Motivated by the impressive but diffuse scope of DDoS research and reporting, we undertake a multistakeholder (joint industry-academic) analysis to seek convergence across the best available macroscopic views of the relative trends in two dominant classes of attacks - direct-path attacks and reflection-amplification attacks. We first analyze 24 industry reports to extract trends and (in)consistencies across observations by commercial stakeholders in 2022. We then analyze ten data sets spanning industry and academic sources, across four years (2019-2023), to find and explain discrepancies based on data sources, vantage points, methods, and parameters. Our method includes a new approach: we share an aggregated list of DDoS targets with industry players who return the results of joining this list with their proprietary data sources to reveal gaps in visibility of the academic data sources. We use academic data sources to explore an industry-reported relative drop in spoofed reflection-amplification attacks in 2021-2022. Our study illustrates the value, but also the challenge, in independent validation of security-related properties of Internet infrastructure. Finally, we reflect on opportunities to facilitate greater common understanding of the DDoS landscape. We hope our results inform not only future academic and industry pursuits but also emerging policy efforts to reduce systemic Internet security vulnerabilities.

There has been substantial commentary on the role of cyberattacks carried out by low-level cybercrime actors in the Russia-Ukraine conflict. We analyse 358k website defacement attacks, 1.7M UDP amplification DDoS attacks, 1764 posts made by 372 users on Hack Forums mentioning the two countries, and 441 Telegram announcements (with 58k replies) of a volunteer hacking group for two months before and four months after the invasion. We find the conflict briefly but notably caught the attention of low-level cybercrime actors, with significant increases in online discussion and both types of attacks targeting Russia and Ukraine. However, there was little evidence of high-profile actions; the role of these players in the ongoing hybrid warfare is minor, and they should be separated from persistent and motivated 'hacktivists' in state-sponsored operations. Their involvement in the conflict appears to have been short-lived and fleeting, with a clear loss of interest in discussing the situation and carrying out both website defacement and DDoS attacks against either Russia or Ukraine after just a few weeks.

Illegal booter services offer denial of service (DoS) attacks for a fee of a few tens of dollars a month. Internationally, police have implemented a range of different types of intervention aimed at those using and offering booter services, including arrests and website takedown. In order to measure the impact of these interventions we look at the usage reports that booters themselves provide and at measurements of reflected UDP DoS attacks, leveraging a five year measurement dataset that has been statistically demonstrated to have very high coverage. We analysed time series data (using a negative binomial regression model) to show that several interventions have had a statistically significant impact on the number of attacks. We show that, while there is no consistent effect of highly-publicised court cases, takedowns of individual booters precede significant, but short-lived, reductions in recorded attack numbers. However, more wide-ranging disruptions have much longer effects. The closure of HackForums' booter market reduced attacks for 13 weeks globally (and for longer in particular countries) and the FBI's coordinated operation in December 2018, which involved both takedowns and arrests, reduced attacks by a third for at least 10 weeks and resulted in lasting change to the structure of the booter market.

eWhoring is the term used by offenders to refer to a type of online fraud in which cybersexual encounters are simulated for financial gain. Perpetrators use social engineering techniques to impersonate young women in online communities, e.g., chat or social networking sites. They engage potential customers in conversation with the aim of selling misleading sexual material -- mostly photographs and interactive video shows -- illicitly compiled from third-party sites. eWhoring is a popular topic in underground communities, with forums acting as a gateway into offending. Users not only share knowledge and tutorials, but also trade in goods and services, such as packs of images and videos. In this paper, we present a processing pipeline to quantitatively analyse various aspects of eWhoring. Our pipeline integrates multiple tools to crawl, annotate, and classify material in a semi-automatic way. It builds in precautions to safeguard against significant ethical issues, such as avoiding the researchers' exposure to pornographic material, and legal concerns, which were justified as some of the images were classified as child exploitation material. We use it to perform a longitudinal measurement of eWhoring activities in 10 specialised underground forums from 2008 to 2019. Our study focuses on three of the main eWhoring components: (i) the acquisition and provenance of images; (ii) the financial profits and monetisation techniques; and (iii) a social network analysis of the offenders, including their relationships, interests, and pathways before and after engaging in this fraudulent activity. We provide recommendations, including potential intervention approaches.

Underground forums allow criminals to interact, exchange knowledge, and trade in products and services. They also provide a pathway into cybercrime, tempting the curious to join those already motivated to obtain easy money. Analysing these forums enables us to better understand the behaviours of offenders and pathways into crime. Prior research has been valuable, but limited by a reliance on datasets that are incomplete or outdated. More complete data, going back many years, allows for comprehensive research into the evolution of forums and their users. We describe CrimeBot, a crawler designed around the particular challenges of capturing data from underground forums. CrimeBot is used to update and maintain CrimeBB, a dataset of more than 48m posts made from 1m accounts in 4 different operational forums over a decade. This dataset presents a new opportunity for large-scale and longitudinal analysis using up-to-date information. We illustrate the potential by presenting a case study using CrimeBB, which analyses which activities lead new actors into engagement with cybercrime. CrimeBB is available to other academic researchers under a legal agreement, designed to prevent misuse and provide safeguards for ethical research.

We evaluate the use of data obtained by illicit means against a broad set of ethical and legal issues. Our analysis covers both the direct collection, and secondary uses of, data obtained via illicit means such as exploiting a vulnerability, or unauthorized disclosure. We extract ethical principles from existing advice and guidance and analyse how they have been applied within more than 20 recent peer reviewed papers that deal with illicitly obtained datasets. We find that existing advice and guidance does not address all of the problems that researchers have faced and explain how the papers tackle ethical issues inconsistently, and sometimes not at all. Our analysis reveals not only a lack of application of safeguards but also that legitimate ethical justifications for research are being overlooked. In many cases positive benefits, as well as potential harms, remain entirely unidentified. Few papers record explicit Research Ethics Board (REB) approval for the activity that is described and the justifications given for exemption suggest deficiencies in the REB process.

Device Analyzer is an Android app available from the Google Play store. It is designed to collect a large range of data from the handset and, with agreement from our contributors, share it with researchers around the world. Researchers can access the data collected, and can also use the platform to support their own user studies. In this paper we provide an overview of the privacy-enhancing techniques used in Device Analzyer, including transparency, consent, purpose, access, withdrawal, and accountability. We also demonstrate the utility of our platform by assessing the security of the Android ecosystem to privilege escalation attacks and determine that 88% of Android devices are, on average, vulnerable to one or more of these type of attacks.