On the morality of teaching students IT crime skills

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Abstract

A superficial introduction to the world of viruses, worms and other malware is often sufficient to get students dreaming about the potential power wielded by those technologies. One needs about a minute to teach them how to build a powerful Trojan Horse, how to distribute such a construction as targeted malware and how to monetise the few minutes they invested in such an effort. Such teaching is rewarding since it is one of the few examples where many students immediately apply their new skills to impress friends. Of course the intention is not to make them criminals, but to gain the deep understanding of issues that would otherwise require them to spent hours with books that discuss abstract concepts that often remains abstract. The question is whether computing educator should ever even consider teaching students skills that may be abused in this manner. In this paper I argue that knowledge to harm and knowledge to help overlap in many professional contexts. The lecture argues questions on the morally of imparting potentially malicious knowledge should differentiate between imparting it to those entering a profession and imparting it to the masses. While this does not prevent the professional from abusing knowledge, it is argued that the benefit to society will outweigh the harm. In the non-professional context little benefit is likely to accrue to society, but opportunistic abuse of knowledge already acquired is significantly more probable than the possibility of someone purposefully acquiring and abusing such knowledge. However, even more important than professionalism is the sense of community. It is argued that meaningful professional communities that are able to use harmful knowledge responsibly are rare in computing. Hence care should be exercised when potentially harmful information is to be taught and self-censorship ought to be exercised in general.

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Olivier, M. S. (2016). On the morality of teaching students IT crime skills. In Communications in Computer and Information Science (Vol. 642, pp. 3–21). Springer Verlag. https://doi.org/10.1007/978-3-319-47680-3_1

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