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Detecting Cyberattacks Using Linguistic Analysis

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Advances in Human Factors in Robots, Unmanned Systems and Cybersecurity (AHFE 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 268))

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Abstract

Increasingly, computer users throughout the world are faced with various types of cyberattacks that might originate anywhere. In many cases, for example with ransomware, the unsuspecting user might receive a message requesting a payment of funds lest some dire consequence occur. The nature of such a message may lead to an analysis of the origin of the attack, based on the use of language in the demand. For example, if the targeted user is English-speaking, the language in the attack might have been originated by a speaker of another language, who might use human translation or machine translation in the attack. In this paper, we explore the possibility of determining in part the source of an attack through linguistic analysis of sample test messages that might have been translated by human or machine methods, and from one of a range of human languages.

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References

  1. Patterson, W., Murray, A., Fleming, L.: Distinguishing a human or machine cyberattacker. In: Ahram, T., Karwowski, W., Vergnano, A., Leali, F., Taiar, R. (eds.) IHSI 2020. AISC, vol. 1131, pp. 335–340. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-39512-4_53

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  2. https://en.m.wikipedia.org/wiki/List_of_languages_by_number_of_native_speakers

  3. https://en.wikipedia.org/wiki/Levenshtein_distance

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© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Patterson, W. (2021). Detecting Cyberattacks Using Linguistic Analysis. In: Zallio, M., Raymundo Ibañez, C., Hernandez, J.H. (eds) Advances in Human Factors in Robots, Unmanned Systems and Cybersecurity. AHFE 2021. Lecture Notes in Networks and Systems, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-030-79997-7_21

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