We provide fast algorithms to compute the exact additive and XOR differential probabilities of ChaCha20 half quarter-round H and, under an independence assumption, an approximation of the differential probabilities of the full quarter-round. We give experimental evidence of the correctness of our approximation, and show that the independence assumption holds better for the XOR differential probability than the additive differential probability. We then propose an efficient greedy strategy to maximise differential characteristics for the full quarter-round, and use it to determine explicit differential trails for the ChaCha permutation. We also provide an MILP model to search for differential trails in ChaCha and compare its performance and effectiveness with our method. We believe these results might bring new insights in the differential cryptanalysis of ChaCha20 and of similar ARX ciphers.
The recent advances in cryptanalysis techniques and the leakage of information about the cryptosystem used are major threats to information systems. An adversary may succeed in decrypting ciphertexts, while users of a particular cryptosystem unknowingly continue using the compromised cryptosystem. Therefore, this paper presents a novel cryptosystem based on Latin square and cognitive AI/ML for blockchain and covert communications. This cryptosystem is capable of operating in quadruple modes keyless, symmetric, asymmetric, and hybrid encryption to cipher in cipher, and hence we call it CipherInCipher. Unlike all contemporary techniques including obscurity, CipherInCipher is a public-based approach that does not depend on the secrecy of any of its related components. It attains a high level of security that protects private information not only by having strong ciphertext but also by preventing an adversary from obtaining the actual ciphertext. The presented validation study demonstrates the robust CipherInCipher capabilities of achieving the cryptographic goal.
In ASIACRYPT 2017, Rønjom et al. reported Yoyo tricks on generic rounds of SPNs. Then they applied it to AES and found the most effective way to distinguish AES in several rounds. In FSE 2018, Saha et al. distinguished AES in a known key setting up to 8 rounds. In AFRICACRYPT 2022, Gupta et al. published a block cipher Future, whose design is like AES with some tweaks. In this paper, we analysed Future by Yoyo trick in both secret key settings and known key settings. We show that in the secret key setting, one can distinguish Future upto five and six rounds with data complexity 2 9.83 and 2 58.83 respectively. We also demonstrate that with known key settings, one can distinguish Future with data complexity 2 15 for both six and eight rounds. Our attack is based on an adaptively chosen plaintext/ciphertext attack.
In recent years, the development of various visual sensing and image analysis techniques has resulted in the creation of images that contain extremely sensitive data. Unauthorised individuals who access this data illegally risk capturing and disclosing all the sensitive information. To address this issue, we propose a simple and effective image and object encryption approach using a multiplicative cipher and K-means clustering algorithm. The proposed approach involves two levels of encryption, object detection, and K-means clustering in two different phases. In phase 1, the main object from the original image is encrypted using a multiplicative cipher. Phase 2 uses the K-means clustering technique to encrypt the noisy image generated in phase 1. The decryption process is similar to the encryption process but is carried out in reverse order. Moreover, the proposed approach is indeed lossless, even if data is encrypted multiple times. Furthermore, the proposed technique is demonstrated to be robust to differential attacks and resistant to statistical attacks. The results of different experiments show that the approach is effective, secure, and suitable for a wide range of industrial applications.
Attribute-based encryption (ABE) enables a flexible approach to data storage in the cloud by allowing many users to encrypt data with attributes and ensuring that only authorised users with the matching attributes can access the data. However, the original ABE system is often static, which limits its flexibility. Therefore, we propose a novel attribute-based encryption with security auditing, dynamic multi-authority, and privacy-preserving (PPADMA-ABE) system that enhances the practicality and flexibility. Our scheme supports dynamic changes under the coexistence of multiple authorities and enables self-auditing to meet potential practical requirements. Additionally, we have outsourced a significant amount of user-side operations, which reduces the decryption cost at the terminal to a constant level. Finally, we prove that our scheme is secure against selective chosen-ciphertext attacks and can withstand collusion by malicious users or authorities. In summary, PPADMA-ABE provides a more practical and flexible solution for dynamic multi-authority ABE with privacy preservation.
The development of smart applications in e-healthcare has aroused the exponential growth of healthcare data. Therefore, the data owner tends to outsource them to powerful cloud servers, which can provide query services. However, for privacy concerns, the data owner may outsource the encrypted data instead of plaintexts. Moreover, when using the data query service, query users may search the data based on their preferences. To address the aforementioned issues, in this paper, we propose WeightedSim, an efficient and privacy-preserving weighted similarity range query scheme for outsourced healthcare data. Specifically, we first develop an encrypted R-tree index by utilising the symmetric homomorphic encryption (SHE) technique and then employ it to perform a weighted similarity range query under the two cloud servers model. We analyse the security of our scheme to be selectively secure when the SHE is semantically secure against CPA and also conduct extensive experiments to validate the scheme's efficacy.
Private set intersection (PSI) evaluation is a well-known secure multiparty computation problem that has received much attention. Authors generally tend to state improved performance as a goal and justification for their proposed PSI schemes. In this paper, we propose an original and new approach to two-party PSI evaluation for small sets that is based on small RSA subgroups. Contrary to previous approaches that at best incur linear communication and computational complexity to the set size, our scheme is the first to achieve constant communication and computational complexity incurring only 2 group elements and 5 exponentiations. An extended PSI scheme handling larger sets is also proposed.
Identity-based encryption with equality test (IBEET) provides an attractive method to test whether two ciphertexts are encryptions of the same plaintext without certificate managements. However, none of the existing IBEET constructions can provide a way to revoke the user in the scenario where the user's private key is compromised or identity gets expired, which is undesirable for identity-based setting. Furthermore, the user cannot revoke the tester when it no longer wants the tester to test its ciphertexts. How to achieve both user and tester revocation in IBEET remains a challenging task. In this paper, we propose a new primitive called revocable identity-based encryption with equality test (R-IBEET), which can solve the aforementioned two problems simultaneously, and formalise the security models of R-IBEET against three types of adversaries. Then we propose a concrete construction of R-IBEET. Our scheme is pairing-free, thus is more efficient compared with the related work.
Blind signature-based (BSB) e-coins are powerful tools that provide anonymity and privacy protection in e-networks. We propose a novel architecture, comprising of a novel voucher-based blind signature scheme and database efficiency algorithm, for BSB e-coins. We find that our architecture reduces the data burden of the double spending detection database of any BSB e-coin system by at least 49.793598% and upwards to a negligible data burden when more ideal deposit patterns are facilitated, and increases BSB e-coin system scalability by causing operational costs per unit of time to increase much slower than growth in the size of the e-coin ecosystem in a growing BSB e-coin network. Our architecture if implemented can immediately reduce the cost of BSB e-coin networks in applications such as anonymised healthcare donor funding networks, anonymised voting, anonymous subscriptions, and ecommerce networks, among many others, and makes large-scale BSB e-coin systems much cheaper and more applicable.
The proliferation of the internet of medical things (IoMT) is proving to be a disruptive technology in contemporary healthcare. However, given the sensitivity of the nature of data being shared in this system security, and privacy are critical issues. Attribute-based encryption is a proactive technique for efficient one-to-many data sharing. Specifically, multi-authority-ciphertext policy-attribute-based encryption (MA-CP-ABE) is a suitable method given the multi-stakeholder ecosystem of IoMT-based healthcare. In this work, conventional MA-CP-ABE techniques have been modified to address several existing security limitations. To the best of our knowledge, the proposed work is first to address fault tolerance in MA-CP-ABE, without any redundancy at attribute authority's level and to develop a mechanism for full and partial revocation of compromised authority. A non-monotonic fully hidden access structure further enhances the security of the scheme while efficiently performing encryption/decryption operations even for a large number of attributes, making it suitable for the secure sharing of IoMT data.
