Haeberlen, Andreas
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Publication Tracking Adversarial Behavior in Distributed Systems With Secure Network Provenance(2010-01-01) Haeberlen, Andreas; Zhou, Wenchao; Loo, Boon Thau; Sherr, MicahThis paper presents secure network provenance (SNP), a novel technique for tracking down compromised nodes in a distributed system and assessing the damage that they may have caused to other nodes. SNP enables operators to ask the system why it is in a certain state – for example, why a suspicious routing table entry is present on a certain router, or where a given cache entry originated. SNP is robust to manipulation; its tamper-evident properties ensure that operators can detect when compromised nodes lie or falsely implicate correct nodes. Thus, compromised nodes can at worst refuse to participate, making their presence evident to operators. We describe an algorithm for answering SNP queries, as well as a proof-of-concept implementation.Publication Fault Tolerance and the Five-Second Rule(2015-05-01) Chen, Ang; Xiao, Hanjun; Haeberlen, Andreas; Phan, Linh T.X.We propose a new approach to fault tolerance that we call bounded-time recovery (BTR). BTR is intended for systems that need strong timeliness guarantees during normal operation but can tolerate short outages in an emergency, e.g., when they are under attack. We argue that BTR could be a good fit for many cyber-physical systems. We also sketch a technical approach to providing BTR, and we discuss some challenges that still remain.Publication Detecting Covert Timing Channels with Time-Deterministic Replay(2014-10-01) Chen, Ang; Haeberlen, Andreas; Moore, W. Brad; Phan, Linh T.X.; Xiao, Hanjun; Sherr, Micah; Zhou, WenchaoThis paper presents a mechanism called timedeterministic replay (TDR) that can reproduce the execution of a program, including its precise timing. Without TDR, reproducing the timing of an execution is difficult because there are many sources of timing variability – such as preemptions, hardware interrupts, cache effects, scheduling decisions, etc. TDR uses a combination of techniques to either mitigate or eliminate most of these sources of variability. Using a prototype implementation of TDR in a Java Virtual Machine, we show that it is possible to reproduce the timing to within 1.85% of the original execution, even on commodity hardware. The paper discusses several potential applications of TDR, and studies one of them in detail: the detection of a covert timing channel. Timing channels can be used to exfiltrate information from a compromised machine; they work by subtly varying the timing of the machine’s outputs, and it is this variation that can be detected with TDR. Unlike prior solutions, which generally look for a specific type of timing channel, our approach can detect a wide variety of channels with high accuracy.Publication Having Your Cake and Eating It Too: Routing Security with Privacy Protections(2011-11-01) Gurney, Alexander JT; Haeberlen, Andreas; Loo, Boon Thau; Zhuo, Wenchao; Sherr, MicahInternet Service Providers typically do not reveal details of their interdomain routing policies due to security concerns, or for commercial or legal reasons. As a result, it is difficult to hold ISPs accountable for their contractual agreements. Existing solutions can check basic properties, e.g., whether route announcements correspond to valid routes, but they do not verify how these routes were chosen. In essence, today’s Internet forces us to choose between per-AS privacy and verifiability. In this paper, we argue that making this difficult tradeoff is unnecessary. We propose private and verifiable routing (PVR), a technique that enables ISPs to check whether their neighbors are fulfilling their contractual promises to them, and to obtain evidence of any violations, without disclosing information that the routing protocol does not already reveal. As initial evidence that PVR is feasible, we sketch a PVR system that can verify some simple BGP policies. We conclude by highlighting several research challenges as future work.Publication Accountable Virtual Machines(2010-10-01) Haeberlen, Andreas; Aditya, Paarijaat; Rodrigues, Rodrigo; Druschel, PeterIn this paper, we introduce accountable virtual machines (AVMs). Like ordinary virtual machines, AVMs can execute binary software images in a virtualized copy of a computer system; in addition, they can record non-repudiable information that allows auditors to subsequently check whether the software behaved as intended. AVMs provide strong accountability, which is important, for instance, in distributed systems where different hosts and organizations do not necessarily trust each other, or where software is hosted on third-party operated platforms. AVMs can provide accountability for unmodified binary images and do not require trusted hardware. To demonstrate that AVMs are practical, we have designed and implemented a prototype AVM monitor based on VMwareWorkstation, and used it to detect several existing cheats in Counterstrike, a popular online multi-player game.Publication Secure Network Provenance(2011-10-01) Zhuo, Wenchao; Fei, Qiong; Haeberlen, Andreas; Narayan, Arjun; Loo, Boon Thau; Sherr, MicahThis paper introduces secure network provenance (SNP), a novel technique that enables networked systems to explain to their operators why they are in a certain state – e.g., why a suspicious routing table entry is present on a certain router, or where a given cache entry originated. SNP provides network forensics capabilities by permitting operators to track down faulty or misbehaving nodes, and to assess the damage such nodes may have caused to the rest of the system. SNP is designed for adversarial settings and is robust to manipulation; its tamper-evident properties ensure that operators can detect when compromised nodes lie or falsely implicate correct nodes. We also present the design of SNooPy, a general-purpose SNP system. To demonstrate that SNooPy is practical, we apply it to three example applications: the Quagga BGP daemon, a declarative implementation of Chord, and Hadoop MapReduce. Our results indicate that SNooPy can efficiently explain state in an adversarial setting, that it can be applied with minimal effort, and that its costs are low enough to be practical.Publication TAP: Time-Aware Provenance for Distributed Systems(2011-06-01) Haeberlen, Andreas; Zhuo, Wenchao; Ives, Zachary G; Ding, Ling; Loo, Boon ThauIn this paper, we explore the use of provenance for analyzing execution dynamics in distributed systems. We argue that provenance could have significant practical benefits for system administrators, e.g., for reasoning about changes in a system’s state, diagnosing protocol misconfigurations, detecting intrusions, and pinpointing performance bottlenecks. However, to realize this vision, we must revisit several aspects of provenance management. As a first step, we present time-aware provenance (TAP), an enhanced provenance model that explicitly represents time, distributed state, and state changes. We outline our research agenda towards developing novel query processing, languages, and optimization techniques that can be used to efficiently and securely query time-aware provenance, even in the presence of transient state or untrusted nodes.Publication NetTrails: A Declarative Platform for Maintaining and Querying Provenance in Distributed Systems(2011-06-01) Zhuo, Wenchao; Fei, Qiong; Haeberlen, Andreas; Sun, Shengzhi; Ives, Zachary G; Tao, Tao; Loo, Boon Thau; Sherr, MicahWe demonstrate NetTrails, a declarative platform for maintaining and interactively querying network provenance in a distributed system. Network provenance describes the history and derivations of network state that result from the execution of a distributed protocol. It has broad applicability in the management, diagnosis, and security analysis of networks. Our demonstration shows the use of NetTrails for maintaining and querying network provenance in a variety of distributed settings, ranging from declarative networks to unmodified legacy distributed systems. We conclude our demonstration with a discussion of our ongoing research on enhancing the query language and security guarantees.Publication Reliable Client Accounting for Hybrid Content-Distribution Networks(2012-04-01) Aditya, Paarijaat; Zhao, Mingchen; Lin, Yin; Haeberlen, Andreas; Druschel, Peter; Maggs, Bruce; Wishon, BillContent distribution networks (CDNs) have started to adopt hybrid designs, which employ both dedicated edge servers and resources contributed by clients. Hybrid designs combine many of the advantages of infrastructurebased and peer-to-peer systems, but they also present new challenges. This paper identifies reliable client accounting as one such challenge. Operators of hybrid CDNs are accountable to their customers (i.e., content providers) for the CDN’s performance. Therefore, they need to offer reliable quality of service and a detailed account of content served. Service quality and accurate accounting, however, depend in part on interactions among untrusted clients. Using the Akamai NetSession client network in a case study, we demonstrate that a small number of malicious clients used in a clever attack could cause significant accounting inaccuracies. We present a method for providing reliable accounting of client interactions in hybrid CDNs. The proposed method leverages the unique characteristics of hybrid systems to limit the loss of accounting accuracy and service quality caused by faulty or compromised clients. We also describe RCA, a system that applies this method to a commercial hybrid content-distribution network. Using trace-driven simulations, we show that RCA can detect and mitigate a variety of attacks, at the expense of a moderate increase in logging overhead.Publication Secure Network Provenance(2011-10-01) Zhou, Wenchao; Fei, Qiong; Haeberlen, Andreas; Narayan, Arjun; Loo, Boon Thau; Sherr, MicahThis paper introduces secure network provenance (SNP), a novel technique that enables networked systems to explain to their operators why they are in a certain state – e.g., why a suspicious routing table entry is present on a certain router, or where a given cache entry originated. SNP provides network forensics capabilities by permitting operators to track down faulty or misbehaving nodes, and to assess the damage such nodes may have caused to the rest of the system. SNP is designed for adversarial settings and is robust to manipulation; its tamper-evident properties ensure that operators can detect when compromised nodes lie or falsely implicate correct nodes. We also present the design of SNooPy, a general-purpose SNP system. To demonstrate that SNooPy is practical, we apply it to three example applications: the Quagga BGP daemon, a declarative implementation of Chord, and Hadoop MapReduce. Our results indicate that SNooPy can efficiently explain state in an adversarial setting, that it can be applied with minimal effort, and that its costs are low enough to be practical.