October 19, 2017

Mitigating the Increasing Risks of an Insecure Internet of Things

The emergence and proliferation of Internet of Things (IoT) devices on industrial, enterprise, and home networks brings with it unprecedented risk. The potential magnitude of this risk was made concrete in October 2016, when insecure Internet-connected cameras launched a distributed denial of service (DDoS) attack on Dyn, a provider of DNS service for many large online service providers (e.g., Twitter, Reddit). Although this incident caused large-scale disruption, it is noteworthy that the attack involved only a few hundred thousand endpoints and a traffic rate of about 1.2 terabits per second. With predictions of upwards of a billion IoT devices within the next five to ten years, the risk of similar, yet much larger attacks, is imminent.

The Growing Risks of Insecure IoT Devices

One of the biggest contributors to the risk of future attack is the fact that many IoT devices have long-standing, widely known software vulnerabilities that make them vulnerable to exploit and control by remote attackers. Worse yet, the vendors of these IoT devices often have provenance in the hardware industry, but they may lack expertise or resources in software development and systems security. As a result, IoT device manufacturers may ship devices that are extremely difficult, if not practically impossible, to secure. The large number of insecure IoT devices connected to the Internet poses unprecedented risks to consumer privacy, as well as threats to the underlying physical infrastructure and the global Internet at large:

  • Data privacy risks. Internet-connected devices increasingly collect data about the physical world, including information about the functioning of infrastructure such as the power grid and transportation systems, as well as personal or private data on individual consumers. At present, many IoT devices either do not encrypt their communications or use a form of encrypted transport that is vulnerable to attack. Many of these devices also store the data they collect in cloud-hosted services, which may be the target of data breaches or other attack.
  • Risks to availability of critical infrastructure and the Internet at large. As the Mirai botnet attack of October 2016 demonstrated, Internet services often share underlying dependencies on the underlying infrastructure: crippling many websites offline did not require direct attacks on these services, but rather a targeted attack on the underlying infrastructure on which many of these services depend (i.e., the Domain Name System). More broadly, one might expect future attacks that target not just the Internet infrastructure but also physical infrastructure that is increasingly Internet- connected (e.g., power and water systems). The dependencies that are inherent in the current Internet architecture create immediate threats to resilience.

    The large magnitude and broad scope of these risks implore us to seek solutions that will improve infrastructure resilience in the face of Internet-connected devices that are extremely difficult to secure. A central question in this problem area concerns the responsibility that each stakeholder in this ecosystem should bear, and the respective roles of technology and regulation (whether via industry self-regulation or otherwise) in securing both the Internet and associated physical infrastructure against these increased risks.

Risk Mitigation and Management

One possible lever for either government or self-regulation is the IoT device manufacturers. One possibility, for example, might be a device certification program for manufacturers that could attest to adherence to best common practice for device and software security. A well-known (and oft-used) analogy is the UL certification process for electrical devices and appliances.

Despite its conceptual appeal, however, a certification approach poses several practical challenges. One challenge is outlining and prescribing best common practices in the first place, particularly due to the rate at which technology (and attacks) progress. Any specific set of prescriptions runs the risk of falling out of date as technology advances; similarly, certification can readily devolve into a checklist of attributes that vendors satisfy, without necessarily adhering to the process by which these devices are secured over time. As daunting as challenges of specifying a certification program may seem, enforcing adherence to a certification program may prove even more challenging. Specifically, consumers may not appreciate the value of certification, particularly if meeting the requirements of certification increases the cost of a device. This concern may be particularly acute for consumer IoT, where consumers may not bear the direct costs of connecting insecure devices to their home networks.

The consumer is another stakeholder who could be incentivized to improve the security of the devices that they connect to their networks (in addition to more effectively securing the networks to which they connect these devices). As the entity who purchases and ultimately connects IoT devices to the network, the consumer appears well-situated to ensure the security of the IoT devices on their respective networks. Unfortunately, the picture is a bit more nuanced. First, consumers typically lack either the aptitude or interest (or both!) to secure either their own networks or the devices that they connect to them. Home broadband Internet access users have generally proved to be poor at applying software updates in a timely fashion, for example, and have been equally delinquent in securing their home networks. Even skilled network administrators regularly face network misconfigurations, attacks, and data breaches. Second, in many cases, users may lack the incentives to ensure that their devices are secure. In the case of the Mirai botnet, for example, consumers did not directly face the brunt of the attack; rather, the ultimate victims of the attack were DNS service providers and, indirectly, online service providers such as Twitter. To the first order, consumers suffered little direct consequence as a result of insecure devices on their networks.

Consumers’ misaligned incentives suggest several possible courses of action. One approach might involve placing some responsibility or liability on consumers for the devices that they connect to the network, in the same way that a citizen might be fined for other transgressions that have externalities (e.g., fines for noise or environmental pollution). Alternatively, Internet service providers (or another entity) might offer users a credit for purchasing and connecting only devices that it pass certification; another variation of this approach might require users to purchase ”Internet insurance” from their Internet service providers that could help offset the cost of future attacks. Consumers might receive credits or lower premiums based on the risk associated with their behavior (i.e., their software update practices, results from security audits of devices that they connect to the network).

A third stakeholder to consider is the Internet service provider (ISP), who provides Internet connectivity to the consumer. The ISP has considerable incentives to ensure that the devices that its customer connects to the network are secure: insecure devices increase the presence of attack traffic and may ultimately degrade Internet service or performance for the rest of the ISPs’ customers. From a technical perspective, the ISP is also in a uniquely effective position to detect and squelch attack traffic coming from IoT devices. Yet, relying on the ISP alone to protect the network against insecure IoT devices is fraught with non-technical complications. Specifically, while the ISP could technically defend against an attack by disconnecting or firewalling consumer devices that are launching attacks, such an approach will certainly result in increased complaints and technical support calls from customers, who connect devices to the network and simply expect them to work. Second, many of the technical capabilities that an ISP might have at its disposal (e.g., the ability to identify attack traffic coming from a specific device) introduce serious privacy concerns. For example, being able to alert a customer to (say) a compromised baby monitor requires the ISP to know (and document) that a consumer has such a device in the first place.

Ultimately, managing the increased risks associated with insecure IoT devices may require action from all three stakeholders. Some of the salient questions will concern how the risks can be best balanced against the higher operational costs that will be associated with improving security, as well as who will ultimately bear these responsibilities and costs.

Improving Infrastructure Resilience

In addition to improving defenses against the insecure devices themselves, it is also critical to determine how to better build resilience into the underlying Internet infrastructure to cope with these attacks. If one views the occasional IoT-based attack inevitable to some degree, one major concern is ensuring that the Internet Infrastructure (and the associated cyberphysical infrastructure) remains both secure and available in the face of attack. In the case of the Mirai attack on Dyn, for example, the severity of the attack was exacerbated by the fact that many online services depended on the infrastructure that was attacked. Computer scientists and Internet engineers should be thinking about technologies that can both potentially decouple these underlying dependencies and ensure that the infrastructure itself remains secure even in the event that regulatory or legal levers fail to prevent every attack. One possibility that we are exploring, for example, is the role that an automated home network firewall could play in (1) help- ing users keep better inventory of connected IoT devices; (2) providing users both visibility into and control over the traffic flows that these devices send.

Summary

Improving the resilience of the Internet and cyberphysical infrastructure in the face of insecure IoT devices will require a combination of technical and regulatory mechanisms. Engineers and regulators will need to work together to improve security and privacy of the Internet of Things. Engineers must continue to advance the state of the art in technologies ranging from lightweight encryption to statistical network anomaly detection to help reduce risk; similarly, engineers must design the network to improve resilience in the face of the increased risk of attack. On the other hand, realizing these advances in deployment will require the appropriate alignment of incentives, so that the parties that introduce risks are more aligned with those who bear the costs of the resulting attacks.

The Effects of the Forthcoming FCC Privacy Rules on Internet Security

Last week, the Federal Communications Commission (FCC) announced new privacy rules that govern how Internet service providers can share information about consumers with third parties.  One focus of this rulemaking has been on the use and sharing of so-called “Consumer Proprietary Network Information (CPNI)”—information about subscribers—for advertising. The Center for Information Technology Policy and the Center for Democracy and Technology jointly hosted a panel exploring this topic last May, and I have previously written on certain aspects of this issue, including what ISPs might be able to infer about user behavior, even if network traffic were encrypted.

Although the forthcoming rulemaking targets the collection, use, and sharing of customer data with “third parties”, an important—and oft-forgotten—facet of this discussion is that (1) ISPs rely on the collection, use, and sharing of CPNI to operate and secure their networks and (2) network researchers (myself included) rely on this data to conduct our research.  As one example of our work that is discussed today in the Wall Street Journal, we used DNS domain registration data to identify cybercriminals before they launch attacks. Performing this research required access to all .com domain registrations. We have also developed algorithms that detect the misuse of DNS domain names by analyzing the DNS lookups themselves. We have also worked with ISPs to explore the relationship between Internet speeds and usage, which required access to byte-level usage data from individual customers. ISPs also rely on third parties, including Verisign and Arbor Networks, to detect and mitigating attacks; network equipment vendors also use traffic traces from ISPs to test new products and protocols. In summary, although the goal of the FCC’s rulemaking is to protect the use of consumer data, the rulemaking could have had unintended negative consequences for the stability and security of the Internet, as well as for Internet innovation.

In response to the potential negative effects this rule could have created for Internet security and networking researchers, I filed comment with the FCC highlighting how network operators researchers depend on data to keep the network operating well, to keep it secure, and to foster continued innovation.  My comment in May highlights the type of data that Internet service providers (ISPs) collect, how they use it for operational and research purposes, and potential privacy concerns with each of these datasets.  In my comment, I exhaustively enumerate the types of data that ISPs collect; the following data types are particularly interesting because ISPs and researchers rely on them heavily, yet they also introduce certain privacy concerns:

  • IPFIX (“NetFlow”) data, which is the Internet traffic equivalent of call data records. IPFIX data is collected at a router and contains statistics about each traffic flow that traverses the router. It contains information about the “metadata” of each flow (e.g., the source and destination IP address, the start and end time of the flow). This data doesn’t contain “payload” information, but as previous research on information like telephone metadata has shown, a lot can be learned about a user from this kind of information. Nonetheless, this data has been used in research and security for many purposes, including (among other things) detecting botnets and denial of service attacks.
  • DNS Query data, which contains information about the domain names that each IP address (i.e., customer) is looking up (i.e., from a Web browser, from an IoT device, etc.). DNS query data can be highly revealing, as we have shown in previous work. Yet, at the same time, DNS query data is also incredibly valuable for detecting Internet abuse, including botnets and malware.

Over the summer, I gave a follow-up a presentation and filed follow-up comments (several of which were jointly authored with members of the networking and security research community) to help draw attention to how much Internet research depends on access to this type of data.  In early August, a group of us filed a comment with proposed wording for the upcoming rule. In this comment, we delineated the types of work that should be exempt from the upcoming rules. We argue that research should be exempt from the rulemaking if the research: (1) aims to promote security, stability, and reliability of networks, (2) does not have the end-goal of violating user privacy; (3) has benefits that outweigh the privacy risks; (4) takes steps to mitigate privacy risks; (5) would be enhanced by access to the ISP data.  In delineating this type of research, our goal was to explicitly “carve out” researchers at universities and research labs without opening a loophole for third-party advertisers.

Of course, the exception notwithstanding, researchers also should be mindful of user privacy when conducting research. Just because a researcher is “allowed” to receive a particular data trace from an ISP does not mean that such data should be shared. For example, much network and security research is possible with de-identified network traffic data (e.g., data with anonymized IP addresses), or without packet “payloads” (i.e., the kind of traffic data collected with Deep Packet Inspection). Researchers and ISPs should always take care to apply data minimization techniques that limit the disclosure of private information to only the granularity that is necessary to perform the research. Various practices for minimization exist, such as hashing or removing IP addresses, aggregating statistics over longer time windows, and so forth. The network and security research communities should continue developing norms and standard practices for deciding when, how, and to what degree private data from ISPs can be minimized when it is shared.

The FCC, ISPs, customers, and researchers should all care about the security, operation, and performance of the Internet.  Achieving these goals often involves sharing customer data with third-parties, such as the network and security research community. As a member of the research community, I am looking forward to reading the text of the rule, which, if our comments are incorporated, will help preserve both customer privacy and the research that keeps the Internet secure and performing well.

The Interconnection Measurement Project

Building on the March 11 release of the “Revealing Utilization at Internet Interconnection Points” working paper, today, CITP is excited to announce the launch of the Interconnection Measurement Project. This unprecedented initiative includes the launch of a project-specific website and the ongoing collection, analysis, and release of capacity and utilization data from ISP interconnection points. CITP’s Interconnection Measurement Project uses the same method that I detailed in the working paper and includes the participation of seven ISPs—Bright House Networks, Comcast, Cox, Mediacom, Midco, Suddenlink, and Time Warner Cable.

The project website—which we aim to update regularly—includes additional views of the data that are not included in the working paper. The visualizations are organized into three categories: (1) Aggregate Views; (2) Regional Views; and (3) Views by Interconnect. The Aggregate Views provide peak utilization, growth in capacity and usage, as well as the distribution of peak utilization across interconnects and across participating ISPs, on a monthly basis across the entire data set. The Regional Views provide monthly peak utilization by region and distribution of peak utilization across interconnects by region. Finally, the Views by Interconnect provide details into daily per-link utilization statistics, as well as the distribution of peak utilization by link and by capacity, also on a monthly basis.The website visualizations also include an additional month of data (March 2016) beyond what the original working paper included. CITP plans to regularly update the visualizations with new data to provide a picture of how the Internet is evolving, and we will assess the project annually to ensure that the data, reports, and insights that we offer remain relevant.

The March data is consistent with the initial findings detailed in the working paper: that many interconnects have significant spare capacity, that this spare capacity exists both across ISPs in each region and in aggregate for any individual ISP, and that the aggregate utilization across interconnects is roughly 50 percent during peak periods.

The seven participating ISPs collectively account for about 50 percent of all US broadband subscribers. We at CITP hope that these ISPs are merely the pioneers of what may eventually become a much larger effort. As we continue to advance this field of research and deepen our understanding of traffic characteristics at interconnection points, we welcome the participation of even more ISPs as well as other network operators and edge providers in this important effort.