{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T12:33:02Z","timestamp":1776774782999,"version":"3.51.2"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,12,10]],"date-time":"2024-12-10T00:00:00Z","timestamp":1733788800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,12,10]],"date-time":"2024-12-10T00:00:00Z","timestamp":1733788800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cybersecurity"],"abstract":"Abstract<\/jats:title>PRESENT is a lightweight block cipher, which has attracted many scholars to research its security. In 2022, Zahednejad et al. proposed the integral neural distinguisher on round-reduced PRESENT. In this paper, a new integral neural distinguisher for PRESENT is constructed. In contrast to Zahednejad\u2019s works, the proposed integral neural distinguisher can improve the number of attack rounds in one round. This paper proposes a new data format ($$invP_{0}^{n},invP_{1}^{n},\\ldots ,invP_{15}^{n},invS_{0}^{n},invS_{1}^{n},\\ldots ,invS_{15}^{n}$$<\/jats:tex-math>\n \n i<\/mml:mi>\n n<\/mml:mi>\n v<\/mml:mi>\n \n P<\/mml:mi>\n \n 0<\/mml:mn>\n <\/mml:mrow>\n n<\/mml:mi>\n <\/mml:msubsup>\n ,<\/mml:mo>\n i<\/mml:mi>\n n<\/mml:mi>\n v<\/mml:mi>\n \n P<\/mml:mi>\n \n 1<\/mml:mn>\n <\/mml:mrow>\n n<\/mml:mi>\n <\/mml:msubsup>\n ,<\/mml:mo>\n \u2026<\/mml:mo>\n ,<\/mml:mo>\n i<\/mml:mi>\n n<\/mml:mi>\n v<\/mml:mi>\n \n P<\/mml:mi>\n \n 15<\/mml:mn>\n <\/mml:mrow>\n n<\/mml:mi>\n <\/mml:msubsup>\n ,<\/mml:mo>\n i<\/mml:mi>\n n<\/mml:mi>\n v<\/mml:mi>\n \n S<\/mml:mi>\n \n 0<\/mml:mn>\n <\/mml:mrow>\n n<\/mml:mi>\n <\/mml:msubsup>\n ,<\/mml:mo>\n i<\/mml:mi>\n n<\/mml:mi>\n v<\/mml:mi>\n \n S<\/mml:mi>\n \n 1<\/mml:mn>\n <\/mml:mrow>\n n<\/mml:mi>\n <\/mml:msubsup>\n ,<\/mml:mo>\n \u2026<\/mml:mo>\n ,<\/mml:mo>\n i<\/mml:mi>\n n<\/mml:mi>\n v<\/mml:mi>\n \n S<\/mml:mi>\n \n 15<\/mml:mn>\n <\/mml:mrow>\n n<\/mml:mi>\n <\/mml:msubsup>\n <\/mml:mrow>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula>), which can exposes more features of PRESENT previous round ciphertext. Simultaneously, this paper incorporates MBConv module into the convolutional layers of DenseNet, which enable the neural network to identify a greater variety of features in ciphertext. The data format of the paper is analysed. The results of the analysis show that the data format in this paper is able to identify more features compared to Zahednejad\u2019s data format. Further to this, experiments are performed on PRESENT using the integral neural distinguisher in this paper. The experimental results show that the changes make to the neural network and data format have improved the accuracy of distinguishers. Finally, key recovery attacks are conducted on the integral neural distinguishers of SmallPresent-(8) to demonstrate the efficacy of the distinguisher proposed in this paper. The results demonstrate that the key recovery success rates for 5-round and 6-round are 98% and 90%, considering error bits within a range of two bits.<\/jats:p>","DOI":"10.1186\/s42400-024-00258-0","type":"journal-article","created":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T23:02:12Z","timestamp":1733785332000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Improved integral neural distinguisher model for lightweight cipher PRESENT"],"prefix":"10.1186","volume":"7","author":[{"given":"Wanqing","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7394-0761","authenticated-orcid":false,"given":"Mingyu","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,10]]},"reference":[{"key":"258_CR1","first-page":"395","volume-title":"Structural cryptanalysis of SASAS","author":"A Biryukov","year":"2001","unstructured":"Biryukov A, Shamir A (2001) Structural cryptanalysis of SASAS. Springer, pp 395\u2013405"},{"key":"258_CR2","first-page":"35","volume-title":"Multiple differential cryptanalysis: theory and practice","author":"C Blondeau","year":"2011","unstructured":"Blondeau C, G\u00e9rard B (2011) Multiple differential cryptanalysis: theory and practice. Springer, pp 35\u201354"},{"key":"258_CR3","first-page":"450","volume-title":"Present: an ultra-lightweight block cipher","author":"A Bogdanov","year":"2007","unstructured":"Bogdanov A et al (2007) Present: an ultra-lightweight block cipher. Springer, pp 450\u2013466"},{"key":"258_CR4","first-page":"310","volume":"2021","author":"Y Chen","year":"2021","unstructured":"Chen Y, Yu H (2021) A new neural distinguisher model considering derived features from multiple ciphertext pairs. IACR Cryptol ePrint Arch 2021:310","journal-title":"IACR Cryptol ePrint Arch"},{"key":"258_CR5","first-page":"302","volume-title":"Linear cryptanalysis of reduced-round present","author":"JY Cho","year":"2010","unstructured":"Cho JY (2010) Linear cryptanalysis of reduced-round present. Springer, pp 302\u2013317"},{"key":"258_CR6","doi-asserted-by":"crossref","unstructured":"Chollet F (2017) Xception: deep learning with depthwise separable convolutions, pp 1251\u20131258","DOI":"10.1109\/CVPR.2017.195"},{"key":"258_CR7","first-page":"195","volume-title":"A statistical saturation attack against the block cipher present","author":"B Collard","year":"2009","unstructured":"Collard B, Standaert F-X (2009) A statistical saturation attack against the block cipher present. Springer, pp 195\u2013210"},{"key":"258_CR8","first-page":"149","volume-title":"The block cipher square","author":"J Daemen","year":"1997","unstructured":"Daemen J, Knudsen L, Rijmen V (1997) The block cipher square. Springer, pp 149\u2013165"},{"key":"258_CR9","first-page":"150","volume-title":"Improving attacks on round-reduced speck32\/64 using deep learning","author":"A Gohr","year":"2019","unstructured":"Gohr A (2019) Improving attacks on round-reduced speck32\/64 using deep learning. Springer, pp 150\u2013179"},{"key":"258_CR10","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"258_CR11","first-page":"131","volume-title":"Linear attack on round-reduced des using deep learning","author":"B Hou","year":"2020","unstructured":"Hou B, Li Y, Zhao H, Wu B (2020) Linear attack on round-reduced des using deep learning. Springer, pp 131\u2013145"},{"key":"258_CR12","doi-asserted-by":"crossref","unstructured":"Howard A et\u00a0al (2019) Searching for mobilenetv3, pp 1314\u20131324","DOI":"10.1109\/ICCV.2019.00140"},{"key":"258_CR13","doi-asserted-by":"crossref","unstructured":"Huang G, Liu Z, Van Der\u00a0Maaten L, Weinberger K\u00a0Q (2017) Densely connected convolutional networks, pp 4700\u20134708","DOI":"10.1109\/CVPR.2017.243"},{"key":"258_CR14","unstructured":"Jain A, Kohli V, Mishra G (2020) Deep learning based differential distinguisher for lightweight cipher present. Cryptology ePrint Archive"},{"key":"258_CR15","first-page":"248","volume-title":"Output prediction attacks on block ciphers using deep learning","author":"H Kimura","year":"2022","unstructured":"Kimura H et al (2022) Output prediction attacks on block ciphers using deep learning. Springer, pp 248\u2013276"},{"key":"258_CR16","first-page":"112","volume-title":"Integral cryptanalysis","author":"L Knudsen","year":"2002","unstructured":"Knudsen L, Wagner D (2002) Integral cryptanalysis. Springer, pp 112\u2013127"},{"key":"258_CR17","unstructured":"Leander G (2010) Small scale variants of the block cipher present. Cryptology ePrint Archive"},{"key":"258_CR18","first-page":"1","volume-title":"The saturation attack\u2013a bait for twofish","author":"S Lucks","year":"2001","unstructured":"Lucks S (2001) The saturation attack\u2013a bait for twofish. Springer, pp 1\u201315"},{"key":"258_CR19","first-page":"58","volume-title":"Linear (hull) and algebraic cryptanalysis of the block cipher present","author":"J Nakahara","year":"2009","unstructured":"Nakahara J, Sepehrdad P, Zhang B, Wang M (2009) Linear (hull) and algebraic cryptanalysis of the block cipher present. Springer, pp 58\u201375"},{"key":"258_CR20","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","volume":"27","author":"CE Shannon","year":"1948","unstructured":"Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379\u2013423","journal-title":"Bell Syst Tech J"},{"key":"258_CR21","unstructured":"Tan M, Le Q (2019) Efficientnet: rethinking model scaling for convolutional neural networks, pp 6105\u20136114 (PMLR)"},{"key":"258_CR22","doi-asserted-by":"crossref","unstructured":"Tan M et\u00a0al (2019) Mnasnet: platform-aware neural architecture search for mobile, pp 2820\u20132828","DOI":"10.1109\/CVPR.2019.00293"},{"key":"258_CR23","first-page":"287","volume-title":"Structural evaluation by generalized integral property","author":"Y Todo","year":"2015","unstructured":"Todo Y (2015) Structural evaluation by generalized integral property. Springer, pp 287\u2013314"},{"key":"258_CR24","first-page":"19","volume-title":"Compact representation for division property","author":"Y Todo","year":"2016","unstructured":"Todo Y, Morii M (2016) Compact representation for division property. Springer, pp 19\u201335"},{"key":"258_CR25","first-page":"40","volume-title":"Differential cryptanalysis of reduced-round present","author":"M Wang","year":"2008","unstructured":"Wang M (2008) Differential cryptanalysis of reduced-round present. Springer, pp 40\u201349"},{"key":"258_CR26","first-page":"163","volume-title":"Improved integral attacks on present-80","author":"S Wang","year":"2018","unstructured":"Wang S, Xiang Z, Zeng X, Zhang S (2018) Improved integral attacks on present-80. Springer, pp 163\u2013182"},{"key":"258_CR27","first-page":"331","volume-title":"Integral attacks on reduced-round present","author":"S Wu","year":"2013","unstructured":"Wu S, Wang M (2013) Integral attacks on reduced-round present. Springer, pp 331\u2013345"},{"key":"258_CR28","first-page":"648","volume-title":"Applying MILP method to searching integral distinguishers based on division property for 6 lightweight block ciphers","author":"Z Xiang","year":"2016","unstructured":"Xiang Z, Zhang W, Bao Z, Lin D (2016) Applying MILP method to searching integral distinguishers based on division property for 6 lightweight block ciphers. Springer, pp 648\u2013678"},{"key":"258_CR29","doi-asserted-by":"crossref","unstructured":"Xie S, Girshick R, Doll\u00e1r P, Tu Z, He K (2017) Aggregated residual transformations for deep neural networks, pp 1492\u20131500","DOI":"10.1109\/CVPR.2017.634"},{"key":"258_CR30","first-page":"379","volume-title":"Side channel cube attack on present","author":"L Yang","year":"2009","unstructured":"Yang L, Wang M, Qiao S (2009) Side channel cube attack on present. Springer, pp 379\u2013391"},{"key":"258_CR31","first-page":"363","volume-title":"Bit-pattern based integral attack","author":"MR Z\u2019aba","year":"2008","unstructured":"Z\u2019aba MR, Raddum H, Henricksen M, Dawson E (2008) Bit-pattern based integral attack. Springer, pp 363\u2013381"},{"key":"258_CR32","doi-asserted-by":"publisher","first-page":"7584","DOI":"10.1002\/int.22895","volume":"37","author":"B Zahednejad","year":"2022","unstructured":"Zahednejad B, Lyu L (2022) An improved integral distinguisher scheme based on neural networks. Int J Intell Syst 37:7584\u20137613","journal-title":"Int J Intell Syst"}],"container-title":["Cybersecurity"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s42400-024-00258-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s42400-024-00258-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s42400-024-00258-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,10]],"date-time":"2024-12-10T00:03:03Z","timestamp":1733788983000},"score":1,"resource":{"primary":{"URL":"https:\/\/cybersecurity.springeropen.com\/articles\/10.1186\/s42400-024-00258-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,10]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["258"],"URL":"https:\/\/doi.org\/10.1186\/s42400-024-00258-0","relation":{},"ISSN":["2523-3246"],"issn-type":[{"value":"2523-3246","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,10]]},"assertion":[{"value":"4 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 May 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 December 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"65"}}