Internet Service Providers (ISPs) are getting involved in remediating Internet of Things (IoT) infections of end users. This endeavor runs into serious usability problems. Given that it is usually unknown what kind of device is infected, they can only provide users with very generic cleanup advice, trying to cover all device types and remediation paths. Does this advice work? To what extent do users comply with the instructions? And does more compliance lead to higher cleanup rates? This study is the first to shed light on these questions. In partnership with an ISP, we designed a randomized control experiment followed up by a user survey. We randomly assigned 177 consumers affected by malware from the Mirai family to three different groups: (i) notified via a walled garden (quarantine network), (ii) notified via email, and (iii) no immediate notification, i.e. a control group. The notification asks the user to take five steps to remediate the infection. We conducted a phone survey with 95 of these customers based on communication–human information processing theory. We model the impact of the treatment, comprehension, and motivation on the compliance rate of each customer, while controlling for differences in demographics and infected device types. We also estimate the extent to which compliance leads to successful cleanup of the infected IoT devices. While only 24% of notified users perform all five remediation steps, 92% of notified users perform at least one action. Compliance increases the probability of successful cleanup by 32%, while the presence of competing malware reduces it by 54%. We provide an empirical basis to shape ISP best practices in the fight against IoT malware.
For technical reasons the number of authors shown on this cover page is limited to a maximum of 10. * TU-Delft (Netherlands), † SIDN Labs (Netherlands), ‡ NICT (Japan)Abstract-For the mitigation of compromised Internet of Things (IoT) devices we rely on Internet Service Providers (ISPs) and their users. Given that devices are in the hands of their subscribers, what can ISPs realistically do? This study examines the effects of ISP countermeasures on infections caused by variants of the notorious Mirai family of IoT malware, still among the dominant families. We collect and analyze more than 4 years of longitudinal darknet data tracking Mirai-like infections in conjunction with threat intelligence data on various other IoT and non-IoT botnets across the globe from January 2016 to May 2020. We measure the effect of two ISP countermeasures on Mirai variant infection numbers: (i) reducing the attack surface (i.e., closing ports that are used by the malware for propagation) and (ii) ISPs increasing their general network hygiene and malware removal efforts (as observed by proxy of the remediation of infections of other families of IoT and non-IoT malware and reductions in the number of DDoS amplifiers in their networks). We map our infection data to 342 broadband providers that have the bulk of the broadband market share in their respective 83 countries. We find that the number of infections correlates strongly with the number of ISP subscribers (R 2 =0.55). Yet, infection numbers can still vary by three orders of magnitude even for ISPs with comparable subscriber numbers. We observe that many ISPs, together with their subscribers, have reduced their attack surface for IoT compromise by blocking traffic to commonly-exploited infection vectors such as Telnet and FTP. We statistically estimate the impact of these reductions on infection levels and, counter-intuitively, find no significant impact. In contrast, we do find a significant impact for improving general network hygiene and best malware mitigation practices. ISPs that were more successful in reducing DDoS amplifiers and non-Mirai malware infections in their networks also end up with significantly lower Mirai infection rates. In other words, rather than investing in IoT-specific countermeasures like reducing the attack surface, our findings suggest that ISPs might be better off investing in general security efforts to improve network hygiene and clean up abuse.
Consumer IoT devices may suffer malware attacks, and be recruited into botnets or worse. There is evidence that generic advice to device owners to address IoT malware can be successful, but this does not account for emerging forms of persistent IoT malware. Less is known about persistent malware, which resides on persistent storage, requiring targeted manual effort to remove it. This paper presents a field study on the removal of persistent IoT malware by consumers. We partnered with an ISP to contrast remediation times of 760 customers across three malware categories: Windows malware, non-persistent IoT malware, and persistent IoT malware. We also contacted ISP customers identified as having persistent IoT malware on their network-attached storage devices, specifically QSnatch. We found that persistent IoT malware exhibits a mean infection duration many times higher than Windows or Mirai malware; QSnatch has a survival probability of 30% after 180 days, whereby most if not all other observed malware types have been removed. For interviewed device users, QSnatch infections lasted longer, so are apparently more difficult to get rid of, yet participants did not report experiencing difficulty in following notification instructions. We see two factors driving this paradoxical finding: First, most users reported having high technical competency. Also, we found evidence of planning behavior for these tasks and the need for multiple notifications. Our findings demonstrate the critical nature of interventions from outside for persistent malware, since automatic scan of an AV tool or a power cycle, like we are used to for Windows malware and Mirai infections, will not solve persistent IoT malware infections.
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