|09:15-10:15||Keynote: Lea Kissner (Humu)
Building for trust, building with respect
In the past years, we have seen a wide range of products fail because they were not built with sufficient respect for users' wishes, their privacy, or their security. Sometimes this happened because a system did not work as designed, but very often these failures happened when the system did work as designed. For companies, this has meant everything from minor PR embarrassments to complete product shutdowns and regulatory and legal consequences; for the people affected, the consequences were typically far more severe.
In order to gain the trust of users, we need to build products with respect at their core. That both means good design and follow-through in both the squishy human aspects and the hard-core systems aspects; they must work together repeatedly in a harmonious, predictable whole. This talk works through real-life patterns which lead to these better systems and outlines lines of research which can directly improve the lives of users (including your own).
|10:45-11:35||SESSION 1 - Privacy Risk Modeling and Assessment
-Laurens Sion, Dimitri Van Landuyt, Kim Wuyts and Wouter Joosen: Privacy Risk Assessment for Data Subject-aware Threat Modeling
-Ali Kassem, Gergely Acs, Claude Castelluccia and Catuscia Palamidessi: Differential Inference Testing: A Practical Approach to Evaluate Sanitization Techniques
-Kim Wuyts, Laurens Sion, Dimitri Van Landuyt and Wouter Joosen: Knowledge is Power: Systematic Reuse of Privacy Knowledge for Threat Elicitation
|11:35-12:25||SESSION 2 - Implementing Privacy
-Tavish Vaidya and Micah Sherr: You Talk too Much: Limiting Privacy Exposure via Voice Input
-Takahito Sakamoto and Masahiro Matsunaga: After GDPR, Still Tracking or Not? Understanding Opt-Out States for Online Behavioral Advertising
-Ala'A Al-Momani, Frank Kargl, Robert Schmidt, Antonio Kung and Christoph Bösch: A Privacy-Aware V-Model for Software Development
|12:25-12:30||Best paper award|
|13:30-14:30||Keynote: Carmela Troncoso (EPFL)
Privacy technologies need to go to the gym: on the challenges of privacy engineering in an Agile world
Privacy by Design concept was hailed as a main vehicle to build systems that inherently address privacy concerns in the late 2000s. Since then, a number of methods and guidelines have been proposed to translate its core principles into actionable elements that can be digested by software engineers (e.g., requirements engineering, design patterns, or technological components). Such methods find their roots in either policy recommendations or practices by privacy researchers. As a result, they consider systems design as a structured process in which requirements, design, deployment, and maintenance can be executed sequentially and are fully under the control of the system developers in a single organization. Thus, most proposed principles and practices assume that privacy considerations established at the onset of the process will trickle through the product lifecycle resulting in privacy-preserving solutions.
However, the reality of system designers nowadays is very different. In most industries, the systems development cycle is not anymore a monolithic cycle, but a combination of small cycles in which requirements, environments, and objectives may change in an agile manner. Furthermore, the software supply chain is no longer internal to organizations or limited to one-to-one relationships between developers and suppliers. Instead, developers rely on cloud environments where microservices are offered by a number of (platform) actors whose goals and privacy requirements may be very different from those of the system under development.
In this talk we will explore the challenges that such an ever-changing modularized software environment poses for privacy engineering. Concretely, will discuss how the field of privacy engineering and privacy enhancing technologies can cope with composition of microservices and agile software practices, as well as with the need to integrate and compose privacy technologies into larger systems.
|14:30-15:15||SESSION 3 - Secure Input, Output and Computation
-Asma Aloufi and Peizhao Hu: Collaborative Homomorphic Computation on Data Encrypted under Multiple Keys
-Shengbao Zheng, Zhenyu Zhou, Heyi Tang and Xiaowei Yang: SwitchMan: An Easy-to-Use Approach to Secure User Input and Output
|15:45-17:00||Panel: Engineering Privacy with Distributed Machine Learning
Luca Melis (Amazon)
Payman Mohassel (Facebook)
Daniel Ramage (Google Research)
Ryan Rogers (LinkedIn)
Abhradeep Thakurta (UC Santa Cruz)