Ciphertext Space Research Articles

Design of Privacy Protection System for Target Search Based on Selection Algorithm and Sustainable Iteration Index

The data self-destruct method based on privacy cloud proposed in this paper can realize the automatic destruction of cloud data after expiration, and based on this method, a self-destruct image protection system is implemented. This project intends to combine the adaptive scale invariant Feature conversion (SIFT) extraction of ciphertext images with binary SIFT to ensure the confidentiality of the images uploaded to the server in the ciphertext space. The security protection of data is realized using Paillier homomorphic encryption technology. The feature of SIFT is extracted from the encrypted region, and it is expressed in binary form to reduce the amount of computation and memory overhead. The experimental results show that this method can effectively prevent the automatic destruction of images after expiration, so as to ensure that the user's personal information is not leaked.

Secure Particle Filtering With Paillier Encryption–Decryption Scheme: Application to Multi-Machine Power Grids

This paper is concerned with the encryption-decryption-based state estimation problem for a class of multi-machine power grids with non-Gaussian noises. For the purposes of security enhancement and data privacy protection, the Paillier encryption-decryption scheme is adopted to map the measurement data into the ciphertext space before being transmitted through the communication network. The aim of this paper is to develop a novel secure particle filter algorithm to cope with the nonlinearity/non-Gaussianity from the system plant and the decrypted signals after the measurement transmission. In particular, a modified likelihood function is proposed to obtain the importance weights where the encryption-decryption process of the measurement data is taken into full consideration. The developed algorithm is applied to multi-machine power grids, and it is demonstrated via simulation studies (on three test scenarios of the IEEE 39-bus power system) that our proposed secure state estimation scheme possesses the desired performance index in terms of security and accuracy.

Computing primitive idempotents in finite commutative rings and applications

In this paper, we compute an algebraic decomposition of black-box rings in the generic ring model. More precisely, we explicitly decompose a black-box ring as a direct product of a nilpotent black-box ring and unital local black-box rings, by computing all its primitive idempotents. The algorithm presented in this paper uses quantum subroutines for the computation of the p-power parts of a black-box ring and then classical algorithms for the computation of the corresponding primitive idempotents. As a by-product, we get that the reduction of a black-box ring is also a black-box ring. The first application of this decomposition is an extension of the work of Maurer and Raub (2007) on representation problem in black-box finite fields to the case of reduced p-power black-box rings. Another important application is an IND-CCA1 attack for any ring homomorphic encryption scheme in the generic ring model. Moreover, when the plaintext space is a finite reduced black-box ring, we present a plaintext-recovery attack based on representation problem in black-box prime fields. In particular, if the ciphertext space has smooth characteristic, the plaintext-recovery attack is effectively computable in the generic ring model.

Advancing Federated Learning through Verifiable Computations and Homomorphic Encryption.

Federated learning, as one of the three main technical routes for privacy computing, has been widely studied and applied in both academia and industry. However, malicious nodes may tamper with the algorithm execution process or submit false learning results, which directly affects the performance of federated learning. In addition, learning nodes can easily obtain the global model. In practical applications, we would like to obtain the federated learning results only by the demand side. Unfortunately, no discussion on protecting the privacy of the global model is found in the existing research. As emerging cryptographic tools, the zero-knowledge virtual machine (ZKVM) and homomorphic encryption provide new ideas for the design of federated learning frameworks. We have introduced ZKVM for the first time, creating learning nodes as local computing provers. This provides execution integrity proofs for multi-class machine learning algorithms. Meanwhile, we discuss how to generate verifiable proofs for large-scale machine learning tasks under resource constraints. In addition, we implement the fully homomorphic encryption (FHE) scheme in ZKVM. We encrypt the model weights so that the federated learning nodes always collaborate in the ciphertext space. The real results can be obtained only after the demand side decrypts them using the private key. The innovativeness of this paper is demonstrated in the following aspects: 1. We introduce the ZKVM for the first time, which achieves zero-knowledge proofs (ZKP) for machine learning tasks with multiple classes and arbitrary scales. 2. We encrypt the global model, which protects the model privacy during local computation and transmission. 3. We propose and implement a new federated learning framework. We measure the verification costs under different federated learning rounds on the IRIS dataset. Despite the impact of homomorphic encryption on computational accuracy, the framework proposed in this paper achieves a satisfactory 90% model accuracy. Our framework is highly secure and is expected to further improve the overall efficiency as cryptographic tools continue to evolve.

A unified description of cryptosystems: From classical to quantum protocols

The launch of quantum computing has created new challenges in the field of cryptography. Nowadays this field of research is extremely active in physics, mathematics and computer science. In this paper we present an overview of the most common classical and quantum protocols. The former are usually defined through a 5-uple given by a plaintext space, a ciphertext space, an encryption and decryption space, an encryption function and a decryption function. Here, we show how to unify quantum and classical protocols by using the same formalism of the 5-uple mentioned above.

Construction of Virtual Marketing Interactive Platform for Digital Twin Innovation and Entrepreneurship Based on Blockchain

With the rapid development and application of internet technology, people are gradually entering a state of digital life. However, it is difficult for digital assets to be circulated with a unified standard protocol. Blockchain has the characteristics of decentralization, trustworthiness, and immutability, which can be used to solve the above problems. Although virtual marketing technology shows great potential, as a form of organization that is difficult to manage, there is still a lack of experience in the form factors and operation mechanism of a virtual business model. Therefore, combined with the realistic background, this paper built a digital twin innovation and entrepreneurship virtual marketing interactive platform based on blockchain. The article analyzed the data structure of the blockchain and completed the construction of the platform operation mode. It studied the encryption and decryption process of cryptography and expanded the ciphertext space, then the blockchain is encrypted and decrypted again, and finally, a chi-square analysis is performed. After building the platform, it conducted market research and analyzed the main operating indicators of the A platform on the market. Then, it compared the uncertain string preprocessing enumeration length change and the index occupied space between the platform constructed in this paper and the platform in the literature. The comparison results have shown that the index proposed in this paper is 320 MB in 8 iterative calculations, while the bibliographic index starts at 10000 MB and keeps increasing during the iterative calculation process. The two are not in the same order of magnitude, illustrating the superiority of the platform in this paper.

Implementing efficient attribute encryption in IoV under cloud environments

CP-ABE is a flexible cryptographic algorithm that enables efficient implementation of access control techniques in cloud architectures. However, when CP-ABE is applied to the IoV environment, the weak performance of IoV individuals will inevitably reduce the efficiency of the overall cryptosystem. In addition, various contingencies in IoV require CP-ABE to be able to dynamically respond to various access requests, and generating only a single ciphertext cannot satisfy various additional access requests. In this paper, we propose an encryption algorithm VM-CP-ABE for IoV in cloud environment, which has the features of offline encryption and outsourced decryption. The offline encryption process utilizes the large amount of offline time of individuals in the vehicular network to generate the initial ciphertext segments, while executing its secret sharing process for each offline phase of the ciphertext segments, thus completing the initial combination of ciphertext parameters. The outsourced decryption can generate transformation keys, thus stripping the most complex pairing operations in the decryption process from the weak performing IoV individuals and transferring this part of operations to the more powerful outsourced individuals. In addition, VM-CP-ABE can generate special hierarchical ciphertexts that will have a smaller ciphertext space. And it can avoid the problem of space efficiency due to the high volume of access control policy transfer. We show the static security of all mechanisms of VM-CP-ABE and conclude with a detailed efficiency analysis. VM-CP-ABE is more time- and space-efficient than traditional attribute encryption for extensive sets of IoV attributes in cloud environments.

Hyperelliptic Covers of Different Degree for Elliptic Curves

In elliptic curve cryptography (ECC) and hyperelliptic curve cryptography (HECC), the size of cipher-text space defined by the cardinality of Jacobian is a significant factor to measure the security level. Counting problems on Jacobians of elliptic curve can be solved in polynomial time by Schoof–Elkies–Atkin (SEA) algorithm. However, counting problems on Jacobians of hyperelliptic curves are solved less satisfactorily than those on elliptic curves. So, we consider the construction of the cover map from the hyperelliptic curves to the elliptic curves to convert point counting problems on hyperelliptic curves to those on elliptic curves. We can also use the cover map as a kind of cover attacks. Given an elliptic curve over an extension field of degree n , one might try to use the cover attack to reduce the discrete logarithm problem (DLP) in the group of rational points of the elliptic curve to DLPs in the Jacobian of a curve of genus g ≥ n over the base field. An algorithm has been proposed for finding genus 3 hyperelliptic covers as a cover attack for elliptic curves with cofactor 2. Our algorithms are about the cover map from hyperelliptic curves of genus 2 to elliptic curves of prime order. As an application, an example of an elliptic curve whose order is a 256-bit prime vulnerable to our algorithms is given.

Secure Teleoperation Control Using Somewhat Homomorphic Encryption

The goal of this research is to establish control theoretic methods to enhance cyber security of networked motion control systems by utilizing somewhat homomorphic encryption. The proposed approach will encrypt the entire motion control schemes including: sensor signals, model parameters, feedback gains, and performs computation in the ciphertext space to generate motion commands to servo systems without a security hole. The paper will discuss implementation of encrypted bilateral teleoperation control schemes with nonlinear friction compensation. The paper will present (1) encrypted teleoperation control realization with somewhat homomorphic encryption and (2) simulation results.

Privacy-Preserving Hierarchical State Estimation in Untrustworthy Cloud Environments

Hierarchical state estimation (HSE) is often deployed to evaluate the states of an interconnected power system from telemetered measurements. By HSE, each low-level control center (LCC) takes charge of the estimation of its internal states, whereas a trusted high-level control center (HCC) assumes the coordination of boundary states. However, a trusted HCC may not always exist in practice; a cloud server can take the role of an HCC in case no such facility is available. Since it is prohibited to release sensitive power grid data to untrustworthy cloud environments, considerations need to be given to avoid breaches of LCCs' privacy when outsourcing the coordination tasks to the cloud server. To this end, this article proposes a privacy-preserving HSE framework, which rearranges the regular HSE procedure to integrate a degree-2 variant of the Thresholded Paillier Cryptosystem (D2TPC). Attributed to D2TPC, computations by the cloud-based HCC can be conducted entirely in the ciphertext space. Even if the HCC and some LCCs conspire together to share the information they have, the privacy of non-conspiring LCCs is still assured. Experiments on various scales of test systems demonstrate a high level of accuracy, efficiency, and scalability of the proposed framework.

Lightweight Privacy-Preserving Scheme in Wi-Fi Fingerprint-Based Indoor Localization

Wi-Fi fingerprint-based localization, a common indoor localization technique, plays an important role in the Internet of Things, supporting a number of mobile applications, e.g., navigation indoor, trackingetc. However, Wi-Fi fingerprint-based localization suffers from the privacy issue, disclosing users’ location privacy and the data privacy of localization server (LS). Existing work cannot completely protect LS's data privacy, and moreover, incurs larger amount of computation and communication overhead. In this article, we propose a lightweight privacy-preserving scheme (LWP $^{2}$ ) which protects both location privacy and data privacy with lower cost. The main idea of LWP $^{2}$ is to first formalize the privacy-preserving localization problem as minimizing the least-squared-error for an overdetermined linear formulation, and then design a lightweight solution in ciphertext space using the special structure of the overdetermined linear formulation. Extensive experiments have validated the privacy preservation and the efficiency improvement of LWP $^{2}$ .

Error Amplification in Code-based Cryptography

Code-based cryptography is one of the main techniques enabling cryptographic primitives in a post-quantum scenario. In particular, the MDPC scheme is a basic scheme from which many other schemes have been derived. These schemes rely on iterative decoding in the decryption process and thus have a certain small probability p of having a decryption (decoding) error.In this paper we show a very fundamental and important property of code-based encryption schemes. Given one initial error pattern that fails to decode, the time needed to generate another message that fails to decode is strictly much less than 1/p. We show this by developing a method for fast generation of undecodable error patterns (error pattern chaining), which additionally proves that a measure of closeness in ciphertext space can be exploited through its strong linkage to the difficulty of decoding these messages. Furthermore, if side-channel information is also available (time to decode), then the initial error pattern no longer needs to be given since one can be easily generated in this case.These observations are fundamentally important because they show that a, say, 128- bit encryption scheme is not inherently safe from reaction attacks even if it employs a decoder with a failure rate of 2−128. In fact, unless explicit protective measures are taken, having a failure rate at all – of any magnitude – can pose a security problem because of the error amplification effect of our method.A key-recovery reaction attack was recently shown on the MDPC scheme as well as similar schemes, taking advantage of decoding errors in order to recover the secret key. It was also shown that knowing the number of iterations in the iterative decoding step, which could be received in a timing attack, would also enable and enhance such an attack. In this paper we apply our error pattern chaining method to show how to improve the performance of such reaction attacks in the CPA case. We show that after identifying a single decoding error (or a decoding step taking more time than expected in a timing attack), we can adaptively create new error patterns that have a much higher decoding error probability than for a random error. This leads to a significant improvement of the attack based on decoding errors in the CPA case and it also gives the strongest known attack on MDPC-like schemes, both with and without using side-channel information.

A chaos-based probabilistic block cipher for image encryption

Traditional encryption is based on secrecy provided by secret-key. But this leads to generation of same cipher text when the encryption scheme is applied to same plaintext with same key. Thus, replay of messages can be effortlessly identified by an adversary which can be a weak link in any communication. Probabilistic encryption is an approach to overcome this weakness where different cipher texts are generated each time same plaintext is encrypted using the same key.Extending the probabilistic approach, which is generally employed in asymmetric encryption, this paper proposes a new chaos-based probabilistic symmetric encryption scheme with customizable block-size suitable for image encryption. It employs a Random Bits Insertion phase followed by four rounds of two-staged diffusion involving simple XOR (exclusive-OR) operation making it computationally efficient. Random Bits Insertion makes the scheme probabilistic. This phase also helps in increasing entropy and making intensity distribution more uniform in cipher. The generated cipher text is twice the size of plain text. An increase in cipher text space is inevitable for probabilistic encryption and it provides an advantage as the apparent message space for the attacker is increased. The observations show that the scheme offers high strength to resist statistical and cryptanalytic attacks.

A lightweight and efficient encryption scheme based on LFSR

Privacy and trust in wireless networks have attracted plenty of attention in the information age. Various types of high-complexity encrypt algorithms are exploited for improving the security of the communication, such as providing security in global system for mobile (GSM) communication cell phones. This paper proposes a new algorithm, which combines the Vigenere cipher, linear feedback shift register (LFSR) and one-time pad (OTP) together to reduce the computational complexity and improve the system security. Benefitting from the combination of these advantages, our proposed algorithm makes and attack process more complicated. Particularly, when the Vigenere cipher is expanded to including alphabets, symbols and numbers, it will become safer and more difficult to break just by using frequency or brute force methods, etc. The alphabet entropies of plain and cipher texts are calculated and compared. In addition, the cipher text space is further expanded. The numerical results, obtained through Java programming language, illustrate that the proposed cryptosystem is safer than the conventional Vigenere cipher.

A new code-based encryption scheme and its applications

More and more data has to be dealt with in the current network computing. An extremely efficient encryption algorithm can greatly improve the efficiency and security of the process in large data environment. As a significant candidate of post-quantum cryptosystem, McEliece public-key cryptosystem (PKC) has one remarkable advantage that it has a very fast and efficient encryption process. In this paper, we put forward a new efficient CPA-secure variant of the McEliece cryptosystem whose advantage is that we can enlarge the plain-text space while the cipher-text space unchanged. We formally prove the security of the scheme. Our proof is based on the learning parity with noise (LPN) problem. We also extend our scheme to a CCA-secure cryptosystem and a signcryption.

A new construction on randomized message-locked encryption in the standard model via UCEs

We present a new primitive of randomized message-locked encryption (MLE) in this paper and define a new security model for it. The new primitive, named message-locked encryption3 (hereafter referred as MLE3), is actually a variant of randomized message-locked encryption (Bellare et al. Eurocrypt13). In order to prevent trivial attacks, our primitive admits a semi-trusted server, which is allowed to hold a secret key of public key encryption (PKE), to verify the correctness of a tag. The new security notion, called privacy chosen-distribution attacks3 (PRV-CDA3), requires that a ciphertext generated by encrypting an unpredictable message and another ciphertext (possible invalid) chosen randomly from a ciphertext space are indistinguishable. Compared with the priori proposed security notion, privacy chosen-distribution attacks (PRV-CDA) (Bellare et al. Eurocrypt13), which requires that two ciphertexts generated by encrypting two unpredictable messages are indistinguishable, the security notion we propose is much stronger. Based on the new primitive, under the blackbox reductions, we put forward a novel construction which achieves both privacy chosen-distribution attacks3 (PRV-CDA3) and strong tag consistency (STC) securities in the standard model via universal computational extractors (UCEs) (Bellare et al. Crypto13). In addition, our scheme also provides the validity-testing for ciphertext.

An efficient privacy preserving data aggregation approach for mobile sensing

The advances in sensing capabilities of smartphones give rise to a variety of mobile participatory sensing applications that collect users' personal data. Because of the existence of both sensitive, private personal data, and untrusted aggregator, serious privacy concerns on users arise. Currently, existing privacy preserving data collection methods either require bidirectional communications between an untrusted aggregator and mobile users in every aggregation period, or have high computation or communication overhead. To address these problems, we propose an efficient data aggregation approach by which an untrusted aggregator in mobile sensing can collect the statistics over the data contributed by multiple mobile users, while supporting privacy preservation of each user and data integrity verification. In this approach, information hiding and homomorphic encryption are applied to guarantee the data privacy of mobile users. In detail, a breadth-first search tree is first constructed at the initial phase among the mobile users, and then the original datum of each user is perturbed among its neighbors in ciphertext space by using information hiding and homomorphic encryption. The evaluations of our approach show that our protocol requires lower communication and computation overhead and thus more feasible for the computation constrained mobile devices. Copyright © 2016 John Wiley & Sons, Ltd.

A realizable quantum encryption algorithm for qubits

A realizable quantum encryption algorithm for qubits is presented by employing bit-wise quantum computation. System extension and bit-swapping are introduced into the encryption process, which makes the ciphertext space expanded greatly. The security of the proposed algorithm is analysed in detail and the schematic physical implementation is also provided. It is shown that the algorithm, which can prevent quantum attack strategy as well as classical attack strategy, is effective to protect qubits. Finally, we extend our algorithm to encrypt classical binary bits and quantum entanglements.