活动简介
This year’s program seeks to highlight challenges to privacy posed by widespread adoption of machine learning and artificial intelligence technologies. One motivation for this focus stems from goals and provisions of the European General Data Protection Regulation (GDPR), including requirements for privacy and data protection by design, providing notices and information about the logic of automated decision-making, and emphasis on privacy management and accountability structures in organizations that process personal data. Interpreting and operationalizing these requirements for systems that employ machine learning and artificial intelligence technologies is a daunting task.
As engineering is asked to play a larger role in privacy governance, software developers need tools for understanding, systematizing, and embedding privacy into systems and workflows. This work also requires greater engagement with design, legal, and public policy departments. Methods and tools for bridging privacy work across these communities are essential to success. Furthermore, research that focuses on techniques and tools that can aid the translation of legal and normative concepts into systems requirements are of great value.
Organizations also need tools for systematically evaluating whether systems fulfill users’ privacy needs and requirements and for providing necessary technical assurances. Methods that can support organizations and engineers in developing (socio-)technical systems that address these requirements is of increasing value to respond to the existing societal challenges associated with privacy.
征稿信息
重要日期
征稿范围
Topics of interests include, but are not limited to:
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Integrating law and policy compliance into the development process
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Privacy or data protection impact assessments in the engineering context
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Privacy engineering and data driven software development
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Privacy engineering and machine learning
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Privacy engineering and artificial intelligence
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Privacy engineering and data subject access rights
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Privacy risk management models
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Privacy breach recovery methods
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Privacy engineering and data portability
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Technical standards, heuristics and best practices for privacy engineering
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Privacy engineering in technical standards
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Privacy requirements elicitation and analysis methods
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User privacy and data protection requirements
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Management of privacy requirements with other system requirements
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Privacy requirements elicitation and analysis techniques
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Privacy design patterns
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Privacy-preserving architectures
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Privacy engineering and databases, services and the cloud
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Privacy engineering in networks
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Engineering techniques for fairness, transparency, and privacy in databases
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Privacy engineering in the context of interaction design and usability
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Privacy testing and evaluation methods
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Validation and verification of privacy requirements
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Privacy Engineering and design
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Engineering Privacy Enhancing Technologies (PETs)
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Integration of PETs into systems or the development ecosystem
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Models and approaches for the verification of privacy properties
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Tools and formal languages supporting privacy engineering
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Usable privacy for developers
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Teaching and training privacy engineering
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Adaptations of privacy engineering into specific software development processes
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Pilots and real-world applications
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Evaluation of privacy engineering methods, technologies and tools
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Privacy engineering and accountability
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Privacy engineering and business processes
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Privacy engineering and manageability of data in (large) enterprises
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Organizational, legal, political and economic aspects of privacy engineering
全部留言
重要日期
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04月27日
2018
会议日期
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01月12日 2018
摘要截稿日期
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01月19日 2018
初稿截稿日期
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02月05日 2018
初稿录用通知日期
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02月23日 2018
终稿截稿日期
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04月27日 2018
注册截止日期
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