, a major limitation of standard ACs is the disclosure of the issuer’s identity, which can leak sensitive contextual information about the holder. Issuer-hiding ACs address this by making a credential’s origin indistinguishable among a set of issuers. Despite this advancement, existing solutions suffer from practical limitations that hinder their deployment in decentralized environments: inflexible credential models that restrict issuer and holder autonomy, flawed revocation mechanisms that compromise security, and weak attribute hiding that fails to meet data minimization principles. This paper introduces a new scheme called IRAC to overcome these challenges. We propose a flexible credential model that employs vector commitments with a padding strategy to unify credentials from heterogeneous issuers, enabling privacy-preserving authentication without enforcing a global static attribute set or verifier-defined policies. Furthermore, we design a secure decentralized revocation mechanism where holders prove non-revocation by demonstrating their credential’s hash lies within a gap in the issuer’s sorted revocation list while maintaining issuer anonymity. IRAC also strengthens attribute hiding by utilizing zk-SNARKs and vector commitments, allowing holders to prove statements about their attributes without disclosing the attributes themselves or the credential structure. Security analysis and performance evaluations demonstrate its practical feasibility for decentralized networks, where a credential presentation can be generated within 1 second.
Confidential communication among a dynamic group of participants that ensures flexible and efficient many-to- many communication is highly desired capability. We leverage attribute-based encryption (ABE) for confidential group communication and enhance it by a graph-based namespace to create an efficient framework that allows groups to be formed and changed dynamically. In this paper, we focus on the important additional need to maintain the anonymity of recipients of a message, when using ABE for group communication for a variety of usage scenarios (e.g., emergency response). We propose ABEAT, an efficient and anonymous dynamic group communication system that also minimizes overhead on receivers who are not the intended recipients of a message. In ABEAT, we propose a new anonymous KP-ABE approach to maintain recipient anonymity. ABEAT hides the clear attribute in the ciphertext of KP-ABE, and also prevents several attacks that seek to break anonymity. ABEAT provides fast recipient verification, dramatically lowering the decryption overhead for non-recipients by more than a factor of 90 versus the current state of the art such as hidden vector encryption (HVE). In fact, it is even 40% less than FABEO, which offers no anonymity.
In this paper, a behaviour-sensitive session orchestration architecture over secure communication and the rationale behind it will be proposed and discussed, which is a variant of mixed public-key cryptography that aims at offering more manageable, secret, and authenticity in real-time messaging infrastructure. The architecture incorporates the use of RSA and Diffie Hellman in ensuring the setup of user sessions and relies on AES to encrypt instantaneous messages very quickly. Multi-fernet algorithm supports the distribution of session keys and ensures that the key is recovered by the authorized parties only. There are also digital signatures based on RSA that facilitate authentication and non-repudiation but strong hash algorithms are applied to ensure the privacy of user passwords. The system has collaborative features along with cryptographic protection, including co-host delegation, active user blocking, permissions and multi-session to support multi-user logins. Also, the design enables the dynamically updating of the authentication credentials without disruption of the existing communication. The suggested hybrid configuration has a higher level of defense against cryptographic attacks and unauthorized access than single algorithm implementations, which is why it is a more robust and secure solution. In conclusion, the provided solution contributes to the fact that the process of communication in the environment of multi-users becomes much safer, convenient, and manageable.