Contemporary digital systems are increasingly designed to manipulate, “nudge” and “direct” users into performing actions they might not otherwise make. These manipulative and deceptive tendencies are called –“dark patterns'' – are “user interface design choices that benefit an online service by coercing, steering, or deceiving users into making unintended and potentially harmful decisions''. Dark patterns exploit users’ psychological characteristics against them, to distract, deceive, harm, or overtly coerce users into performing actions or decisions that are beneficial to a digital service’s owner. Today, dark patterns are implemented in digital systems with unprecedented sophistication and are extremely prevalent: 95% of mobile apps more than 10% of global shopping websites contain at least one dark pattern, and the 200 most popular apps and websites in the EU contain at least one dark pattern according to EU Commission report. Dark patterns are present in many different digital contexts—impacting users in e-commerce, health, social media, games, as well as on multiple devices (on the Web, mobile apps, IoT devices and augmented/virtual reality). As a consequence, dark patterns practices expose users to a multitude of harms — financial loss, invasion of privacy, loss of autonomy, psychological harm, and collective harm — resulting in the subverted individual’s autonomy and decision-making, which confirms that harm is a constituent element of dark patterns in addition to behavioral manipulation in general. Dark patterns have also been demonstrated to alter and manipulate user behavior and may be even more harmful to certain user groups, such as children and the elderly, according to the EU and US regulators. Dark patterns have recently become a new field of transdisciplinary research—initially introduced in the area of Human-Computer Interaction (HCI) and design, it has been extended to law, computer science, economics, and psychology. The response to dark patterns has evolved from theoretical problem-based academic work and behavioral studies to active enforcement by regulatory bodies worldwide. A recent systematic review of dark patterns has identified 79 academic papers across fields including HCI, but also the computer science field of security and privacy, game studies, and law. Moreover, in our recent joint work, we have grouped 245 definitions of dark patterns from 10 different taxonomies into a preliminary ontology with only 64 (6 high-level, 24 meso-level, and 34 low-level) patterns, with the aim to provide a consistent and shared vocabulary for regulators, scholars, and industry to better communicate about dark patterns practices. In order to protect users from manipulation, deception, and harms caused by dark patterns in digital systems, the TULIP project aims at advancing the knowledge about the cognitive mechanisms used by dark patterns, developing new methods for automatic detection of dark patterns across contexts and tools to help regulators collect evidence of dark patterns. To achieve these ambitious goals, in this project we will advance the research in dark patterns from three dimensions: legal (Cristiana Santos), human-computer interaction (Colin Gray) and computer science (Nataliia Bielova and a 4th PI). Our research will address conceptual and methodological aspects (defining and understanding varieties and cognitive mechanisms of dark patterns), technical aspects (large-scale automatic detection of dark patterns across digital contexts and devices and expert-oriented tools, such as browser extensions) and legal aspects (interpretation and application of regulatory and legal frameworks applicable to dark patterns, as well as evidence collection for regulators).