Secure Deep Learning Engineering: A Road Towards Quality Assurance of Intelligent Systems

Yang Liu, Lei Ma, Jianjun Zhao

研究成果: 著書/レポートタイプへの貢献会議での発言

抜粋

Over the past decades, deep learning (DL) systems have achieved tremendous success and gained great popularity in various applications, such as intelligent machines, image processing, speech processing, and medical diagnostics. Deep neural networks are the key driving force behind its recent success, but still seem to be a magic black box lacking interpretability and understanding. This brings up many open safety and security issues with enormous and urgent demands on rigorous methodologies and engineering practice for quality enhancement. A plethora of studies have shown that state-of-the-art DL systems suffer from defects and vulnerabilities that can lead to severe loss and tragedies, especially when applied to real-world safety-critical applications. In this paper, we perform a large-scale study and construct a paper repository of 223 relevant works to the quality assurance, security, and interpretation of deep learning. Based on this, we, from a software quality assurance perspective, pinpoint challenges and future opportunities to facilitate drawing the attention of the software engineering community towards addressing the pressing industrial demand of secure intelligent systems.

元の言語英語
ホスト出版物のタイトルFormal Methods and Software Engineering - 21st International Conference on Formal Engineering Methods, ICFEM 2019, Proceedings
編集者Yamine Ait-Ameur, Shengchao Qin
出版者Springer
ページ3-15
ページ数13
ISBN(印刷物)9783030324087
DOI
出版物ステータス出版済み - 1 1 2019
イベント21st International Conference on Formal Engineering Methods, ICFEM 2019 - Shenzhen, 中国
継続期間: 11 5 201911 9 2019

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11852 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

会議

会議21st International Conference on Formal Engineering Methods, ICFEM 2019
中国
Shenzhen
期間11/5/1911/9/19

    フィンガープリント

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

これを引用

Liu, Y., Ma, L., & Zhao, J. (2019). Secure Deep Learning Engineering: A Road Towards Quality Assurance of Intelligent Systems. : Y. Ait-Ameur, & S. Qin (版), Formal Methods and Software Engineering - 21st International Conference on Formal Engineering Methods, ICFEM 2019, Proceedings (pp. 3-15). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 11852 LNCS). Springer. https://doi.org/10.1007/978-3-030-32409-4_1