Collision Attack Research Articles

Inverting Cryptographic Hash Functions via Cube-and-Conquer

MD4 and MD5 are fundamental cryptographic hash functions proposed in the early 1990s. MD4 consists of 48 steps and produces a 128-bit hash given a message of arbitrary finite size. MD5 is a more secure 64-step extension of MD4. Both MD4 and MD5 are vulnerable to practical collision attacks, yet it is still not realistic to invert them, i.e., to find a message given a hash. In 2007, the 39-step version of MD4 was inverted by reducing to SAT and applying a CDCL solver along with the so-called Dobbertin’s constraints. As for MD5, in 2012 its 28-step version was inverted via a CDCL solver for one specified hash without adding any extra constraints. In this study, Cube-and-Conquer (a combination of CDCL and lookahead) is applied to invert step-reduced versions of MD4 and MD5. For this purpose, two algorithms are proposed. The first one generates inverse problems for MD4 by gradually modifying the Dobbertin’s constraints. The second algorithm tries the cubing phase of Cube-and-Conquer with different cutoff thresholds to find the one with the minimum runtime estimate of the conquer phase. This algorithm operates in two modes: (i) estimating the hardness of a given propositional Boolean formula; (ii) incomplete SAT solving of a given satisfiable propositional Boolean formula. While the first algorithm is focused on inverting step-reduced MD4, the second one is not area-specific and is therefore applicable to a variety of classes of hard SAT instances. In this study, 40-, 41-, 42-, and 43-step MD4 are inverted for the first time via the first algorithm and the estimating mode of the second algorithm. Also, 28-step MD5 is inverted for four hashes via the incomplete SAT solving mode of the second algorithm. For three hashes out of them, it is done for the first time.

A Security Analysis of Restricted Syndrome Decoding Problems

Restricted syndrome decoding problems (R-SDP and R-SDP( G )) provide an interesting basis for post-quantum cryptography. Indeed, they feature in CROSS, a submission in the ongoing process for standardizing post-quantum signatures. This work improves our understanding of the security of both problems. Firstly, we propose and implement a novel collision attack on R-SDP( G ) that provides the best attack under realistic restrictions on memory. Secondly, we derive precise complexity estimates for algebraic attacks on R-SDP that are shown to be accurate by our experiments. We note that neither of these improvements threatens the updated parameters of CROSS.

Plaintext-based Side-channel Collision Attack

Side-channel Collision Attacks (SCCA) is a classical method that exploits information dependency leaked during cryptographic operations. Unlike collision attacks that seek instances where two different inputs to a cryptographic algorithm yield identical outputs, SCCAs specifically target the internal state, where identical outputs are more likely. Although SCCA does not rely on the pre-assumption of the leakage model, it explicitly operates on precise trace segments reflecting the target operation, which is challenging to perform when the leakage measurements are noisy. Besides, its attack performance may vary dramatically, as it relies on selecting a reference byte (and its corresponding leakages) to “collide” other bytes. A poor selection would lead to many bytes unrecoverable. These two facts make its real-world application problematic. This paper addresses these challenges by introducing a novel plaintext-based SCCA. We leverage the bijective relationship between plaintext and secret data, using plaintext as labels to train profiling models to depict leakages from varying operations. By comparing the leakage representations produced by the profiling model instead of the leakage segmentation itself, all secret key differences can be revealed simultaneously without processing leakage traces. Furthermore, we propose a novel error correction scheme to rectify false predictions further. Experimental results show that our approach significantly surpasses the state-of-the-art SCCA in both attack performance and computational complexity (e.g., training time reduced from approximately three hours to five minutes). These findings underscore our method's effectiveness and practicality in real-world attack scenarios.

Strict Avalanche Criterion of SHA-256 and Sub-Function-Removed Variants

The measure of diffusion, the property of dissipating patterns and statistical structures in cryptographic transformations, serves as a valuable heuristic for assessing the obscurity of patterns that could lead to collisions. As with many cryptographic hash functions, SHA-256 is thought to exhibit the property of diffusion. While SHA-256’s diffuse output is loosely documented, even less is known about how the diffusion rate changes across the 64 rounds in its compression function and how the algorithm’s individual sub-functions contribute to the overall diffusion. The diffusion of the unmodified compression function is initially measured using the Strict Avalanche Criterion (SAC), with the aim of understanding the alteration in diffusion across the 64 rounds of compression. The level to which sub-functions affect diffusion is subsequently measured, enabling potential prioritization of these sub-functions in future collision attacks. To accomplish this, the compression function is modified by removing sub-functions, and the diffusion of these new variants is measured. While the SAC measurements of each function eventually plateau close to the 50% target, no function, including the unmodified compression function, strictly meets the SAC, and multiple variant functions diffuse at comparatively slower rates.

Improved Quantum Rebound Attacks on Double Block Length Hashing with Round-Reduced AES-256 and ARIA-256

At EUROCRYPT 2020, Hosoyamada and Sasaki proposed the first dedicated quantum collision attacks on hash functions. Their proposal presented a quantum adaptation of the rebound attack and revealed that differential trails, which have too low probability for use in classical settings, might be exploitable in quantum settings. After their work, subsequent research has actively delved into analyzing the security of hash functions in the quantum setting.In this paper, we revisit the quantum rebound attacks on the double block hash function Hirose instantiated with 10-round AES-256 (HCF-AES-256) and 7-round ARIA-256 (HCF-ARIA-256) proposed by Chauhan et al. and Baek et al., respectively. Initially, we identify the flaws in their work and reevaluate the complexity of the attacks. We reveal that the flaws stem from not considering the issue that the S-box differential equation has one solution on average. Earlier research addressed this problem by adding auxiliary bits to the search space. If this method is used to correct the flaws, the resulting time complexities are 217.36 and 220.94 times higher than their proposals. Consequently, in some settings, their attacks become less efficient than generic attacks.Subsequently, we propose improved quantum rebound attacks using nested quantum amplitude amplification and quantum state preparation. Our improved attack efficiently pre-filters the search space, leading to a reduction in overall time complexity. We first classically reduce the search space and employ quantum state preparation to generate a superposition state over the pre-filtered search space. We then use nested quantum amplitude amplification to further reduce the search space quantumly. As a result, we achieve a reduction in the time complexity of the quantum rebound attacks on HCF-AES-256 and HCF-ARIA-256 by factors of 211.2 and 219.5, respectively, making the attacks more efficient than generic attacks again.

Cryptanalysis of Selected ARX-Based Block Ciphers

The security of digital communication and information systems is mostly dependent on block ciphers. ARX-based ciphers are widely used due to their simplicity and efficiency. This paper provides an exhaustive cryptanalysis of a subset of ARX-based block ciphers, with particular emphasis on SIMON, SPECK, and IDEA. These ciphers need to be exposed for their weaknesses in algebraic attack resistance and cryptographic properties such as key sensitivity. In addition, we assess the resource utilization and speed of these ciphers, both of which are critical for practical implementation. SMT (Satisfiability Modulo Theories) framework is utilized to tackle constraint fulfillment problems based on first-order logic. The following cryptographic steps use SMT solvers: differential cryptanalysis, collision attack, pre-image attack, modular root-finding, and cryptographic primitive verification. We show that SMT solvers can solve block cipher cryptanalysis constraints. In a cryptanalytic attack, we convert block cipher boolean equations to Z3py. The proposed cryptanalysis method evaluates ARX cipher performance. This method recovers the partial secret key using plaintext and ciphertext pairs, partial key bits, and a predetermined number of rounds. To determine whether SIMON, SPECK, or IDEA are appropriate for distinct security requirements, we conducted a comparative analysis of the results and presented them in tabulated form. This research builds a better understanding of ARX-based block ciphers and allows us to develop more robust and efficient cryptographic algorithms to protect sensitive data in modern communication systems.

Statistical privacy protection for secure data access control in cloud

Cloud Service Providers (CSPs) allow data owners to migrate their data to resource-rich and powerful cloud servers and provide access to this data by individual users. Some of this data may be highly sensitive and important and CSPs cannot always be trusted to provide secure access. It is also important for end users to protect their identities against malicious authorities and providers, when they access services and data. Attribute-Based Encryption (ABE) is an end-to-end public key encryption mechanism, which provides secure and reliable fine-grained access control over encrypted data using defined policies and constraints. Since, in ABE, users are identified by their attributes and not by their identities, collecting and analyzing attributes may reveal their identities and violate their anonymity. Towards this end, we define a new anonymity model in the context of ABE. We analyze several existing anonymous ABE schemes and identify their vulnerabilities in user authorization and user anonymity protection. Subsequently, we propose a Privacy-Preserving Access Control Scheme (PACS), which supports multi-authority, anonymizes user identity, and is immune against users collusion attacks, authorities collusion attacks and chosen plaintext attacks. We also propose an extension of PACS, called Statistical Privacy-Preserving Access Control Scheme (SPACS), which supports statistical anonymity even if malicious authorities and providers statistically analyze the attributes. Lastly, we show that the efficiency of our scheme is comparable to other existing schemes. Our analysis show that SPACS can successfully protect against Collision Attacks and Chosen Plaintext Attacks.

Edwards curve digital signature algorithm for video integrity verification on blockchain framework

Within the field of forensic science, video integrity is an essential component that ensures the validity and dependability of visual evidence that is essential for court cases. Maintaining the integrity of justice in a time when digital modification tools are easily accessible requires making sure that video recordings are unaltered. Video footage is carefully inspected by forensic analysts who use advanced tools to look for indications of manipulation or change. This paper presents a novel, lightweight approach for verifying the integrity of video data. The proposed method utilizes the blockchain and the Edwards Curve Digital Signature Algorithm, coupled with the BLAKE2b hash function. Signatures are generated for video clips with a predetermined size called video segments and stored in blocks chronologically. The signature of the previous block is stored in the current block to add another layer of security. At the time of validation, these signatures are verified. Experimental results show that the proposed method outperforms state-of-the-art methods in both speed and security. Our method is capable of identifying any type of forgery on any video file, by anyone, at any given moment, with insignificant additional storage requirements. Furthermore, our security analysis shows that our method is resilient against various types of attacks, including collision attacks, key substitution attacks, side-channel attacks, and chosen message attacks. The proposed lightweight video integrity verification method is better suited for use in resource constrained devices.

A Data Sharing Model for Blockchain Trusted Sensor Leveraging Mimic Hash Mechanism

Blockchain, as a distributed trust database, has been widely applied in the field of trustworthy sharing of Internet of Things (IoT) sensor data. A single hash mechanism has achieved, to some extent, the trustworthy on-chain storage of blockchain sensor data, that is, the consistency of data on and off the chain. However, it still faces potential security risks such as collision attacks, short password attacks, and rainbow table attacks. To address this issue, this paper proposes a resiliently secure blockchain sensor data trustworthy sharing model based on a mimic hash mechanism. Specifically, in response to the security risks that may arise from the single hash mechanism, this study innovatively introduces a mimic hash mechanism and proposes two methods for constructing mimic hashes based on Verifiable Random Function (VRF) and Cyber Mimic Defense (CMD) in dedicated Wireless Sensor Networks (WSNs) and open public networks, respectively. Theoretical analysis and experimental results demonstrate that this model effectively solves the problem of trustworthy on-chain storage of sensor data in edge computing environments, enhancing the trustworthiness and security of the data on the chain.

Advanced approaches to prevent ARP attacks

Advanced approaches to prevent ARP attacks

Improved 2-round collision attack on IoT hash standard ASCON-HASH

Lightweight cryptography algorithms are a class of ciphers designed to protect data generated and transmitted by the Internet of Things. They typically have low requirements in terms of storage space and power consumption, and are well-suited for resource-limited application scenarios such as embedded systems, actuators, and sensors. The NIST-approved competition for lightweight cryptography aims to identify lightweight cryptographic algorithms that can serve as standards. Its objective is to enhance data security in various scenarios. Among the chosen standards for lightweight cryptography, ASCON has been selected. ASCON-HASH is a hash function within the ASCON family. This paper presents a detailed analysis of the differential characteristics of ASCON-HASH, utilizing the quadratic S-box. Additionally, we employ message modification techniques and ultimately demonstrate a non-practical collision attack on the 2-round ASCON-HASH, requiring a time complexity of 298 hash function calls.

How to Launch a Powerful Side-Channel Collision Attack?

A cryptographic implementation produces very similar power leakages when fed with the same input. Side-channel collision attacks exploit these similarities to establish the relationship between sub-keys and improve the efficiency of key recovery. Benefiting from independence of leakage model, they play an important role in non-profiled setting. However, performance of existing approaches against single collision value is still sub-optimal and optimization is promising. Motivated by this, we first theoretically analyze the mathematical dependency between the number of collisions and the number of encryptions, and propose an efficient side-channel attack named Collision-Paired Correlation Attack (CPCA) to guarantee that the side with fewer samples in a collision is completely paired in low noise scenario. This allows overcoming the inefficient utilization of information in existing works. Moreover, to further employ underlying informativeness, we maximize collision pairs as many as possible. This optimization significantly improves performance of CPCA and thereby extends it to large noise scenarios. Finally, to achieve moderate computational complexity, two equivalent variants of CPCA are investigated to address the potential problem of limited computing resources. Our further theoretical study illustrates that CPCA provides the upper security bound of Correlation-Enhanced Collision Attack (CECA), and experimental results fully verify its superiority.

Automating Collision Attacks on RIPEMD-160

As an ISO/IEC standard, the hash function RIPEMD-160 has been used to generate the Bitcoin address with SHA-256. However, due to the complex doublebranch structure of RIPEMD-160, the best collision attack only reaches 36 out of 80 steps of RIPEMD-160, and the best semi-free-start (SFS) collision attack only reaches 40 steps. To improve the 36-step collision attack proposed at EUROCRYPT 2023, we explored the possibility of using different message differences to increase the number of attacked steps, and we finally identified one choice allowing a 40-step collision attack. To find the corresponding 40-step differential characteristic, we re-implement the MILP-based method to search for signed differential characteristics with SAT/SMT. As a result, we can find a colliding message pair for 40-step RIPEMD-160 in practical time, which significantly improves the best collision attack on RIPEMD-160. For the best SFS collision attack published at ToSC 2019, we observe that the bottleneck is the probability of the right-branch differential characteristics as they are fully uncontrolled in the message modification. To address this issue, we utilize our SAT/SMT-based tool to search for high-probability differential characteristics for the right branch. Consequently, we can mount successful SFS collision attacks on 41, 42 and 43 steps of RIPEMD-160, thus significantly improving the SFS collision attacks. In addition, we also searched for a 44-step differential characteristic, but the differential probability is too low to allow a meaningful SFS collision attack.

Practical and Malicious Multiparty Private Set Intersection for Small Sets

Private set intersection (PSI) is a pivotal subject in the realm of privacy computation. Numerous research endeavors have concentrated on situations involving vast and imbalanced sets. Nevertheless, there is a scarcity of existing PSI protocols tailored for small sets. Those that exist are either restricted to interactions between two parties or necessitate resource-intensive homomorphic operations. To bring forth practical multiparty private set intersection solutions for small sets, we present two multiparty PSI protocols founded on the principles of Oblivious Key–Value Stores (OKVSs), polynomials, and gabled cuckoo tables. Our security analysis underscores the resilience of these protocols against malicious models and collision attacks. Through experimental evaluations, we establish that, in comparison to related endeavors, our protocols excel in small-set contexts, particularly in low-bandwidth wide area network (WAN) settings.

Restricted near collision attack on Plantlet

Restricted near collision attack on Plantlet

A quantum algorithm for finding collision-inducing disturbance vectors in SHA-1

Modern cryptographic protocols rely on sophisticated hash functions to generate quasi-unique numbers that serve as signatures for user authentication and other security verifications. The security could be compromised by finding texts hash-mappable to identical numbers, forming so-called collision attack. Seeding a disturbance vector in the hash mapping to obtain a successful collision is that a major focus of cryptography study in the past two decades to improve hash protocols. We propose an algorithm that takes advantage of entangled quantum states for concurrent seeding of candidate disturbance vectors, out of which the one entailing collision is selected through a combination of quantum search, phase gating, diffusion gating, and information feedbacks from classical computing machinery. The complexity reduction is shown to be on the order of where n is the number of qubits encoding addresses. We demonstrate the practicality of the proposed by an implementation scheme based on degenerate optical parametric oscillators.

Performance Evaluation of VANET using Directional Location Aided Routing (D-LAR) Protocol with Sleep Scheduling Algorithm

Neighboring radio networks are those that do not instantly supply communications infrastructure after deployment, have radio transceivers with restricted transmission range, and are unaware of possible neighbors. Vehicle-to-vehicle communication is an effective means to convey information through an asymmetric vehicle ad hoc network, and it can provide high security while also reducing energy usage. A new protocol is known as energy efficiency, the D-LAR (Directed Location Assist) protocol, is used to determine a node's energy efficiency. To determine the sleep and active states of nodes, propose a sleep scheduling technique. It can also provide a more accurate location of a moving vehicle than existing location support protocols. In comparison to other current systems, the simulation results suggest that the proposed D-LAR technique has the advantages of decreasing the collision attack detection delay time and enhancing security.

A Novel Cryptographic Technique for Cloud Environment Based on Feedback DNA

Abstract: In the era of cloud computing, ensuring data security is crucial for users and organizations. This paper presents an innovative approach called F-DNAES, which combines DNA cryptography and the Advanced Encryption Standard (AES) algorithm, to enhance data security in cloud-based environments. The proposed methodology focuses on securing data during its transmission and storage in the cloud. By leveraging the unique properties of DNA, such as its storage capacity and stability, along with the robustness of AES encryption, F-DNAES provides a highly secure and efficient solution. The proposed method also ensures the authentication of the Data owners and the users. The F-DNAES model effectively mitigates potential security threats such as phishing attacks, collision attacks, and password guessing attacks. It also offers superior performance in terms of key generation, encryption, and decryption processes. The proposed approach can be applied to various cloud-based scenarios, including IoT infrastructure, web-based applications, and network security. F-DNAES contributes to strengthening data privacy and security, providing users with a trusted and reliable solution in cloud environments.

Search framework for neutral bits and boomerangs in SHA‐1 collision attacks

AbstractNeutral bits and boomerangs are key techniques for accelerating collision search in SHA‐1 attacks. The current acceleration techniques for SHA‐1 near‐collision attacks are reviewed and a generic search framework for neutral bits and boomerangs is presented. The framework can efficiently construct auxiliary paths for a given differential path and message bit relations and find and store ideal boomerangs. The framework was applied to free‐start attacks for 76‐step SHA‐1, and the complexity was reduced from to . Relaxing the boomerang's restrictions on message words, the authors propose an accelerating technique termed semi‐boomerangs, combined with the search framework of boomerangs, which increases the speed of collision search by 3.48 times in a free‐start attack for 80‐step SHA‐1 and the complexity for 80‐step attack was reduced from to .

Revisit two memoryless state‐recovery cryptanalysis methods on A5/1

AbstractAt ASIACRYPT 2019, Zhang proposed a near collision attack on A5/1 claiming to recover the 64‐bit A5/1 state with a time complexity around 232 cipher ticks with negligible memory requirements. Soon after its proposal, Zhang's near collision attack was severely challenged by Derbez et al. who claimed that Zhang's attack cannot have a time complexity lower than Golic's memoryless guess‐and‐determine attack dating back to EUROCRYPT 1997. In this article, both the guess‐and‐determine and the near collision attacks for recovering A5/1 states with negligible memory complexities are studied. Firstly, a new guessing technique called the move guessing technique that can construct linear equation filters in a more efficient manner is proposed. Such a technique can be applied to both guess‐and‐determine and collision attacks for efficiency improvements. Secondly, the filtering strength of the linear equation systems is taken into account for complexity analysis. Such filtering strength are evaluated with practical experiments making the complexities more convincing. Based on such new techniques, the authors are able to give 2 new guess‐and‐determine attacks on A5/1: the 1st attack recovers the internal state with time complexity 243.92; the 2nd one recovers a different state with complexity 243.25. Golic's guess‐and‐determine attack and Zhang's near collision attacks are revisited. According to our detailed analysis, the complexity of Golic's recovery attack is no lower than 246.04, higher than the previously believed 243. On the other hand, Zhang's near collision attack recovers with the time complexity 253.19: such a complexity can be further lowered to 250.78 with our move guessing technique.