The goal of the energy internet is to enable communication between distributed energy endpoints to facilitate information exchange and trading matching. Blockchain, which ensures content consistency, bridges the gaps between multiple energy stakeholders and satisfies the need for universal trust. However, applying blockchain directly in peer-to-peer trading can result in the permanent inclusion of illegal or outdated data in blockchain databases, hindering efficient interaction. Driven by emerging application requirements and legal regulations, redactable blockchain (EuroS&P 2017) was introduced, allowing the block history to be rewritten via collisions in chameleon hash functions. Nevertheless, current solutions still face challenges, including trapdoor security risks, privacy leakage, and indefinite redactions. This paper presents a redactable energy blockchain scheme (REBS) with partially attribute-based policy hiding, which enables controlled multi-authority key generation and redactor attribute verification. To prevent the abuse of redaction permission, REBS employs time-updatable chameleon hash functions for redaction. Additionally, we design a delegation algorithm that adds dynamic flexibility to attribute verification nodes, permitting them to delegate key share distribution authority to other nodes on demand. The detailed security proofs and performance evaluations demonstrate the feasibility of REBS.

Data cleaning improves quality and consistency by detecting, localizing, and repairing “dirty” data without compromising sensitive information. Collaborative Data Cleaning employs a distributed model to avoid single points of failure and trust issues in centralized systems, although it incurs additional communication overhead. Blass et al. (S&P’23) were the first to implement CDC via balanced Private Set Intersection (PSI). Unbalanced PSI (e.g.,uPSI-CA, USENIX’23) does not address the localization of intersections within datasets and thus cannot be directly applied to CDC. uPSI-based data cleaning remains largely unexplored. In this paper, we propose an efficient CDC scheme for unbalanced datasets, nameduECDC.uECDCemploys oblivious key-value stores for slice matching, achieving: i) a reduction of 18% ~ 85% in offline phase runtime, and ii) a reduction of 8% ~ 43% in online phase runtime (under large-scale data settings on the server side), when compared to the slice-linking approach ofuPSI-CA. Moreover, we encode server-side data for fast localization of intersection data in unbalanced settings. Under the semi-honest adversary model,uECDCis provably secure. Implementation in Python and C++ demonstrates thatuECDCis practically feasible.

An optimized implementation of S-boxes has a significant impact on the performance of cryptographic primitives. SAT-based methods can find optimal implementations for moderately sized S-boxes but their efficiency decreases when handling complex S-boxes. To improve the efficiency of the implementations, we propose two different methods, namely OR-encoding and IF-encoding, to encode the implementations of S-boxes. Furthermore, we also simplify the encoding of the outputs of logic gates and introduce new SAT-based search methods to optimize the implementations of S-boxes. Finally, to get a better trade-off between the search results (optimized implementations of S-boxes) and the search efficiency (in terms of time complexity), an encoding scheme using local solutions is proposed. Compared to the previous methods, our algorithms are relatively simple and more efficient. For instance, when a serial software implementation is considered, then the S-boxes of Sycon, ASCON, and the$\chi $function in Xoodyak, require 6, 1, and 2 fewer programming instructions, respectively, than the best known methods. Similar improvements are obtained for hardware implementations of S-boxes in some cryptographic primitives (e.g. LBlock, RECTANGLE, PRESENT/PHOTON-Beetle, TWINE, and ASCON), with the saving of gate equivalent (GE) that range from 1.67GE to 5.34GE compared to the current best implementations. Furthermore, our model can be applied to 6-bit, 7-bit, and 8-bit S-boxes, when the considered S-boxes are of low complexity.

Keyword-based auditing (KA) provides a means for users to verify the integrity of only the outsourced data they are interested in. Existing KA schemes employ relation authentication labels to conduct targeted audits with keywords, which significantly improves the cost-effectiveness. However, such schemes typically support only a single-challenge scenario, which may not always be practical. To overcome this constraint, we introduce a hierarchical challenge mechanism grounded in user attributes. This mechanism leverages inequality and affiliation relationships to comply with a predefined tree structure for access policies. Incorporated during the challenge-response phase of the auditing model, it permits users to initiate cross-challenges. Expanding upon this hierarchical mechanism, we propose an attribute-based hierarchical keyword auditing scheme, abbreviated as$\mathcal{AHKA}$.$\mathcal{AHKA}$combines searchable encryption to conduct cross-targeted audits and benefits from the hash collision mapping of Bloom filters to safeguard against keyword guessing attacks. Moreover, we design a fault localization algorithm based on a variant of the binary search technique. It locates in batch the faulty cloud servers and damaged data blocks after an audit failure. As an integral part of$\mathcal{AHKA}$, the algorithm significantly enhances our scheme's practicability. Security analyses indicate that$\mathcal{AHKA}$can effectively withstand both forgery and replace attacks on audit proofs. The smart contract component ensures that our scheme's processes can be monitored and regulated. Experimental data corroborate that deploying$\mathcal{AHKA}$on the client side and on the blockchain is both efficient and feasible.

The concept of transparency order is introduced to measure the resistance of n , m -functions against multi-bit differential power analysis in the Hamming weight model, including the original transparency order (denoted by TO ), redefined transparency order (denoted by RTO ), and modified transparency order (denoted by MTO ). In this paper, we firstly give a relationship between MTO and RTO and show that RTO is less than or equal to MTO for any n , m -functions. We also give a tight upper bound and a tight lower bound on MTO for balanced n , m -functions. Secondly, some relationships between MTO and the maximal absolute value of the Walsh transform (or the sum-of-squares indicator, algebraic immunity, and the nonlinearity of its coordinates) for n , m -functions are obtained, respectively. Finally, we give MTO and RTO for (4,4) S-boxes which are commonly used in the design of lightweight block ciphers, respectively.

Encryption algorithm has an important application in ensuring the security of the Internet of Things. Boolean function is the basic component of symmetric encryption algorithm, and its many cryptographic properties are important indicators to measure the security of cryptographic algorithm. This paper focuses on the sum-of-squares indicator of Boolean function; an upper bound and a lower bound of the sum-of-squares on Boolean functions are obtained by the decomposition Boolean functions; some properties and a search algorithm of Boolean functions with the same autocorrelation (or cross-correlation) distribution are given. Finally, a construction method to obtain a balanced Boolean function with small sum-of-squares indicator is derived by decomposition Boolean functions. Compared with the known balanced Boolean functions, the constructed functions have the higher nonlinearity and the better global avalanche characteristics property.