In this dissertation we develop empirical measurement methods and systems for understanding politically and economically motivated Internet threats. Specifically, we examine the problems of Internet censorship and advertising abuse in-depth and at-scale. To understand censorship, we develop Augur and Iris, methods and accompanying systems that allow us to perform global, longitudinal measurement of Internet censorship at the TCP/IP and DNS layers of the network stack—without the use of volunteers. This work addresses a range of both technical and extra-technical challenges, at a scale and fidelity not previously achieved. In combating advertising abuse, we investigate and chronicle multiple facets of the ecosystem—from clickbots to large-scale botnets to advertising injection—using a variety of empirical methods. Our work ultimately identifies fundamental structural weak-points leverageable for defense, resulting in dismantling botnets, cleaning up ad networks, and protecting users.