Chosen Plaintext Attack Research Articles

A quantum resistant multi-user signcryption scheme featuring key invisibility for Internet of Things

With the advent of ubiquitous computing, multiple heterogeneous devices have evolved with increased connectivity, yielding the Internet of Things (IoT). For establishing secure communication, IoT has effectively become a primary security concern. The massive connectivity of the resource-constrained devices in IoT and enormous data on the air have made information vulnerable to several types of attacks. Although several resource-intensive cryptographic algorithms have been proposed to combat this security threat, signcryption has been identified as a sound solution for such an application.In this work, we propose an isogeny-based signcryption scheme by integrating HyPKE, an isogeny-based encryption scheme with an isogeny-based signature SeaSign based on Fiat Shamir with aborts. Apart from confidentiality and authenticity requirements, our scheme also achieves ciphertext anonymity and key invisibility, unlike the existing signcryption schemes in the post-quantum world. More positively, our security model considers insider attacks, supports multi-users setting and offers non-repudiation. Our work also studies the key privacy notion of the isogeny-based encryption scheme Hashed-PKE, which can be of independent interest in designing several anonymous channels or privacy-preserving protocols. More precisely, we showed Hashed-PKE achieves indistinguishability of keys against chosen-plaintext attack. This leads to the indistinguishability of keys against chosen-ciphertext attack security of HyPKE, a hybrid encryption scheme that is obtained by applying the Fujisaki Okamoto transformation to Hashed-PKE. We have proved our result in the standard model assuming the hardness of the Commutative Supersingular Decisional Diffie–Hellman assumption.

A hyperchaotic image encryption algorithm based on LSTM neural network and lifting wavelet transform

In order to solve the problems of simple permutation-diffusion structure, low encryption efficiency and small chaos range of existing chaotic systems, this paper proposes a hyperchaotic image encryption algorithm based on LSTM neural network and lifting wavelet transform. By building upon the Lorenz chaotic system, we construct a new hyperchaotic system in this paper, which has more complex dynamic characteristics and higher Lyapunov exponent. Then, the image is encrypted by lifting wavelet transform and zigzag conversion algorithm. Finally, the trained LSTM neural network is used to process the Henon chaotic sequence to obtain the second key for encryption, which can effectively resist chosen-plaintext attack. The experimental findings indicate that the proposed encryption algorithm has good performance in key security, differential attack, statistical analysis and operation efficiency, which indicates that the algorithm has high security.

Cryptanalyzing an image cipher using multiple chaos and DNA operations

Recently, an improved color image cipher (ICIC-DNA) based on multiple deoxyribonucleic acid (DNA) sequence operations with DNA synthetic image and chaos was proposed. ICIC-DNA features the use of multiple chaotic systems and diverse DNA operations. However, after our careful cryptanalysis, we found that ICIC-DNA has several fatal security flaws. First, despite the use of multiple chaotic systems, the corresponding encryption sequences are independent of the plaintext, such that equivalent keys exist. Second, the diverse DNA operation is essentially a 2-bit data substitution process, and thus can be equivalently simplified. Third, ICIC-DNA includes substitution and permutation of DNA domains, and based on the equivalent simplification operation, the substitution and permutation can be attacked separately. Based on these, we propose a chosen-plaintext attack method to attack ICIC-DNA. Differential analysis is firstly adopted to break the DNA-base permutation process, and then the DNA domain encryption is eliminated, and finally the equivalent key is used to achieve complete cracking. Theoretical analysis and experimental results show that the proposed attack method is effective and has low computational complexity and data complexity.

Improved diffractive-imaging based image encryption scheme in 3D space

In this paper, we present an improved diffractive-imaging-based image encryption scheme in 3D space. In this cryptosystem, the plaintext is divided into several sub-images by binary amplitude masks and then diffused into 3D space at different axial positions for encryption, which confuses the relation between the plaintext and the ciphertext to make the chosen-plaintext attack no longer work. For the decryption, we develop a modified iterative retrieval algorithm to retrieve a decrypted image with high quality. Additionally, this cryptosystem obtains higher security without increasing the amount of the ciphertext. Compared with previous diffractive-imaging-based image encryption schemes, the key space is enlarged so greatly that this cryptosystem can resist the brute force attack. Furthermore, this scheme can significantly reduce the computation and retrieve a decrypted image with high-quality.

Multiple-Valued Plaintext-Checking Side-Channel Attacks on Post-Quantum KEMs

In this paper, we present a side-channel analysis (SCA) on key encapsulation mechanisms (KEMs) based on the Fujisaki–Okamoto (FO) transformation and its variants. Many post-quantum KEMs usually perform re-encryption during key decapsulation to achieve chosen-ciphertext attack (CCA) security. The side-channel leakage of re-encryption can be exploited to mount a key-recovery plaintext-checking attack (KR-PCA), even if the chosen-plaintext attack (CCA) secure decryption constructing the KEM is securely implemented. Herein, we propose an efficient side-channel-assisted KR-PCA on post-quantum KEMs, and achieve a key recovery with significantly fewer attack traces than existing ones in TCHES 2022 and 2023. The basic concept of the proposed attack is to introduce a new KR-PCA based on a multiple-valued (MV-)PC oracle and then implement a dedicated MV-PC oracle based on a multi-classification neural network (NN). The proposed attack is applicable to the NIST PQC selected algorithm Kyber and the similar lattice-based Saber, FrodoKEM and NTRU Prime, as well as SIKE. We also present how to realize a sufficiently reliable MV-PC oracle from NN model outputs that are not 100% accurate, and analyze the tradeoff between the key recovery success rate and the number of attack traces. We assess the feasibility of the proposed attack through attack experiments on three typical symmetric primitives to instantiate a random oracle (SHAKE, SHA3, and AES software). The proposed attack reduces the number of attack traces required for a reliable key recovery by up to 87% compared to the existing attacks against Kyber and other lattice-based KEMs, under the condition of 99.9999% success rate for key recovery. The proposed attack can also reduce the number of attack traces by 85% for SIKE.

Dap-FL: Federated Learning Flourishes by Adaptive Tuning and Secure Aggregation

Federated learning (FL), an attractive and promising distributed machine learning paradigm, has sparked extensive interest in exploiting tremendous data stored on ubiquitous mobile devices. However, conventional FL suffers severely from resource heterogeneity, as clients with weak computational and communication capabilities may be unable to complete local training using the same local training hyper-parameters. In this paper, we propose Dap-FL, a deep deterministic policy gradient (DDPG)-assisted adaptive FL system, in which local learning rates and local training epochs are adaptively adjusted by all resource-heterogeneous clients through locally deployed DDPG-assisted adaptive hyper-parameter selection schemes. Particularly, the rationality of the proposed hyper-parameter selection scheme is confirmed through rigorous mathematical proof. Besides, due to the thoughtlessness of security consideration of adaptive FL systems in previous studies, we introduce the Paillier cryptosystem to aggregate local models in a secure and privacy-preserving manner. Rigorous analyses show that the proposed Dap-FL system could protect clients' private local models against chosen-plaintext attacks and chosen-message attacks in a widely used honest-but-curious participants and active adversaries security model. More importantly, through ingenious and extensive experiments, the proposed Dap-FL achieves higher model prediction accuracy than two state-of-the-art RL-assisted FL methods, i.e., 6.03% higher than DDPG-based FL and 7.85% higher than DQN-based FL. In addition, experimental results also show that the proposed Dap-FL achieves higher global model prediction accuracy and faster convergence rates than conventional FL, and the comprehensiveness of the adjusted local training hyper-parameters is validated.

Redactable Blockchain-Enabled Hierarchical Access Control Framework for Data Sharing in Electronic Medical Records

The application of blockchain to data sharing in an untrusted environment has received widespread industry attention in recent years. However, the tamper-proof property of blockchain brings protection for sharing data and also leads to a new limitation for the deletion of malicious data. Nowadays, many methods based on redactable blockchain with a chameleon hash is proposed to attempt to solve the above problem, but loss of effective access control to the modifiers can easily lead to breaking the positive characteristics of the blockchain. To address the aforementioned problem, a hierarchical access control redactable blockchain model for data sharing through attribute-based encryption and a chameleon hash is introduced. Under this model, the data owner can specify who can modify their data by setting an access policy and authenticating the modifier with a digital signature. The data owner's full control over rights is guaranteed, while the modifier's behavior is regulated. In addition, the hierarchical access control decentralized technique solves the overpowerful problem of center authority and single-point-of-failure problems in the existing works. The security analysis indicates that the proposed scheme achieves indistinguishable chosen plaintext attack security as well as collision resistance security. Performance analysis shows that the proposed scheme is more complete and has better efficiency compared with other schemes.

Toward Efficient Homomorphic Encryption for Outsourced Databases through Parallel Caching

Many applications deployed to public clouds are concerned about the confidentiality of their outsourced data, such as financial services and electronic patient records. A plausible solution to this problem is homomorphic encryption (HE), which supports certain algebraic operations directly over the ciphertexts. The downside of HE schemes is their significant, if not prohibitive, performance overhead for data-intensive workloads that are very common for outsourced databases, or database-as-a-serve in cloud computing. The objective of this work is to mitigate the performance overhead incurred by the HE module in outsourced databases. To that end, this paper proposes a radix-based parallel caching optimization for accelerating the performance of homomorphic encryption (HE) of outsourced databases in cloud computing. The key insight of the proposed optimization is caching selected radix-ciphertexts in parallel without violating existing security guarantees of the primitive/base HE scheme. We design the radix HE algorithm and apply it to both batch- and incremental-HE schemes; we demonstrate the security of those radix-based HE schemes by showing that the problem of breaking them can be reduced to the problem of breaking their base HE schemes that are known IND-CPA (i.e. Indistinguishability under Chosen-Plaintext Attack). We implement the radix-based schemes as middleware of a 10-node Cassandra cluster on CloudLab; experiments on six workloads show that the proposed caching can boost state-of-the-art HE schemes, such as Paillier and Symmetria, by up to five orders of magnitude.

Coordinated-security based on probabilistic shaping and encryption in MMW-RoF system.

A coordinated-security probabilistic shaping (PS) physical layer encryption scheme is proposed for a W-band millimeter-wave radio-over-fiber (MMW-RoF) system. This scheme mainly includes substituting encryption, coordinated encrypted PS, and unequal length grouping scrambling, which can realize the coordination between PS and chaotic encryption. The key space of the proposed scheme is 10103, which can effectively prevent against brute force cracking and chosen-plaintext attacks. The encrypted orthogonal frequency division multiplexing (OFDM) signal is successfully transmitted over 50-km standard single-mode fiber (SSMF) and a 5-m wireless channel. The results show that the proposed scheme achieves 0.8-dB received optical power gain at a bit error rate (BER) of 10-3 compared with a traditional OFDM signal. The superiority of the proposed scheme in security performance and BER performance has been verified.

A novel image compression and encryption scheme based on conservative chaotic system and DNA method

An image compression encryption scheme on the strength of a conservative chaotic map, compressed sensing (CS) and DNA method is proposed. Built on the hash algorithm, a novel algorithm for generating the initial state of the chaotic map is designed, which makes the algorithm resistant to chosen-plaintext and known-plaintext attacks. The pseudo-random sequences which are produced by the conservative chaotic map are devoted to constructing the measurement matrix of CS and control the encoding and operation mode of DNA, which improves the complexity of the cryptosystem. In addition, a novel Integrated Cyclic Crossover and Mutation algorithm (ICCM) based on DNA method is proposed. ICCM simultaneously completes the scrambling and diffusion of images based on the loop structure, which greatly enhances the security of the algorithm. Experimental results and a number of security analyses demonstrate that the scheme has excellent performance and robustness, and has good resistance to various attacks.

Security analysis of a chaotic encryption algorithm related to the sum of plaintext pixel value

The security analysis of the existing chaotic image encryption algorithm is mainly for the algorithm whose secret keys are independent of plaintext, while a few cryptanalyses on plaintext-related scheme are released. This paper analyzes the security of a chaotic encryption algorithm related to the sum of plaintext pixel value (SPPV). It is found that for all plaintexts with the same SPPV, the chaotic sequences used for encryption are identical. Accordingly, there exist a series of equivalent keys corresponding to the different SPPVs, a codebook attack method to crack this type of encryption algorithm is proposed. Since the SPPV is predictable, limited in number and reconfigurable, the chosen-plaintext attack is adopted to analyze the plaintext with all possible SPPVs. And the corresponding equivalent keys are calculated, respectively. These equivalent keys corresponding to SPPV finally form a complete codebook for cracking the original encryption scheme. The research result shows that any encryption algorithm related to SPPV can be cracked by the codebook attack method proposed in this paper. Therefore, the method proposed in this paper owns certain universal applicability. Theoretical analysis and experimental results prove the feasibility of this method.

A Blockchain-Based Efficient and Verifiable Attribute-Based Proxy Re-Encryption Cloud Sharing Scheme

When choosing a third-party cloud storage platform, the confidentiality of data should be the primary concern. To address the issue of one-to-many access control during data sharing, it is important to encrypt data with an access policy that enables fine-grained access. The attribute-based encryption scheme can be used for this purpose. Additionally, attribute-based proxy re-encryption (ABPRE) can generate a secret key using the delegatee’s secret key and access policy to re-encrypt the ciphertext, allowing for one-to-many data sharing. However, this scheme still has some flaws, such as low efficiency, inability to update access rules, and private data leakage. To address these issues, we proposed a scheme that combines attribute-based encryption (ABE) and identity-based encryption (IBE) to achieve efficient data sharing and data correctness verification. We also integrated this scheme with blockchain technology to ensure tamper-proof and regulated data storage, addressing issues such as data tampering and lack of supervision on third-party servers. Finally, to demonstrate the security of our scheme, we evaluated the communication overhead and computation overhead. Our results showed that our scheme is more efficient than other schemes and is secure against chosen plaintext attacks with verifiable properties.

Learning asymmetric encryption using adversarial neural networks

We propose a multi-agent adversarial neural networks model where a sender (Alice) and a receiver (Bob) are able to learn to use a pair of public/private keys in order to protect their communication from one or more attackers/eavesdroppers. Existing work in the field required shared symmetric information between Alice and Bob before initiating the training process. To the best of our knowledge, this is the first work in which Alice and Bob with asymmetric information can train themselves to protect their communication. Our initial model setup contains five agents: sender Alice, receiver Bob, eavesdropper Eve and two neural networks (we call them public keys generator and private keys generator) that, based on a (secret) random noise from Bob, will generate a pair of public/private keys that allows Alice to encrypt a message with the public key and Bob to decrypt the message with the private key while preventing Eve from decrypting the secret message using the public key. We show that the neural networks are able to establish a communication and secure it from Eve. Finally, we consider adversaries stronger than Eve to model leakage attacks, chosen plaintext attacks (CPA) and test the distinguishability between ciphertexts. The last three experiments show that neural networks (with asymmetric information) can secure the communication providing stronger security guarantees and resilience to leakage attacks which may include leakage from the private key.

A Role-Based Encryption (RBE) Scheme for Securing Outsourced Cloud Data in a Multi-Organization Context

Role-Based Encryption (RBE) is an emerging new technique that integrates role based access control (RBAC) model with encryption. RBE embeds RBAC access policies in encrypted data itself so that only users belonging to appropriate roles are able to decrypt and access the data. However, the existing RBE schemes have been focusing on the single-organization cloud storage system, where the stored data can be accessed by users of the same organization. This paper presents a novel RBE scheme with efficient user revocation for the multi-organization cloud storage system, where the data from multiple independent organizations are stored and can be accessed by the authorized users from any other organization. Additionally, an outsourced decryption mechanism is introduced which enables the users to delegate expensive cryptographic operations to the cloud, thereby reducing the overhead on the end-users. Security and performance analyses of the proposed scheme demonstrate that it is provably secure against Chosen Plaintext Attack and can be useful for practical applications due to its low computation overhead.

Quantum Related-Key Attack Based on Simon’s Algorithm and Its Applications

With the development of quantum technology, quantum computing has an increasingly significant impact on cryptanalysis. Several quantum algorithms, such as Simon’s algorithm, Grover’s algorithm, the Bernstein–Vazirani algorithm, Shor’s algorithm, and the Grover-meets-Simon algorithm, have been proposed successively. However, almost all cryptanalysis is based on the quantum chosen-plaintext attack (qCPA) model. This paper focuses on a powerful cryptanalytic model, quantum related-key attack (qRKA), and proposes a strategy of qRKAs against symmetric ciphers using Simon’s algorithm. We construct a periodic function to efficiently recover the secret key of symmetric ciphers if the attacked symmetric ciphers satisfy Simon’s promise, and present the complexity analysis on specific symmetric ciphers. Then, we apply qRKA to the Even–Mansour cipher and SoEM construction, recover their secret keys, and show their complexity comparison in the distinct attack models. This work is of great significance for the qRKA cryptanalysis of existing provably secure cryptographic schemes and the design of future quantum secure cryptographic schemes.

Access control scheme based on blockchain and attribute-based searchable encryption in cloud environment

With the rapid development of cloud computing technology, how to achieve secure access to cloud data has become a current research hotspot. Attribute-based encryption technology provides the feasibility to achieve the above goal. However, most of the existing solutions have high computational and trust costs. Furthermore, the fairness of access authorization and the security of data search can be difficult to guarantee. To address these issues, we propose a novel access control scheme based on blockchain and attribute-based searchable encryption in cloud environment. The proposed scheme achieves fine-grained access control with low computation consumption by implementing proxy encryption and decryption, while supporting policy hiding and attribute revocation. The encrypted file is stored in the IPFS and the metadata ciphertext is stored on the blockchain, which ensures data integrity and confidentiality. Simultaneously, the scheme enables the secure search of ciphertext keyword in an open and transparent blockchain environment. Additionally, an audit contract is designed to constrain user access behavior to dynamically manage access authorization. Security analysis proves that our scheme is resistant to chosen-plaintext attacks and keyword-guessing attacks. Theoretical analysis and experimental results show that our scheme has high computational and storage efficiency, which is more advantageous than other schemes.

A traceable and revocable multi-authority attribute-based access control scheme for mineral industry data secure storage in blockchain

With the rapid advancements of the mineral industry, the data generated by this industry chain have increased dramatically. To reduce the growing pressure of data storage and security risks, we design a credible on-chain and off-chain collaborative dual storage system that integrates blockchain technology and Interplanetary file system (IPFS), also construct a traceable and revocable multi-authority ciphertext-policy attributed-based encryption (CP-ABE) algorithm to meet the demand of privacy protection and dynamic fine-grained access control. Furthermore, the multi-authority layered authorization with a central authority model distributes system overhead while enabling the platform can be regulated. More importantly, our scheme achieves accurate trace of the malicious users by white-box traceability and capable of implementing indirect immediate user and attribute revocation without requiring key or ciphertext updates. Finally, the proposed scheme is indistinguishably secure under chosen-plaintext attack (IND-CPA) in the standard model. And the performance analysis demonstrates that our scheme is feature-rich, practical and efficient.

Side-channel attacks on CRYSTALS-KYBER, countermeasures and comparison with SKELYA (DSTU 8961-2019)

Although the mathematical problems used in post-quantum cryptography algorithms appear to be mathematically secure, a class of attacks known as side-channel attacks may prove to be a threat to the security of such algorithms. Side-channel attacks affect the hardware on which the cryptographic algorithm runs, they are not attacks on the algorithm itself.
 The good news is that side-channel analysis on new post-quantum cryptographic algorithms started early, even before the algorithms were standardized, given that older algorithms still face side-channel problems.
 Kyber is a lattice-based post-quantum algorithm based on the complexity of the M-LWE problem. Kyber offers a secure public key encryption (PKE) scheme against a chosen plaintext attack (CPA) and a secure key encapsulation mechanism against a chosen ciphertext attack (CCA).
 This paper provides a study of side-channel and fault-injection attacks on lattice-based schemes, with focus on the Kyber (KEM).
 Considering the wide range of known attacks, the protection of the algorithm requires the implementation of individual countermeasures. The paper presents and tests a number of countermeasures capable of providing/improving protection against existing SCA/FIA for Kyber KEM.
 The obtained results show that the presented countermeasures incur a reasonable performance cost. Therefore, the use of special countermeasures in real implementations of lattice-based schemes, either alone or as an augmentation of general countermeasures, is necessary.

Optical-cryptographic scheme based on an image self-disordering algorithm.

This paper demonstrates a novel optical-cryptographic system based on a new image self-disordering algorithm (ISDA). The cryptographic stage is based on an iterative procedure using an ordering sequence from the input data to produce diffusion and confusion keys. Our system uses this approach over plaintext and optical cipher from a 2f-coherent processor working with two random phase masks. Since the keys used for encryption depend on the initial input information, the system is resistant to common attacks such as the chosen-plaintext attack (CPA) and the known-plaintext attack (KPA). In addition, since the ISDA operates the optical cipher, the 2f processor linearity is destroyed, producing an enhanced ciphertext in phase and amplitude, improving optical encryption protection. This new approach offers higher security and efficiency than other reported systems. We perform security analyses and validate the feasibility of this proposal by synthesizing an experimental keystream and performing color image encryption.

An IND-CPA Analysis of a Cryptosystem Based on Bivariate Polynomial Reconstruction Problem

The Polynomial Reconstruction Problem (PRP) was introduced in 1999 as a new hard problem in post-quantum cryptography. Augot and Finiasz were the first to design a cryptographic system based on a univariate PRP, which was published at Eurocrypt 2003 and was broken in 2004. In 2013, a bivariate PRP was proposed. The design is a modified version of Augot and Finiasz’s design. Our strategic method, comprising the modified Berlekamp–Welch algorithm and Coron strategies, allowed us to obtain certain secret parameters of the bivariate PRP. This finding resulted in us concluding that the bivariate PRP is not secure against Indistinguishable Chosen-Plaintext Attack (IND-CPA).