黑客(Hacker,台湾译作「骇客」)广义上指在计算机科学,编程以及设计领域有高度理解力的人。 然而,人们通常对黑客一词的理解都是取其狭义的涵义,即信息安全领域的黑客: 未经许可入侵他人系统并窃取数据信息等的可以视为 黑帽黑客,也可取侩客 cracker 的涵义。
而主要从事安全检测,系统调试,技术研究的安全从业者可称为 白帽黑客
还有一种存在称为「脚本小子」,往往冒充黑客也常被人误认为是「黑客」,其实是利用一些现有的工具或者程序达到入侵或破解等目的,然而其知识储备以及对技术的理解力却完全不符合广义黑客的标准,甚至不及狭义黑客标准。

最新论文

Diverse promising datasets have been designed to hold back the development of fake audio detection, such as ASVspoof databases. However, previous datasets ignore an attacking situation, in which the hacker hides some small fake clips in real speech audio. This poses a serious threat since that it is difficult to distinguish the small fake clip from the whole speech utterance. Therefore, this paper develops such a dataset for half-truth audio detection (HAD). Partially fake audio in the HAD dataset involves only changing a few words in an utterance.The audio of the words is generated with the very latest state-of-the-art speech synthesis technology. We can not only detect fake uttrances but also localize manipulated regions in a speech using this dataset. Some benchmark results are presented on this dataset. The results show that partially fake audio presents much more challenging than fully fake audio for fake audio detection.

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