deepexplore:深度学习系统的自动白盒测试

GetMobile Mob. Comput. Commun. Pub Date : 2019-01-17 DOI:10.1145/3308755.3308767

Kexin Pei, Yinzhi Cao, Junfeng Yang, S. Jana

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引用次数: 20

摘要

在过去的几年里，深度学习(DL)取得了巨大的进步，在各种任务上达到或超过了人类的水平，包括图像分类、语音识别和围棋等游戏。这些进步已经导致深度学习在安全和安全关键系统中的广泛采用和部署，例如自动驾驶汽车、恶意软件检测和飞机防撞系统。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

DeepXplore: Automated Whitebox Testing of Deep Learning Systems

Over the past few years, Deep Learning (DL) has made tremendous progress, achieving or surpassing human-level performance for a diverse set of tasks, including image classification, speech recognition, and playing games like Go. These advances have led to widespread adoption and deployment of DL in security- and safety-critical systems, such as selfdriving cars, malware detection, and aircraft collision avoidance systems.

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来源期刊

GetMobile Mob. Comput. Commun.

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