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Unsolicited bulk telephone calls — termed "robocalls" — nearly outnumber legitimate calls, overwhelming telephone users. While the vast majority of these calls are illegal, they are also ephemeral. Although telephone service providers, regulators, and researchers have ready access to call metadata, they do not have tools to investigate call content at the vast scale required. This paper presents SnorCall, a framework that scalably and efficiently extracts content from robocalls. SnorCall leverages the Snorkel framework that allows a domain expert to write simple labeling functions to classify text with high accuracy. We apply SnorCall to a corpus of transcripts covering 232,723 robocalls collected over a 23-month period. Among many other findings, SnorCall enables us to obtain first estimates on how prevalent different scam and legitimate robocall topics are, determine which organizations are referenced in these calls, estimate the average amounts solicited in scam calls, identify shared infrastructure between campaigns, and monitor the rise and fall of election-related political calls. As a result, we demonstrate how regulators, carriers, anti-robocall product vendors, and researchers can use SnorCall to obtain powerful and accurate analyses of robocall content and trends that can lead to better defenses. 

Unsolicited calls are one of the most prominent security issues facing individuals today. Despite wide-spread anecdotal discussion of the problem, many important questions remain unanswered. In this paper, we present the first large-scale, longitudinal analysis of unsolicited calls to a honeypot of up to 66,606 lines over 11 months. From call metadata we characterize the long-term trends of unsolicited calls, develop the first techniques to measure voicemail spam, wangiri attacks, and identify unexplained high-volume call incidences. Additionally, we mechanically answer a subset of the call attempts we receive to cluster related calls into operational campaigns, allowing us to characterize how these campaigns use telephone numbers. Critically, we find no evidence that answering unsolicited calls increases the amount of unsolicited calls received, overturning popular wisdom. We also find that we can reliably isolate individual call campaigns, in the process revealing the extent of two distinct Social Security scams while empirically demonstrating the majority of campaigns rarely reuse phone numbers. These analyses comprise powerful new tools and perspectives for researchers, investigators, and a beleaguered public. 

The importance of secure development of new technologies is unquestioned, yet the best methods to achieve this goal are far from certain. A key issue is that while significant effort is given to evaluating the outcomes of development (e.g., security of a given project), it is far more difficult to determine what organizational practices result in secure projects. In this paper, we quantitatively examine efforts to improve the consideration of security in Requests for Comments (RFCs)--- the design documents for the Internet and many related systems --- through the mandates and guidelines issued to RFC authors. We begin by identifying six metrics that quantify the quantity and quality of security informative content. We then apply these metrics longitudinally over 8,437 documents and 49 years of development to determine whether guidance to RFC authors changed these security metrics in later documents. We find that even a simply worded --- but effectively enforced --- mandate to explicitly consider security created a significant effect in increased discussion and topic coverage of security content both in and outside of a mandated security considerations section. We find that later guidelines with more detailed advice on security also improve both volume and quality of security informative content in RFCs. Our work demonstrates that even modest amounts of guidance can correlate to significant improvements in security focus in RFCs, indicating a promising approach for other network standards bodies.