Cryptanalysis of a Symmetric Fully Homomorphic Encryption Scheme

Wang, Baocang; Zhang, Yu; Zhang, Zhili

doi:10.1109/tifs.2018.2790916

Cited by 50 publications

(28 citation statements)

References 16 publications

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“…Above all, the computational complexity of our attack algorithm is ( 5 log 2 ). Obviously, it is worse than the complexity (log 4 ) of Wang et al 's attack [17]; however, our attack eliminates the assumption of known plaintext/ciphertext pairs.…”

Section: Complexity Analysismentioning

confidence: 89%

“…Recently, Li et al [16] designed a symmetric homomorphic encryption scheme for outsourced databases that allow multiple data owners to efficiently share their data securely without compromising the privacy of the data. However, Wang et al [17] observed that if some plaintext/ciphertext pairs were succesfully overdropped, one can efficiently recover the corresponding secret key of the scheme from the obtained plaintext/ciphertext pairs.…”

Section: Introductionmentioning

confidence: 99%

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Improved Cryptanalysis of a Fully Homomorphic Symmetric Encryption Scheme

Wang

Ping

2019

Security and Communication Networks

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Homomorphic encryption is widely used in the scenarios of big data and cloud computing for supporting calculations on ciphertexts without leaking plaintexts. Recently, Li et al. designed a symmetric homomorphic encryption scheme for outsourced databases. Wang et al. proposed a successful key-recovery attack on the homomorphic encryption scheme but required the adversary to know some plaintext/ciphertext pairs. In this paper, we propose a new ciphertext-only attack on the symmetric fully homomorphic encryption scheme. Our attack improves the previous Wang et al.’s attack by eliminating the assumption of known plaintext/ciphertext pairs. We show that the secret key of the user can be recovered by running lattice reduction algorithms twice. Experiments show that the attack successfully and efficiently recovers the secret key of the randomly generated instances with an overwhelming probability.

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Section: Complexity Analysismentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Improved Cryptanalysis of a Fully Homomorphic Symmetric Encryption Scheme

Wang

Ping

2019

Security and Communication Networks

Self Cite

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“…• Some symmetric key encryption-based schemes (e.g., [14]) can achieve low pruning time and low communication cost. However, they have a weak threat model, and therefore, they possess poor anti-attack capabilities (as analyzed in [15]). Therefore, we believe that there is a critical need to develop a secure and effective association rules mining scheme on multiowner databases with high-efficiency in a strong threat model.…”

Section: Limitation Of Prior Artmentioning

confidence: 99%

“…No adversary can deduce secret keys with only ciphertexts, thus, the schemes are tight to the only-ciphertext-attack. The scheme is proved to be insecure [15] under the known-plaintext-attack and is breached utilizing only three arbitrary pairs of plaintext/ciphertext owing to some internal logic between its parameters. Thus, the scheme cannot resist the attacks of Type-I (2)(3)(4).…”

Section: Comparison Under the Given Attacksmentioning

confidence: 99%

SecEDMO: Enabling Efficient Data Mining with Strong Privacy Protection in Cloud Computing

Lei

et al. 2022

IEEE Trans. Cloud Comput.

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Frequent itemsets mining and association rules mining are among the top used algorithms in the area of data mining. Secure outsourcing of data mining tasks to the third-party cloud is an effective option for data owners. However, due to the untrust cloud and the distrust between data owners, the traditional algorithms which only work over plaintext should be re-considered to take security and privacy concerns into account. For example, each data owner may not be willing to disclose their own private data to others during the cooperative data mining process. The previous solutions are either not sufficiently secure or not efficient. Therefore, we propose a Secure and Efficient Data Mining Outsourcing (SecEDMO) scheme for secure outsourcing of frequent itemsets mining and association rules mining over the joint database (i.e., database aggregated from multiple data owners) in the paradigm of cloud computing. Based on our customized lightweight symmetric homomorphic encryption algorithm and a secure comparison algorithm, SecEDMO can ensure strong privacy protection and low data mining latency simultaneously. Moreover, the well-designed virtual transaction insertion algorithm can hide the information of the original database while still preserving the cloud's ability to perform data mining over the obfuscated data. By evaluation of a numerical experiment and theoretical comparisons, the correctness, security, and efficiency of SecEDMO are confirmed.

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“…The strength of the cryptographic algorithms depended on the techniques used for managing, establishing and distributing the secret keys. Secret keys that are poorly maintained make the 2 of 21 cryptographic algorithm useless, even if the algorithm is theoretically and also, practically ideal [10,11]. Cryptographic algorithms proposed for IoT networks can be classified into the symmetric and asymmetric algorithms.…”

Section: Introductionmentioning

confidence: 99%

A Secure and Efficient Lightweight Symmetric Encryption Scheme for Transfer of Text Files between Embedded IoT Devices

Shrivastava

Paul

Menon³

et al. 2019

Symmetry

154

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Recent advancements in wireless technology have created an exponential rise in the number of connected devices leading to the internet of things (IoT) revolution. Large amounts of data are captured, processed and transmitted through the network by these embedded devices. Security of the transmitted data is a major area of concern in IoT networks. Numerous encryption algorithms have been proposed in these years to ensure security of transmitted data through the IoT network. Tiny encryption algorithm (TEA) is the most attractive among all, with its lower memory utilization and ease of implementation on both hardware and software scales. But one of the major issues of TEA and its numerous developed versions is the usage of the same key through all rounds of encryption, which yields a reduced security evident from the avalanche effect of the algorithm. Also, the encryption and decryption time for text is high, leading to lower efficiency in IoT networks with embedded devices. This paper proposes a novel tiny symmetric encryption algorithm (NTSA) which provides enhanced security for the transfer of text files through the IoT network by introducing additional key confusions dynamically for each round of encryption. Experiments are carried out to analyze the avalanche effect, encryption and decryption time of NTSA in an IoT network including embedded devices. The results show that the proposed NTSA algorithm is much more secure and efficient compared to state-of-the-art existing encryption algorithms.

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Cryptanalysis of a Symmetric Fully Homomorphic Encryption Scheme

Cited by 50 publications

References 16 publications

Improved Cryptanalysis of a Fully Homomorphic Symmetric Encryption Scheme

Improved Cryptanalysis of a Fully Homomorphic Symmetric Encryption Scheme

SecEDMO: Enabling Efficient Data Mining with Strong Privacy Protection in Cloud Computing

A Secure and Efficient Lightweight Symmetric Encryption Scheme for Transfer of Text Files between Embedded IoT Devices

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