Cristel Pelsser

Rémi Van Boxem, Tom Barbette, Cristel Pelsser et al.

Automated bots now account for roughly half of all web requests, and an increasing number deliberately spoof their identity to either evade detection or to not respect robots.txt. Existing countermeasures are either resource-intensive (JavaScript challenges, CAPTCHAs), cost-prohibitive (commercial solutions), or degrade the user experience. This paper proposes a lightweight, passive approach to bot detection that combines user-agent string analysis with favicon-based heuristics, operating entirely on standard web server logs with no client-side interaction. We evaluate the method on over 4.6 million requests containing 54,945 unique user-agent strings collected from website hosted all around the earth. Our approach detects 67.7% of bot traffic while maintaining a false-positive rate of 3%, outperforming state of the art (less than 20%). This method can serve as a first line of defence, routing only genuinely ambiguous requests to active challenges and preserving the experience of legitimate users.

Loïc Miller, Pascal Mérindol, Antoine Gallais et al.

Data leaks and breaches are on the rise. They result in huge losses of money for businesses like the movie industry, as well as a loss of user privacy for businesses dealing with user data like the pharmaceutical industry. Preventing data exposures is challenging, because the causes for such events are various, ranging from hacking to misconfigured databases. Alongside the surge in data exposures, the recent rise of microservices as a paradigm brings the need to not only secure traffic at the border of the network, but also internally, pressing the adoption of new security models such as zero-trust to secure business processes. Business processes can be modeled as workflows, where the owner of the data at risk interacts with contractors to realize a sequence of tasks on this data. In this paper, we show how those workflows can be enforced while preventing data exposure. Following the principles of zero-trust, we develop an infrastructure using the isolation provided by a microservice architecture, to enforce owner policy. We show that our infrastructure is resilient to the set of attacks considered in our security model. We implement a simple, yet realistic, workflow with our infrastructure in a publicly available proof of concept. We then verify that the specified policy is correctly enforced by testing the deployment for policy violations, and estimate the overhead cost of authorization.