Quantum image encryption algorithm based on bit-plane permutation and sine logistic map

Liu, Xingbin; Xiao, Di; Liu, Cong

doi:10.1007/s11128-020-02739-w

Cited by 31 publications

(22 citation statements)

References 31 publications

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“…Vertical Diagonal Figure 5(a) [11] 0.9744 0.9760 0.9550 EI-Latif [11] -0.0020 -0.0095 -0.0015 Ours 0.0019 0.0101 0.0009 Figure 5(b) [12] 0.5776 0.6725 0.6012 Liu [12] -0.0423 0.0202 -0.0212 Ours -0.0124 0.0168 -0.0130 Figure 5(c) [14] 0.9455 0.9314 0.9148 Hu [14] 0.0062 -0.0217 0.0002 Ours -0.0087 0.0098 0.0030 Figure 5(d) [16] 0.9555 0.9241 0.8990 Abd-EI-Atty [16] -0.0126 0.0002 -0.0047 Ours 0.0031 0.0010 -0.0019 Figure 5(f) [20] 0.9507 0.9281 0.8713 Liu [20] 0.0153 0.0191 0.0055 Ours 0.0058 0.0071 0.0051…”

Section: Horizontalmentioning

confidence: 99%

“…Histogram variance Figure 4(a) 11754.4375 Original Others' Ours Figure 5(b) 65912.5468 [12] 269.3906 [12] 254.8438 Figure 5(f) 34877.968 [20] 243.6953 [20] 239.4871…”

Section: Imagementioning

confidence: 99%

“…Figure 8 also illustrates this conclusion. Table 5 shows comparisons with methods from Liu [12] and Liu [20], and it can be seen that our method has lower var.The pixel values of the encrypted image we obtain are more evenly distributed, making it more difficult for an attacker to decipher.…”

Section: Imagementioning

confidence: 99%

“…Almost all of these methods are designed for traditional digital images, while the encryption of quantum images remains in its infancy. However, as the traditional computer approaches its physical limits, researchers are beginning to study a new computing model, and quantum computers have produced a series of satisfactory encryption results [11][12][13][14][15][16][17][18][19][20][21][22][23][24]. For example, EI-Latif [11] presented an encryption algorithm of quantum medical images.…”

Section: Introductionmentioning

confidence: 99%

“…A Double image encryption using 3D Lorenz chaotic system, 2D nonseparable linear canonical transform and QR decomposition was proposed byRakheja [19]. Liu [20] proposed a quantum image encryption algorithm based on bit-plane permutation and sine logistic map. The current encryption technology for quantum images is divided into three categories: scrambling technology based on the basic gray code and bit plane (GB); scrambling technology based on improved GB; and scrambling technology combined with GB and position.…”

Section: Introductionmentioning

confidence: 99%

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A Quantum Image Encryption Method Based on DNACNot

Zhou

2020

IEEE Access

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The image is one of the most important means to store information, and is widely used in every aspect of life. However, the characteristics of images enable them to be easily stolen, tampered with, and copied. Researchers have proposed many encryption methods, with most applying only to traditional digital images. There are few encryption methods for quantum images, and quantum image-oriented encryption technology has begun to attract researchers' attention. This study proposes a quantum image encryption method based on DNA Controlled-Not (DNACNot). Based on the quantum image information, encryption parameters are obtained and transferred as part of a chaotic initial key. Two natural DNA sequences are amplified to obtain the DNA coordinate sequence, and a modified chaos game representation is used to modify the DNA coordinate sequence, which is then used to correct the sequence generated by chaos. The resulting sequence is converted to an integer sequence to obtain DNACNot. A controlled-not operation is performed between DNACNot and the quantum image is scrambled by bit-plane to obtain the encrypted image. The encryption method has high security, a good encryption effect, and a large key space. The method can effectively resist exhaustive, statistical, and differential attacks. The algorithm is easy to implement at a low cost. The encryption time of our proposed method is satisfactory, and the method is suitable for real-time encryption. Moreover, the encryption results can be transmitted over the internet and stored in the cloud.

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Section: Horizontalmentioning

confidence: 99%

“…Histogram variance Figure 4(a) 11754.4375 Original Others' Ours Figure 5(b) 65912.5468 [12] 269.3906 [12] 254.8438 Figure 5(f) 34877.968 [20] 243.6953 [20] 239.4871…”

Section: Imagementioning

confidence: 99%