{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T11:14:38Z","timestamp":1769166878347,"version":"3.49.0"},"reference-count":13,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["No. 830892"],"award-info":[{"award-number":["No. 830892"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["AI Ethics"],"published-print":{"date-parts":[[2022,11]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Artificial intelligence (AI) has found a myriad of applications in many domains of technology, and more importantly, in improving people\u2019s lives. Sadly, AI solutions have already been utilized for various violations and theft, even receiving the name AI or Crime (AIC). This poses a challenge: are cybersecurity experts thus justified to attack malicious AI algorithms, methods and systems as well, to stop them? Would that be fair and ethical? Furthermore, AI and machine learning algorithms are prone to be fooled or misled by the so-called adversarial attacks. However, adversarial attacks could be used by cybersecurity experts to stop the criminals using AI, and tamper with their systems. The paper argues that this kind of attacks could be named Ethical Adversarial Attacks (EAA), and if used fairly, within the regulations and legal frameworks, they would prove to be a valuable aid in the fight against cybercrime.<\/jats:p>","DOI":"10.1007\/s43681-021-00113-9","type":"journal-article","created":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T13:05:40Z","timestamp":1635253540000},"page":"631-634","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["The double-edged sword of AI: Ethical Adversarial Attacks to counter artificial intelligence for crime"],"prefix":"10.1007","volume":"2","author":[{"given":"Micha\u0142","family":"Chora\u015b","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Micha\u0142","family":"Wo\u017aniak","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,26]]},"reference":[{"key":"113_CR1","doi-asserted-by":"publisher","unstructured":"Aleksandra P, Micha\u0142 C, Marek P, Rafa\u0142 Kozik (2021) A $10 million question and other cybersecurity-related ethical dilemmas amid the COVID-19 pandemic. Bus Horiz 64(6):729-734 ISSN 0007-6813. https:\/\/doi.org\/10.1016\/j.bushor.2021.07.010https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0007681321001336","DOI":"10.1016\/j.bushor.2021.07.010"},{"issue":"1","key":"113_CR2","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1186\/s40163-020-00123-8","volume":"9","author":"M Caldwell","year":"2020","unstructured":"Caldwell, M., Andrews, J.T.A., Tanay, T., Griffin, L.D.: AI-enabled future crime. Crime Sci. 9(1), 14 (2020). https:\/\/doi.org\/10.1186\/s40163-020-00123-8","journal-title":"Crime Sci."},{"key":"113_CR3","unstructured":"Chakraborty A, Alam M, Dey V, Chattopadhyay A, Mukhopadhyay D (2018) Adversarial attacks and defences: a survey. arXiv:1810.00069"},{"key":"113_CR4","doi-asserted-by":"publisher","unstructured":"Chora\u015b M, Pawlicki M, Kozik R (2019) The feasibility of deep learning use for adversarial model extraction in the cybersecurity domain. 353\u2013360. https:\/\/doi.org\/10.1007\/978-3-030-33617-2_36","DOI":"10.1007\/978-3-030-33617-2_36"},{"issue":"1","key":"113_CR5","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1109\/MITP.2015.3","volume":"17","author":"S Earley","year":"2015","unstructured":"Earley, S.: Analytics, machine learning, and the internet of things. IT Prof. 17(1), 10\u201313 (2015). https:\/\/doi.org\/10.1109\/MITP.2015.3","journal-title":"IT Prof."},{"issue":"4","key":"113_CR6","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1109\/MITP.2020.3005640","volume":"22","author":"F Gossen","year":"2020","unstructured":"Gossen, F., Margaria, T., Steffen, B.: Towards explainability in machine learning: the formal methods way. IT Prof. 22(4), 8\u201312 (2020). https:\/\/doi.org\/10.1109\/MITP.2020.3005640","journal-title":"IT Prof."},{"issue":"1","key":"113_CR7","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1007\/s11948-018-00081-0","volume":"26","author":"TC King","year":"2020","unstructured":"King, T.C., Aggarwal, N., Taddeo, M., Floridi, L.: Artificial intelligence crime: an interdisciplinary analysis of foreseeable threats and solutions. Sci. Eng. Ethics 26(1), 89\u2013120 (2020). https:\/\/doi.org\/10.1007\/s11948-018-00081-0","journal-title":"Sci. Eng. Ethics"},{"issue":"6","key":"113_CR8","doi-asserted-by":"publisher","first-page":"1893","DOI":"10.1109\/JBHI.2014.2344095","volume":"19","author":"M Mozaffari-Kermani","year":"2015","unstructured":"Mozaffari-Kermani, M., Sur-Kolay, S., Raghunathan, A., Jha, N.K.: Systematic poisoning attacks on and defenses for machine learning in healthcare. IEEE J. Biomed. Health Inform. 19(6), 1893\u20131905 (2015). https:\/\/doi.org\/10.1109\/JBHI.2014.2344095","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"113_CR9","doi-asserted-by":"publisher","DOI":"10.1007\/s00779-020-01510-3","author":"A Pawlicka","year":"2021","unstructured":"Pawlicka, A., Chora\u015b, M., Kozik, R., Pawlicki, M.: First broad and systematic horizon scanning campaign and study to detect societal and ethical dilemmas and emerging issues spanning over cybersecurity solutions. Personal Ubiquitous Comput. (2021). https:\/\/doi.org\/10.1007\/s00779-020-01510-3","journal-title":"Personal Ubiquitous Comput."},{"key":"113_CR10","doi-asserted-by":"publisher","unstructured":"Pawlicka, A., Chora\u015b, M., Pawlicki, M., Kozik, R.: A $10 million question and other cybersecurity-related ethical dilemmas amid the COVID-19 pandemic. Bus Horiz. 64(6),  729\u2013734 (2021b). https:\/\/doi.org\/10.1016\/j.bushor.2021.07.010","DOI":"10.1016\/j.bushor.2021.07.010"},{"key":"113_CR11","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.future.2020.04.013","volume":"110","author":"M Pawlicki","year":"2020","unstructured":"Pawlicki, M., Chora\u015b, M., Kozik, R.: Defending network intrusion detection systems against adversarial evasion attacks. Futur. Gener. Comput. Syst. 110, 148\u2013154 (2020). https:\/\/doi.org\/10.1016\/j.future.2020.04.013","journal-title":"Futur. Gener. Comput. Syst."},{"key":"113_CR12","doi-asserted-by":"publisher","first-page":"667","DOI":"10.1007\/978-981-13-7403-6_58","volume-title":"Emerging Technology in Modelling and Graphics","author":"H Shekhar","year":"2020","unstructured":"Shekhar, H., Seal, S., Kedia, S., Guha, A.: Survey on applications of machine learning in the field of computer vision. In: Mandal, J.K., Bhattacharya, D. (eds.) Emerging Technology in Modelling and Graphics, pp. 667\u2013678. Springer Singapore, Singapore (2020)"},{"issue":"6404","key":"113_CR13","doi-asserted-by":"publisher","first-page":"751","DOI":"10.1126\/science.aat5991","volume":"361","author":"M Taddeo","year":"2018","unstructured":"Taddeo, M., Floridi, L.: How AI can be a force for good. Science 361(6404), 751\u2013752 (2018). https:\/\/doi.org\/10.1126\/science.aat5991","journal-title":"Science"}],"container-title":["AI and Ethics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s43681-021-00113-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s43681-021-00113-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s43681-021-00113-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T08:37:31Z","timestamp":1667378251000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s43681-021-00113-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,26]]},"references-count":13,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,11]]}},"alternative-id":["113"],"URL":"https:\/\/doi.org\/10.1007\/s43681-021-00113-9","relation":{},"ISSN":["2730-5953","2730-5961"],"issn-type":[{"value":"2730-5953","type":"print"},{"value":"2730-5961","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,26]]},"assertion":[{"value":"25 June 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 October 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}