Search Results (15)

For underwater acoustic sensor networks (UWSNs), we propose a lattice-based aggregate signcryption scheme (UASC) to achieve many to one secure and efficient communication in UWSNs. Firstly, UASC constructs the pseudo identity of the node, performs lattice Gaussian sampling on the pseudo identity to generate a partial key, and then combines the underwater environmental noise collected by the node to generate a complete private key, to avoid the key generation center (KGC) leakage problem. Furthermore, UASC reuses the mathematical structures of encryption and signature on the lattice, designing a signcryption framework to achieve identity authentication and data confidentiality protection. By using the relay capability of the surface sink node, UASC combines with the ring learning with errors (RLWE) encryption and the rejection sampling to perform batch signature verification on the aggregate ciphertext set, which improves the overall response efficiency of the system. In addition, to resist tracking attacks, a dynamic update mechanism of pseudo identity and key is designed in UASC. Security analysis and experimental results show that UASC reduces overhead while satisfying relevant security requirements. Full article

As cloud computing proliferates, outsourced data faces severe security threats, yet existing searchable encryption (SE) schemes rely on classical hardness assumptions, centralized trust authorities, and static access control, leaving critical gaps in quantum resistance, single-point-of-failure prevention, and dynamic permission management. To address these limitations, we propose BL-ABSE, a blockchain-enhanced, lattice-based attribute-based searchable encryption framework. BL-ABSE employs the Ring Learning With Errors (RLWE) problem as its security foundation and applies the Number Theoretic Transform (NTT) to reduce polynomial multiplication from $O\left(n^2\right)$ to $O(nlogn)$. To eliminate single-point trust risks, the framework further integrates a $(t,n)$ threshold key protocol across an edge-node consortium governed by Practical Byzantine Fault Tolerance (PBFT) consensus. A smart-contract-maintained on-chain revocation list enables permission withdrawal via a single blockchain transaction without re-encryption. Experimental evaluation demonstrates that commitment generation requires approximately 23 ms at $n=1024$, search latency scales linearly at roughly 29 µs per record, and revocation completes in approximately 2 s regardless of system scale. Formal security proofs under the quantum polynomial-time (QPT) adversary model reduce six security properties—index indistinguishability, query privacy, threshold key security, Byzantine fault tolerance, audit immutability, and revocation immediacy—to the hardness of RLWE and the Short Integer Solution (SIS) problems. To the best of our knowledge, BL-ABSE is the first framework to simultaneously achieve post-quantum security, attribute-based access control, decentralized key management, instant revocation, and immutable auditing within a single unified framework. We further conduct threshold parameter verification, end-to-end revocation latency decomposition, blockchain throughput stress testing, search-pattern leakage quantification, and communication/storage overhead analysis, providing a comprehensive evaluation of both performance and security trade-offs. We explicitly characterize the search-pattern leakage inherent in the deterministic commitment design as a correctness–privacy trade-off and discuss mitigation directions. Full article

Multi-Key Fully Homomorphic Encryption (MK-FHE) is essential for secure multi-party computation but currently faces significant scalability bottlenecks due to linear computational growth and low bootstrapping throughput. To address these limitations, we propose DMBB-RCB, a novel fully homomorphic, bit-wise Dynamic Multi-Key Block-Binary Ring-Compact Bootstrapping scheme. Our contribution is threefold. First, we integrate the Block Binary Distribution into the dynamic setting, reducing the complexity of the core blind rotation operation from O(P⋅n) to O(p⋅k) (where k ≪ n) by leveraging key sparsity. Second, we implement an amortized ring packing strategy that aggregates multiple Learning with Errors (LWE) ciphertexts into the coefficients of a single Ring Learning with Errors (RLWE) polynomial, enabling the parallel refreshing of messages. Third, we introduce a Ring-Compact extraction architecture that natively translates RLWE states into Multi-Key Regev–Gentry–Sahai–Waters (RGSW) ciphertexts via scheme switching. Unlike traditional pipelines that suffer from severe network latency due to interactive multi-party key-switching after each bootstrapping, our architecture keeps the data entirely within the ring domain. This completely eliminates intermediate interaction rounds, enabling depth-unbounded homomorphic evaluations with zero interaction between participants during the computation phase (interaction is strictly reserved for the final joint decryption step). The proposed scheme supports the dynamic addition of participants without parameter re-generation. Theoretical analysis confirms that DMBB-RCB significantly reduces latency and enhances throughput compared to existing dynamic MKHE solutions. Full article

Fully Homomorphic Encryption (FHE) provides strong data confidentiality during computation but often suffers from high latency on Central Processing Units (CPUs). This study evaluates Graphics Processing Unit (GPU) acceleration for modern FHE libraries across a laptop (NVIDIA GTX 1650 Ti), a server (NVIDIA RTX 4060), and a Jetson Nano 2 GB embedded GPU. We benchmark key generation, arithmetic operations, Boolean-gate evaluation and scheme-specific tasks such as relinearization and key switching, using library-provided benchmarks with an explicit baseline (operation scope, timing boundaries, and parameter tuples). Moreover, we compare GPU-native libraries (NuFHE, Phantom-FHE, and Troy-Nova) with CPU-oriented ones (Microsoft SEAL, HElib, OpenFHE, Cupcake, and TFHE-rs). Results show GPUs deliver significant speedups for targeted operations. For example, NuFHE’s NVIDIA CUDA (Compute Unified Device Architecture) backend achieves about 1.4× faster Boolean-gate evaluation on the laptop and 3.4× faster on the server compared to its OpenCL backend. Likewise, RLWE (Ring Learning With Errors)-based schemes (BFV, CKKS, and BGV) see marked gains for polynomial arithmetic such as Number Theoretic Transform (NTT) when executed via Phantom-FHE. However, attempts to add CUDA support to Microsoft SEAL reveal four main challenges: high-precision modular arithmetic on GPUs, sequential dependencies in SEAL’s design, limited GPU memory and complex build-system changes. In light of these findings, we propose revised guidelines for GPU-first FHE libraries and practical recommendations for deploying high-throughput, privacy-preserving solutions on modern GPUs. Full article

To address the growing threat of quantum computing to classical cryptographic primitives, this study introduces NTRU-MCF, a novel lattice-based signature scheme that integrates multidimensional lattice structures with fractional-order chaotic systems. By extending the NTRU framework to multidimensional polynomial rings, NTRU-MCF exponentially expands the private key search space, achieving a key space size $\ge 2^{256}$ for dimensions $m\ge 2$ and rendering brute-force attacks infeasible. By incorporating fractional-order chaotic masks generated via a hyperchaotic Lü system, the scheme introduces nonlinear randomness and robust resistance to physical attacks. Fractional-order chaotic masks, generated via a hyperchaotic Lü system validated through NIST SP 800-22 randomness tests, replace conventional pseudorandom number generators (PRNGs). The sensitivity to initial conditions ensures cryptographic unpredictability, while the use of a fractional-order L hyperchaotic system—instead of conventional pseudorandom number generators (PRNGs)—leverages multiple Lyapunov exponents and initial value sensitivity to embed physically unclonable properties into key generation, effectively mitigating side-channel analysis. Theoretical analysis shows that NTRU-MCF’s security reduces to the Ring Learning with Errors (RLWE) problem, offering superior quantum resistance compared to existing NTRU variants. While its computational and storage complexity suits high-security applications like military and financial systems, it is less suitable for resource-constrained devices. NTRU-MCF provides robust quantum resistance and side-channel defense, advancing PQC for classical computing environments. Full article

In the context of increasing demand for secure and efficient communication networks, addressing the issue of mutual authentication in ethernet passive optical networks (EPONs) has become both valuable and practically significant. This paper proposes a solution based on ideal lattices. The proposed scheme leverages the security of the ring learning with errors (RLWE) problem to establish a robust public-key cryptosystem. By involving ONUs, OLTs, and an SDN controller in the authentication process, it enables mutual authentication through a series of message exchanges facilitated by the SDN controller. Utilizing approximate smooth projection hash functions for secure key exchange and verification, the scheme ensures robust security performance against various attacks, including man-in-the-middle, impersonation, replay, and known key secrecy attacks. Simulation results demonstrate that the proposed solution introduces minimal delay and maintains a high registration success rate compared to traditional authentication methods. Additionally, this paper explores the convergence of quantum network protocols with EPONs, highlighting their potential to achieve unprecedented levels of communication security. Integrating quantum technology with EPON networks, due to the unique security properties of quantum, can also better prevent man-in-the-middle attacks. Secure interception detection techniques based on fundamental quantum properties provide a fundamental security direction for future communication systems, aligning with the growing interest in quantum-resistant cryptographic protocols. Full article

Although the copyright protection schemes supported by blockchain have significantly changed traditional copyright data management, there are still some data security challenges that cannot be ignored, especially the secure access and controllable management of copyright data. Quantum computing attacks also pose a threat to its security. Targeting these issues, we design and propose a blockchain copyright protection scheme based on attribute-based encryption (ABE). In this scheme, the security advantages of blockchain technology are utilized to ensure the authenticity and integrity of copyright data. Based on lattice cryptography and the decision ring learning with errors (R-LWE) problem, a new ABE algorithm that supports searchable ciphertext and policy updates is designed. Then, we introduce it into the blockchain copyright protection scheme, which enables secure access to copyright data and fine-grained control. In addition, the lattice cryptography can strengthen this scheme against quantum attacks. Through security analysis, our scheme can prove to be secure against adaptive chosen keyword attacks, selective chosen plaintext attacks, and adaptive chosen policy attacks in the random oracle model. More importantly, the comparison analysis and experimental results show that our proposed approach has lower computation costs and storage costs. Therefore, our scheme has better security and performance in copyright protection. Full article

The digitization of healthcare data has presented a pressing need to address privacy concerns within the realm of machine learning for healthcare institutions. One promising solution is federated learning, which enables collaborative training of deep machine learning models among medical institutions by sharing model parameters instead of raw data. This study focuses on enhancing an existing privacy-preserving federated learning algorithm for medical data through the utilization of homomorphic encryption, building upon prior research. In contrast to the previous paper, this work is based upon Wibawa, using a single key for HE, our proposed solution is a practical implementation of a preprint with a proposed encryption scheme (xMK-CKKS) for implementing multi-key homomorphic encryption. For this, our work first involves modifying a simple “ring learning with error” RLWE scheme. We then fork a popular federated learning framework for Python where we integrate our own communication process with protocol buffers before we locate and modify the library’s existing training loop in order to further enhance the security of model updates with the multi-key homomorphic encryption scheme. Our experimental evaluations validate that, despite these modifications, our proposed framework maintains a robust model performance, as demonstrated by consistent metrics including validation accuracy, precision, f1-score, and recall. Full article

With the increasing number of edge devices connecting to the cloud for storage and analysis, concerns about security and data privacy have become more prominent. Homomorphic encryption (HE) provides a promising solution by not only preserving data privacy but also enabling meaningful computations on encrypted data; while considerable efforts have been devoted to accelerating expensive homomorphic evaluation in the cloud, little attention has been paid to optimizing encryption and decryption (ENC-DEC) operations on the edge. In this paper, we propose efficient hardware architectures for CKKS-based ENC-DEC accelerators to facilitate computations on the client side. The proposed architectures are configurable to support a wide range of polynomial sizes with multiplicative depths (up to 30 levels) at a 128-bit security guarantee. We evaluate the hardware designs on the Xilinx XCU250 FPGA platform and achieve an average encryption time 23.7× faster than that of the well-known SEAL HE library. By reducing time complexity and improving the hardware utilization of cryptographic algorithms, our configurable CKKS-supported ENC-DEC hardware designs have the potential to greatly accelerate cryptographic processes on the client side in the post-quantum era. Full article

Federal learning and privacy protection are inseparable. The participants in federated learning need to be the targets of privacy protection. On the other hand, federated learning can also be used as a tool for privacy attacks. Group signature is regarded as an effective tool for preserving user privacy. Additionally, message recovery is a useful cryptographic primitive that ensures message recovery during the verification phase. In federated learning, message recovery can reduce the transmission of parameters and help protect parameter privacy. In this paper, we propose a lattice-based group signature with message recovery (GS-MR). We then prove that the GS-MR scheme has full anonymity and traceability under the random oracle model, and we reduce anonymity and traceability to the hardness assumptions of ring learning with errors (RLWE) and ring short integer solution (RSIS), respectively. Furthermore, we conduct some experiments to evaluate the sizes of key and signature, and make a performance comparison between three lattice-based group signature schemes and the GS-MR scheme. The results show that the message–signature size of GS-MR is reduced by an average of 39.17% for less than 2000 members. Full article

Ever since the appearance of quantum computers, prime factoring and discrete logarithm-based cryptography have been questioned, giving birth to the so-called post-quantum cryptography. The most prominent field in post-quantum cryptography is lattice-based cryptography, protocols that are proved to be as difficult to break as certain hard lattice problems like Learning with Errors (LWE) or Ring Learning with Errors (R-LWE). Furthermore, the application of cryptographic techniques to different areas, like electronic voting, has also nourished a great interest in distributed cryptography. In this work, we will give two original threshold protocols based in the lattice problem R-LWE: one for key generation and one for decryption. We will prove them both correct and secure under the assumption of hardness of some well-known lattice problems. Finally, we will give a rough implementation of the protocols in C to give some tentative results about their viability, in particular our model generates keys in the order of ${10}^3$ ms and decrypts and encrypts in the order of ${10}^2$ ms. Full article

There exists a natural trade-off in public key encryption (PKE) schemes based on ring learning with errors (RLWE), namely: we would like a wider error distribution to increase the security, but it comes at the cost of an increased decryption failure rate (DFR). A straightforward solution to this problem is the error-correcting code, which is commonly used in communication systems and already appears in some RLWE-based proposals. However, applying error-correcting codes to those cryptographic schemes is far from simply installing an add-on. Firstly, the residue error term derived by decryption has correlated coefficients, whereas most prevalent error-correcting codes with remarkable error tolerance assume the channel noise to be independent and memoryless. This explains why only simple error-correcting methods are used in existing RLWE-based PKE schemes. Secondly, the residue error term has correlated coefficients leaving accurate DFR estimation challenging even for uncoded plaintext. It can be found in the literature that a tighter DFR estimation can effectively create a DFR margin. Thirdly, most error-correcting codes are not well designed for safety considerations, e.g., syndrome decoding has a nonconstant time nature. A code good at error correcting might be weak under a variety of attacks. In this work, we propose a polar coding scheme for RLWE-based PKE. A relaxed “independence” assumption is used to derive an uncorrelated residue noise term, and a wireless communication strategy, outage, is used to construct polar codes. Furthermore, some knowledge about the residue noise is exploited to improve the decoding performance. With the parameterization of NewHope Round 2, the proposed scheme creates a considerable DRF margin, which gives a competitive security improvement compared to state-of-the-art benchmarks. Specifically, the security is improved by $28.8\%$, while a DFR of $2^{-149}$ is achieved a for code rate pf 0.25, $n=1024,q=$ 12,289, and binomial parameter $k=55$. Moreover, polar encoding and decoding have a quasilinear complexity $O\left(N{log}_{2}N\right)$ and intrinsically support constant-time implementations. Full article

The “Multivariate Ring Learning with Errors” problem was presented as a generalization of Ring Learning with Errors (RLWE), introducing efficiency improvements with respect to the RLWE counterpart thanks to its multivariate structure. Nevertheless, the recent attack presented by Bootland, Castryck and Vercauteren has some important consequences on the security of the multivariate RLWE problem with “non-coprime” cyclotomics; this attack transforms instances of m-RLWE with power-of-two cyclotomic polynomials of degree $n={\prod }_i{n}_i$ into a set of RLWE samples with dimension ${max}_i\left\{n_i\right\}$. This is especially devastating for low-degree cyclotomics (e.g., ${\Phi }_4\left(x\right)=1+x^2$). In this work, we revisit the security of multivariate RLWE and propose new alternative instantiations of the problem that avoid the attack while still preserving the advantages of the multivariate structure, especially when using low-degree polynomials. Additionally, we show how to parameterize these instances in a secure and practical way, therefore enabling constructions and strategies based on m-RLWE that bring notable space and time efficiency improvements over current RLWE-based constructions. Full article

Identity-based encryption (IBE), and its hierarchical extension (HIBE), are interesting cryptographic primitives that aim at the implicit authentication on the users’ public keys by using users’ identities directly. During the past several decades, numerous elegant pairing-based (H)IBE schemes were proposed. However, most pairing-related security assumptions suffer from known quantum algorithmic attacks. Therefore, the construction of lattice-based (H)IBE became one of the hot directions in recent years. In the setting of most existing lattice-based (H)IBE schemes, each bit of a user’s identity is always associated with a parameter matrix. This always leads to drastic but unfavorable increases in the sizes of the system public parameters. To overcome this issue, we propose a flexible trade-off mechanism between the size of the public parameters and the involved computational cost using the blocking technique. More specifically, we divide an identity into $l^{\prime }$ segments and associate each segment with a matrix, while increasing the lattice modulo slightly for maintaining the same security level. As a result, for the setting of 160-bit identities, we show that the size of the public parameters can be reduced by almost 89.7% (resp. 93.8%) while increasing the computational cost by merely 5.2% (resp. 12.25%) when $l^{\prime }$ is a set of 16 (resp. 8). Finally, our IBE scheme is extended to an HIBE scheme, and both of them are proved to achieve the indistinguishability of ciphertexts against adaptively chosen identity and chosen plaintext attack (IND-ID-CPA) in the standard model, assuming that the well-known ring learning with error (RLWE) problem over the involved ideal lattices is intractable, even in the post-quantum era. Full article

In line with the proposed 5th Generation network, content centric network/named data networking (CCN/NDN) has been offered as one of the promising paradigms to cope with the communication needs of future realistic network communications. CCN/NDN allows network communication based on content names and also allows users to obtain information from any of the nearest intermediary caches on the network. Due to that, the ability of cached content to protect itself is essential since contents can be cached on any node everywhere, and publishers may not have total control over their own published data. The attribute based encryption (ABE) scheme is a preferable approach, identified to enable cached contents to be self-secured since it has a special property of encryption with policies. However, most of the proposed ABE schemes for CCN/NDN suffer from some loopholes. They are not flexible in the expression of access policy, they are inefficient, they are based on bilinear maps with pairings, and they are vulnerable to quantum cryptography algorithms. Hence, we propose the ciphertext policy attribute based encryption access control (CP-ABE AC) scheme from a lightweight ideal lattice based on ring learning with error (R-LWE) problem, and demonstrated its use in practical applications. The proposed scheme is proved to be secure and efficient under the decision ring LWE problem in the selective set model. To achieve an efficient scheme, we used an efficient trapdoor technique and the access tree representation of access structure describing the access policies was modified into a new structure, based on a reduced ordered binary decision diagram (reduce-OBDD). This access structure can support Boolean operations such as AND, NOT, OR, and threshold gates. The final result showed that the proposed scheme was secure and efficient for applications, thereby supporting CCN/NDN as a promising paradigm. Full article