Douglas C. Sicker

Low-resource routing attacks against tor

Tor has become one of the most popular overlay networks for anonymizing TCP traffic. Its popularity is due in part to its perceived strong anonymity properties and its relatively low latency service. Low latency is achieved through Torâ s ability to balance the traffic load by optimizing Tor router selection to probabilistically favor routers with highbandwidth capabilities. We investigate how Torâ s routing optimizations impact its ability to provide strong anonymity. Through experiments conducted on PlanetLab, we show the extent to which routing performance optimizations have left the system vulnerable to end-to-end traffic analysis attacks from non-global adversaries with minimal resources. Further, we demonstrate that entry guards, added to mitigate path disruption attacks, are themselves vulnerable to attack. Finally, we explore solutions to improve Torâ s current routing algorithms and propose alternative routing strategies that prevent some of the routing attacks used in our experiments.

Shining Light in Dark Places: Understanding the Tor Network

To date, there has yet to be a study that characterizes the usage of a real deployed anonymity service. We present observations and analysis obtained by participating in the Tor network. Our primary goals are to better understand Tor as it is deployed and through this understanding, propose improvements. In particular, we are interested in answering the following questions: (1) How is Tor being used? (2) How is Tor being mis-used? (3) Who is using Tor? To sample the results, we show that web traffic makes up the majority of the connections and bandwidth, but non-interactive protocols consume a disproportionately large amount of bandwidth when compared to interactive protocols. We provide a survey of how Tor is being misused, both by clients and by Tor router operators. In particular, we develop a method for detecting exit router logging (in certain cases). Finally, we present evidence that Tor is used throughout the world, but router participation is limited to only a few countries.

MultiMAC - an adaptive MAC framework for dynamic radio networking

Software-defined/cognitive radio has recently made the jump from a purely research driven endeavor to one that is now being driven commercially. Such radios offer the promise of spectrum agility and re-configurability through flexibility at the MAC and physical layers. In the wireless domain, it has been shown that hybrid-MAC layer algorithms can lead to improved overall performance in varying network conditions. A hybrid MAC that uses CSMA in low-contention periods and switches to TDMA in high-contention periods can outperform CSMA or TDMA individually. However, such hybrid systems do not offer the flexibility and cognition required of dynamic spectrum networks. In this paper, we describe MultiMAC, a framework and experimental platform for evaluating algorithms that dynamically reconfigure MAC and physical layer properties. MultiMAC acts as a mediating MAC layer and dynamically reconfigures and/or selects from a collection of alternative MAC layers. As a result of monitoring current network metrics, MultiMAC chooses the MAC layer capable of achieving the best performance while ensuring that incoming frames are decoded using the correct MAC layer algorithm. MultiMAC incorporates decision processes to select the appropriate MAC component based on per-node and per-flow statistics. This engine will allow intelligent reconfiguration of the MAC and physical layers in response to changes in external conditions and/or requirements optimizing use of the available spectrum

MOJO: a distributed physical layer anomaly detection system for 802.11 WLANs

Deployments of wireless LANs consisting of hundreds of 802.11 access points with a large number of users have been reported in enterprises as well as college campuses. However, due to the unreliable nature of wireless links, users frequently encounter degraded performance and lack of coverage. This problem is even worse in unplanned networks, such as the numerous access points deployed by homeowners. Existing approaches that aim to diagnose these problems are inefficient because they troubleshoot at too high a level, and are unable to distinguish among the root causes of degradation. This paper designs, implements, and tests fine-grained detection algorithms that are capable of distinguishing between root causes of wireless anomalies at the depth of the physical layer. An important property that emerges from our system is that diagnostic observations are combined from multiple sources over multiple time instances for improved accuracy and efficiency.

A Survey of Wireless Path Loss Prediction and Coverage Mapping Methods

In this paper we provide a thorough and up to date survey of path loss prediction methods, spanning more than 60 years of fairly continuous research. These methods take a variety of approaches to modeling the signal attenuation between wireless transceivers: purely theoretical models, empirically fitted (often statistical) models, deterministic ray-optical models, and measurement-directed methods. Our work here extends and updates excellent, but now dated prior surveys of this important field. We provide a new taxonomy for reasoning about the similarities and differences of the many approaches and provide a brief but complete overview of the various methods as well as describing insights into future directions for research in this area.

Legal issues surrounding monitoring during network research

This work was motivated by a discussion that two of the coauthors (computer science professors) had with the other coauthor (a law professor and a former computer crime Trial Attorney at the U.S. Department of Justice), in which it was pointed out that some of the network measurements that the computer scientists were thinking of making might potentially violate Federal laws. Several Federal laws prohibit or restrict network monitoring and the sharing of records of network activity. These laws are designed to protect online privacy. They apply both to private parties and government agents, although the details vary depending on who is doing the monitoring. The most important thing to note is that none of these laws contain any specific exceptions or safe harbors for scientific or academic research. The laws are complex, but they follow a basic pattern. First, certain types of network monitoring and data access are prohibited. People who violate the prohibitions may be sued by the people whose privacy they invade and potentially prosecuted and convicted of federal crimes (i.e., misdemeanor and felony convictions). In this paper, we will examine these laws and consider what they might mean for the network measurement community. Although we focus on U.S. Federal Law, we also highlight general trends and approaches in state and international laws that impact network researchers. We will examine the steps commonly taken in prior research in network measurement to respect user privacy, and we will compare those approaches to the evolving legal rules. We will also consider whether legislative reform is needed, describe steps that researchers might take when pursuing such work in light of the legal rules, and propose future technical and policy-related steps the community can take to focus more attention on user privacy.

SMACK: a SMart ACKnowledgment scheme for broadcast messages in wireless networks

Network protocol designers, both at the physical and network level, have long considered interference and simultaneous transmission in wireless protocols as a problem to be avoided. This, coupled with a tendency to emulate wired network protocols in the wireless domain, has led to artificial limitations in wireless networks. In this paper, we argue that wireless protocols can exploit simultaneous transmission to reduce the cost of reliable multicast by orders of magnitude. With an appropriate application interface, simultaneous transmission can also greatly speed up common group communication primitives, such as anycast, broadcast, leader election and others. The proposed method precisely fits into the domain of directly reachable nodes where many group communication mechanisms are commonly used in routing protocols and other physical-layer mechanisms. We demonstrate how simultaneous transmission can be used to implement a reliable broadcast for an infrastructure and peer-to-peer network using a prototype reconfigurable hardware. We also validate the notion of using simple spectrum sensing techniques to distinguish multiple transmissions. We then describe how the mechanism can be extended to solve group communication problems and the challenges inherent to build innovative protocols which are faster and reliable at the same time.

Practical radio environment mapping with geostatistics

In this paper we present results from the first application of robust geostatistical modeling techniques to radio environment and coverage mapping of wireless networks. We perform our analysis of these methods with a case study mapping the coverage of a 2.5 GHz WiMax network at the University of Colorado, Boulder. Drawing from our experiences, we propose several new methods and extensions to basic geostatistical theory that are necessary for use in a radio mapping application. We also derive a set of best practices and discuss potential areas of future work. We find that this approach to radio environment mapping is feasible and produces maps that are more accurate and informative than both explicitly tuned path loss models and basic data fitting approaches.

Bounding the error of path loss models

In this paper we analyze the efficacy of basic path loss models at predicting median path loss in urban environments. We attempt to bound the practical error of these models and look at how they may hinder practical wireless applications, and in particular dynamic spectrum access networks. This analysis is made using a large set of measurements from production networks in two US cities. We are able to show quantitatively what many experienced radio engineers understand: these models perform poorly at predicting path loss in even relatively simple outdoor environments and are of little practical use aside from making crude estimates of coverage in the least demanding applications. As a solution, we advocate a renewed focus on measurement-based, adaptive path loss models built on appropriate statistical methods.

A Statistical Method for Reconfiguration of Cognitive Radios

Recent developments in computer technology have enabled radio developers to accomplish in software what traditionally was performed with application-specific integrated circuits. A radio that has the core of its functionality implemented in software is called a software-defined radio. When an SDR has the capability to sense, reason, and dynamically adapt to requirements and environmental change, we call this more capable device a cognitive radio. Many private and public agencies are investing in the promise of CR to improve the utilization of radio frequency spectrum. They envision devices that can sense frequency vacancies and dynamically reconfigure to utilize idle channels. The promise of CR depends on the capability of a radio to change operating frequencies, power, and/or modulation schemes (physical layer flexibility). In addition to this physical layer flexibility, there are a large number of opportunities to capitalize on the interplay of the CR physical layer configuration and other parameters in the radio network protocol stack. At the core of CR functionality is the ability to select from thousands of potential configurations to maximize performance-be it in terms of spectrum use, throughput, or reliability. In this article, we describe a method for selecting from a number of potential configurations to fulfill the communication requirements of a CR network. By using accepted statistical methods, we show how parameters at the physical, data link, network, and application layers interact to affect performance. We build upon this parametric insight with our presentation of a technique for predicting radio performance.