The paper presents a practical application of the crowdsensing idea to measure human mobility and signal coverage in cellular networks. Currently, virtually everyone is carrying a mobile phone, which may be used as a sensor to gather research data by measuring, e.g., human mobility and radio signal levels. However, many users are unwilling to participate in crowdsensing experiments. This work begins with the analysis of the barriers for engaging people in crowdsensing. A survey showed that people who agree to participate in crowdsensing expect a minimum impact on their battery lifetime and phone usage habits. To address these requirements, this paper proposes an application for measuring the location and signal strength data based on energy-efficient GPS tracking, which allows one to perform the measurements of human mobility and radio signal levels with minimum energy utilization and without any engagement of the user. The method described combines measurements from the accelerometer with effective management of the GPS to monitor the user mobility with the decrease in battery lifetime by approximately 20%. To show the applicability of the proposed platform, the sample results of signal level distribution and coverage maps gathered for an LTE network and representing human mobility are shown.

A 2.3Tbps DDoS attack was recently mitigated by Amazon, which is a new record after the 2018 GitHub attack, or the famous 2016 Dyn DNS attack launched from hundreds of thousands of hijacked Internet of Things (IoT) devices. These attacks may disrupt the lives of billions of people worldwide, as we increasingly rely on the Internet. In this paper, we tackle the problem that hijacked IoT devices are often the origin of these attacks. With the goal of protecting the Internet and local networks, we propose Autopolicy: a system that automatically limits the IP traffic bandwidth—and other network resources—available to IoT devices in a particular network. We make use of the fact that devices, such as sensors, cameras, and smart home appliances, rarely need their high-speed network interfaces for normal operation. We present a simple yet flexible architecture for Autopolicy, specifying its functional blocks, message sequences, and general operation in a Software Defined Network. We present the experimental validation results, and release a prototype open source implementation.

The Internet is a critical resource in the daily life of billions of users. To support the growing number of users and their increasing demands, operators continuously scale their network footprint---e.g., by joining Internet Exchange Points (IXPs)---and adopt relevant technologies---such as IPv6---which provides a vastly larger address space than its predecessor. In this paper, we revisit prefix de-aggregation attacks in the light of these two changes and introduce Kirin---an advanced BGP prefix de-aggregation attack that announces millions of IPv6 routes via thousands of IXP connections to overflow the memory of routers within remote ASes. Kirin's highly distributed nature allows it to bypass traditional route-flooding defense mechanisms, such as per-session prefix limits or route flap damping. We analyze Kirin's theoretical feasibility by formulating it as a mathematical optimization problem, test for practical hurdles by deploying enough infrastructure to perform a micro-scale Kirin attack using 4 IXPs, and validate our assumptions via BGP data analysis, real-world measurements, and router testbed experiments. Despite its low deployment cost, we find that Kirin may inject lethal amounts of routes into the routers of thousands of ASes.