Introduction to Modern Cryptography
Abstract
Cryptography plays a key role in ensuring the privacy and integrity of data and the security of computer networks. Introduction to Modern Cryptography provides a rigorous yet accessible treatment of modern cryptography, with a focus on formal definitions, precise assumptions, and rigorous proofs.The authors introduce the core principles of
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The target function in cryptanalytic search problems is usually modeled as a pseudo-random function or a cryptographic hash function.
“The target function in cryptanalytic search problems is usually modeled as a pseudo-random function (PRF) or a cryptographic hash function (CHF).The precise interpretation of this notions can be found in Sects.3.5 and 5.5 of [30].”
From Time–space complexity of quantum search algorithms in symmetric cryptanalysis: applying to AES and SHA-2 (2018) · cites this paper as [30]
If k samples are independently selected out of 2^{2s-2} DPs, the probability of at least one coincidence is approximated by p_BP(k)=1-exp(-k^2/(2•2^{2s-2})).
“p BP (2 2s-2 ) (k) = 1 -exp -k 2 2 • 2 2s-2 .”
From Time–space complexity of quantum search algorithms in symmetric cryptanalysis: applying to AES and SHA-2 (2018) · cites this paper as [30]
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Chatterjee, U., Govindan, V., Sadhukhan, R., Mukhopadhyay, D., Chakraborty, R. S., Mahata, D., & Prabhu, M. M. (2019) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2018.2832201 · Cited by 290 · see citing works
Status report on the third round of the NIST Post-Quantum Cryptography Standardization process
Alagic, G., Apon, D., Cooper, D., Dang, Q., Dang, T., Kelsey, J., Lichtinger, J., Liu, Y.-K., Miller, C., Moody, D., et al. (2022) · doi:10.6028/nist.ir.8413-upd1 · Cited by 301 · see citing works
DNA origami cryptography for secure communication
Zhang, Y., Wang, F., Chao, J., Xie, M., Liu, H., Pan, M., Kopperger, E., Liu, X., Li, Q., Shi, J., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-13517-3 · Cited by 163 · see citing works
Deriving genomic diagnoses without revealing patient genomes
Jagadeesh, K. A., Wu, D. J., Birgmeier, J. A., Boneh, D., & Bejerano, G. (2017) · Science · doi:10.1126/science.aam9710 · Cited by 134 · see citing works
Kim, P., Han, D., & Jeong, K. C. (2018) · Quantum Information Processing · doi:10.1007/s11128-018-2107-3 · Cited by 80 · see citing works
Coutinho, M., De Oliveira Albuquerque, R., Borges, F., García Villalba, L., & Kim, T.-H. (2018) · Sensors · doi:10.3390/s18051306 · Cited by 75 · see citing works
(LABGET) Laboratory, L. T. T. U., Saidi, R., Bentahar, T., (LABGET) Laboratory, L. T. T. U., Cherrid, N., Electronic Department, M. B. B.-2. U., Bentahar, A., (LAMIS) Laboratory, L. T. T. U., Mayache, H., & Higher School of Industrial Technologies-Annaba, A.-2. (2020) · International Journal on Electrical Engineering and Informatics · doi:10.15676/ijeei.2020.12.4.13 · Cited by 4 · see citing works
On Cryptographic Mechanisms for the Selective Disclosure of Verifiable Credentials
Flamini, A., Sciarretta, G., Scuro, M., Sharif, A., Tomasi, A., & Ranise, S. (2024) · arXiv · Cited by 24 · see citing works
- Authors
- Katz, J., & Lindell, Y.
- Venue
- Chapman & Hall/CRC eBooks
- Publisher
- Chapman and Hall/CRC
- Published
- 2007-08-31
- OpenAlex
- W4300349690
- Cited by
- 1,238
- References
- 0
- Citations by year
- 2026: 34 · 2025: 65 · 2024: 101 · 2023: 94 · 2022: 102 · 2021: 73 · 2020: 79 · 2019: 88 · 2018: 78 · 2017: 84 · 2016: 76 · 2015: 86 · 2014: 60 · 2013: 74 · 2012: 64
- FWCI
- 3.35
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Chapman & Hall/CRC eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Physical Sciences › Computer Science › Artificial Intelligence › Coding theory and cryptography
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptographic Implementations and Security
- Keywords
- modern cryptography, data privacy, data integrity, network security, formal definitions, cryptographic assumptions, rigorous proof
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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