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congratulations to Manaf Gharaibeh for his PhD

I would like to congratulate Dr. Manaf Gharaibeh for defending his PhD at Colorado State University in February 2020 and completing his doctoral dissertation “Characterizing the Visible Address Space to Enable Efficient, Continuous IP Geolocation” in March 2020.

From the abstract:

Manaf Gharaibeh’s phd defense, with Christos Papadopoulos.

Internet Protocol (IP) geolocation is vital for location-dependent applications and many network research problems. The benefits to applications include enabling content customization, proximal server selection, and management of digital rights based on the location of users, to name a few. The benefits to networking research include providing geographic context useful for several purposes, such as to study the geographic deployment of Internet resources, bind cloud data to a location, and to study censorship and monitoring, among others.
The measurement-based IP geolocation is widely considered as the state-of-the-art client-independent approach to estimate the location of an IP address. However, full measurement-based geolocation is prohibitive when applied continuously to the entire Internet to maintain up-to-date IP-to-location mappings. Furthermore, many IP address blocks rarely move, making it unnecessary to perform such full geolocation.
The thesis of this dissertation states that \emph{we can enable efficient, continuous IP geolocation by identifying clusters of co-located IP addresses and their location stability from latency observations.} In this statement, a cluster indicates a group of an arbitrary number of adjacent co-located IP addresses (a few up to a /16). Location stability indicates a measure of how often an IP block changes location. We gain efficiency by allowing IP geolocation systems to geolocate IP addresses as units, and by detecting when a geolocation update is required, optimizations not explored in prior work. We present several studies to support this thesis statement.
We first present a study to evaluate the reliability of router geolocation in popular geolocation services, complementing prior work that evaluates end-hosts geolocation in such services. The results show the limitations of these services and the need for better solutions, motivating our work to enable more accurate approaches. Second, we present a method to identify clusters of \emph{co-located} IP addresses by the similarity in their latency. Identifying such clusters allows us to geolocate them efficiently as units without compromising accuracy. Third, we present an efficient delay-based method to identify IP blocks that move over time, allowing us to recognize when geolocation updates are needed and avoid frequent geolocation of the entire Internet to maintain up-to-date geolocation. In our final study, we present a method to identify cellular blocks by their distinctive variation in latency compared to WiFi and wired blocks. Our method to identify cellular blocks allows a better interpretation of their latency estimates and to study their geographic properties without the need for proprietary data from operators or users.

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Publications Students

congratulations to Lan Wei for her new PhD

I would like to congratulate Dr. Lan Wei for defending her PhD in September 2020 and completing her doctoral dissertation “Anycast Stability, Security and Latency in The Domain Name System (DNS) and Content Deliver Networks (CDNs)” in December 2020.

From the abstract:

Clients’ performance is important for both Content-Delivery Networks (CDNs) and the Domain Name System (DNS). Operators would like the service to meet expectations of their users. CDNs providing stable connections will prevent users from experiencing downloading pause from connection breaks. Users expect DNS traffic to be secure without being intercepted or injected. Both CDN and DNS operators care about a short network latency, since users can become frustrated by slow replies.


Many CDNs and DNS services (such as the DNS root) use IP anycast to bring content closer to users. Anycast-based services announce the same IP address(es) from globally distributed sites. In an anycast infrastructure, Internet routing protocols will direct users to a nearby site naturally. The path between a user and an anycast site is formed on a hop-to-hop basis—at each hop} (a network device such as a router), routing protocols like Border Gateway Protocol (BGP) makes the decision about which next hop to go to. ISPs at each hop will impose their routing policies to influence BGP’s decisions. Without globally knowing (also unable to modify) the distributed information of BGP routing table of every ISP on the path, anycast infrastructure operators are unable to predict and control in real-time which specific site a user will visit and what the routing path will look like. Also, any change in routing policy along the path may change both the path and the site visited by a user. We refer to such minimal control over routing towards an anycast service, the uncertainty of anycast routing. Using anycast spares extra traffic management to map users to sites, but can operators provide a good anycast-based service without precise control over the routing?


This routing uncertainty raises three concerns: routing can change, breaking connections; uncertainty about global routing means spoofing can go undetected, and lack of knowledge of global routing can lead to suboptimal latency. In this thesis, we show how we confirm the stability, how we confirm the security, and how we improve the latency of anycast to answer these three concerns. First, routing changes can cause users to switch sites, and therefore break a stateful connection such as a TCP connection immediately. We study routing stability and demonstrate that connections in anycast infrastructure are rarely broken by routing instability. Of all vantage points (VPs), fewer than 0.15% VP’s TCP connections frequently break due to timeout in 5s during all 17 hours we observed. We only observe such frequent TCP connection break in 1 service out of all 12 anycast services studied. A second problem is DNS spoofing, where a third-party can intercept the DNS query and return a false answer. We examine DNS spoofing to study two aspects of security–integrity and privacy, and we design an algorithm to detect spoofing and distinguish different mechanisms to spoof anycast-based DNS. We show that DNS spoofing is uncommon, happening to only 1.7% of all VPs, although increasing over the years. Among all three ways to spoof DNS–injections, proxies, and third-party anycast site (prefix hijack), we show that third-party anycast site is the least popular one. Last, diagnosing poor latency and improving the latency can be difficult for CDNs. We develop a new approach, BAUP (bidirectional anycast unicast probing), which detects inefficient routing with better routing replacement provided. We use BAUP to study anycast latency. By applying BAUP and changing peering policies, a commercial CDN is able to significantly reduce latency, cutting median latency in half from 40ms to 16ms for regional users.

Lan defended her PhD when USC was on work-from-home due to COVID-19; she is the third ANT student with a fully on-line PhD defense.

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Students

congratulations to Calvin Ardi for his new PhD

I would like to congratulate Dr. Calvin Ardi for defending his PhD in April 2020 and completing his doctoral dissertation “Improving Network Security through Collaborative Sharing” in June 2020.

From the abstract:

Calvin Ardi and John Heidemann (inset), after Calvin filed his PhD dissertation.

As our world continues to become more interconnected through the
Internet, cybersecurity incidents are correspondingly increasing in
number, severity, and complexity. The consequences of these attacks
include data loss, financial damages, and are steadily moving from the
digital to the physical world, impacting everything from public
infrastructure to our own homes. The existing mechanisms in
responding to cybersecurity incidents have three problems: they
promote a security monoculture, are too centralized, and are too slow.


In this thesis, we show that improving one’s network security strongly
benefits from a combination of personalized, local detection, coupled
with the controlled exchange of previously-private network information
with collaborators. We address the problem of a security monoculture
with personalized detection, introducing diversity by tailoring to the
individual’s browsing behavior, for example. We approach the problem
of too much centralization by localizing detection, emphasizing
detection techniques that can be used on the client device or local
network without reliance on external services. We counter slow
mechanisms by coupling controlled sharing of information with
collaborators to reactive techniques, enabling a more efficient
response to security events.


We prove that we can improve network security by demonstrating our
thesis with four studies and their respective research contributions
in malicious activity detection and cybersecurity data sharing. In
our first study, we develop Content Reuse Detection, an approach to
locally discover and detect duplication in large corpora and apply our
approach to improve network security by detecting “bad
neighborhoods” of suspicious activity on the web. Our second study
is AuntieTuna, an anti-phishing browser tool that implements personalized,
local detection of phish with user-personalization and improves
network security by reducing successful web phishing attacks. In our
third study, we develop Retro-Future, a framework for controlled information
exchange that enables organizations to control the risk-benefit
trade-off when sharing their previously-private data. Organizations
use Retro-Future to share data within and across collaborating organizations,
and improve their network security by using the shared data to
increase detection’s effectiveness in finding malicious activity.
Finally, we present AuntieTuna2.0 in our fourth study, extending the proactive
detection of phishing sites in AuntieTuna with data sharing between friends.
Users exchange previously-private information with collaborators to
collectively build a defense, improving their network security and
group’s collective immunity against phishing attacks.

Calvin defended his PhD when USC was on work-from-home due to COVID-19; he is the second ANT student with a fully on-line PhD defense.

Categories
Students

congratulations to Hang Guo for his new PhD

I would like to congratulate Dr. Hang Guo for defending his PhD in April 2020 and completing his doctoral dissertation “Detecting and Characterizing Network Devices Using
Signatures of Traffic About End-Points” in May 2020.

Hang Guo and John Heidemann (inset), after Hang filed his PhD dissertation.

From the abstract:

The Internet has become an inseparable part of our society. Since the Internet is essentially a distributed system of billions of inter-connected, networked devices, learning about these devices is essential for better understanding, managing and securing the Internet. To study these network devices, without direct control over them or direct contact with their users, requires traffic-based methods for detecting devices. To identify target devices from traffic measurements, detection of network devices relies on signatures of traffic, mapping from certain characteristics of traffic to target devices. This dissertation focuses on device detection that use signatures of traffic about end-points: mapping from characteristics of traffic end-point, such as counts and identities, to target devices. The thesis of this dissertation is that new signatures of traffic about end-points enable detection and characterizations of new class of network devices. We support this thesis statement through three specific studies, each detecting and characterizing a new class of network devices with a new signature of traffic about end-points. In our first study, we present detection and characterization of network devices that rate limit ICMP traffic based on how they change the responsiveness of traffic end-points to active probings. In our second study, we demonstrate mapping identities of traffic end-points to a new class of network devices: Internet-of-Thing (IoT) devices. In our third study, we explore detecting compromised IoT devices by identifying IoT devices talking to suspicious end-points. Detection of these compromised IoT devices enables us to mitigate DDoS traffic between them and suspicious end-points.

Hang defend his PhD when USC was on work-from-home due to COVID-19, so he is the first ANT student with a fully on-line PhD defense.

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Announcements Students

congratulations to Liang Zhu for his new PhD

I would like to congratulate Dr. Liang Zhu for defending his PhD in August 2018 and completing his doctoral dissertation “Balancing Security and Performance of Network Request-Response Protocols” in September 2018.

Liang Zhu (left) and John Heidemann, after Liang’s PhD defense.

From the abstract:

The Internet has become a popular tool to acquire information and knowledge. Usually information retrieval on the Internet depends on request-response protocols, where clients and servers exchange data. Despite of their wide use, request-response protocols bring challenges for security and privacy. For example, source-address spoofing enables denial-of-service (DoS) attacks, and eavesdropping of unencrypted data leaks sensitive information in request-response protocols. There is often a trade-off between security and performance in request-response protocols. More advanced protocols, such as Transport Layer Security (TLS), are proposed to solve these problems of source spoofing and eavesdropping. However, developers often avoid adopting those advanced protocols, due to performance costs such as client latency and server memory requirement. We need to understand the trade-off between security and performance for request-response protocols and find a reasonable balance, instead of blindly prioritizing one of them.
This thesis of this dissertation states that it is possible to improve security of network request-response protocols without compromising performance, by protocol and deployment optimizations, that are demonstrated through measurements of protocol developments and deployments. We support the thesis statement through three specific studies, each of which uses measurements and experiments to evaluate the development and optimization of a request-response protocol. We show that security benefits can be achieved with modest performance costs. In the first study, we measure the latency of OCSP in TLS connections. We show that OCSP has low latency due to its wide use of CDN and caching, while identifying certificate revocation to secure TLS. In the second study, we propose to use TCP and TLS for DNS to solve a range of fundamental problems in DNS security and privacy. We show that DNS over TCP and TLS can achieve favorable performance with selective optimization. In the third study, we build a configurable, general-purpose DNS trace replay system that emulates global DNS hierarchy in a testbed and enables DNS experiments at scale efficiently. We use this system to further prove the reasonable performance of DNS over TCP and TLS at scale in the real world.

In addition to supporting our thesis, our studies have their own research contributions. Specifically, In the first work, we conducted new measurements of OCSP by examining network traffic of OCSP and showed a significant improvement of OCSP latency: a median latency of only 20ms, much less than the 291ms observed in prior work. We showed that CDN serves 94% of the OCSP traffic and OCSP use is ubiquitous. In the second work, we selected necessary protocol and implementation optimizations for DNS over TCP/TLS, and suggested how to run a production TCP/TLS DNS server [RFC7858]. We suggested appropriate connection timeouts for DNS operations: 20s at authoritative servers and 60s elsewhere. We showed that the cost of DNS over TCP/TLS can be modest. Our trace analysis showed that connection reuse can be frequent (60%-95% for stub and recursive resolvers). We showed that server memory is manageable (additional 3.6GB for a recursive server), and latency of connection-oriented DNS is acceptable (9%-22% slower than UDP). In the third work, we showed how to build a DNS experimentation framework that can scale to emulate a large DNS hierarchy and replay large traces. We used this experimentation framework to explore how traffic volume changes (increasing by 31%) when all DNS queries employ DNSSEC. Our DNS experimentation framework can benefit other studies on DNS performance evaluations.