Publications

Forthcoming
X. Han, et al., “SIGL: Securing Software Installations Through Deep Graph Learning,” in USENIX Security 2021, Forthcoming.Abstract
Many users implicitly assume that software can only be exploited after it is installed. However, recent supply-chain attacks demonstrate that application integrity must be ensured during installation itself. We introduce SIGL, a new tool for detecting malicious behavior during software installation. SIGL collects traces of system call activity, building a data provenance graph that it analyzes using a novel autoencoder architecture with a graph long short-term memory network (graph LSTM) for the encoder and a standard multilayer perceptron for the decoder. SIGL flags suspicious installations as well as the specific installation-time processes that are likely to be malicious. Using a test corpus of 625 malicious installers containing real-world malware, we demonstrate that SIGL has a detection accuracy of 96%, outperforming similar systems from industry and academia by up to 87% in precision and recall and 45% in accuracy. We also demonstrate that SIGL can pinpoint the processes most likely to have triggered malicious behavior, works on different audit platforms and operating systems, and is robust to training data contamination and adversarial attack. It can be used with application-specific models, even in the presence of new software versions, as well as application-agnostic meta-models that encompass a wide range of applications and installers.
R. Ko, B. Loring, R. Netravali, and J. Mickens, “Oblique: Accelerating Page Loads Using Symbolic Execution,” in NSDI 2021, Forthcoming.Abstract

Mobile devices are often stuck behind high-latency links. Unfortunately for mobile browsers, latency (not bandwidth) is often the key influence on page load time. Proxy-based web accelerators hide last-mile latency by analyzing a page's content, and informing clients about useful objects to prefetch. However, most accelerators require content providers to divulge cleartext HTTPS data to third-party analysis servers. Acceleration systems can be installed on first-party web servers, avoiding the violation of end-to-end TLS security; however, due to the administrative overhead (and additional VM costs) associated with running an accelerator, many first-party content providers would prefer to outsource the acceleration work---if outsourcing were secure.

In this paper, we introduce Oblique, a third-party web accelerator which enables secure outsourcing of page analysis. Oblique symbolically executes the client-side of a page load, generating a prefetch list of symbolic URLs. Each symbolic URL describes a URL that a client browser would fetch, given user-specific values for cookies, the User-Agent string, and other sensitive variables. Those sensitive values are never revealed to Oblique's analysis server. Instead, during a real page load, the user's browser concretizes URLs by reading sensitive local state; the browser can then prefetch the associated objects. Experiments involving real sites demonstrate that Oblique preserves TLS integrity while providing better performance than state-of-the-art accelerators. For popular sites, Oblique is also financially cheaper in terms of VM costs.

2020
X. Han, J. Mickens, A. Gehani, M. Seltzer, and T. Pasquier, “Xanthus: Push-button Orchestration of Host Provenance Data Collection,” in Workshop on Practical Reproducible Evaluation of Systems (P-RECS), Stockholm, Sweden, 2020. PaperAbstract
Host-based anomaly detectors generate alarms by inspecting audit logs for suspicious behavior. Unfortunately, evaluating these anomaly detectors is hard. There are few high quality, publicly-available audit logs, and there are no pre-existing frameworks that enable push-button creation of realistic system traces. To make trace generation easier, we created Xanthus, an automated tool that orchestrates virtual machines to generate realistic audit logs. Using Xanthus' simple management interface, administrators select a base VM image, configure a particular tracing framework to use within that VM, and define post-launch scripts that collect and save trace data. Once data collection is finished, Xanthus creates a self-describing archive which contains the VM, its configuration parameters, and the collected trace data. We demonstrate that Xanthus hides many of the tedious (yet subtle) orchestration tasks that humans often get wrong; Xanthus avoids mistakes that lead to non-replicable experiments.
V. Gandhi and J. Mickens, “Rethinking Isolation Mechanisms for Datacenter Multitenancy,” in HotCloud 2020, Boston, MA, 2020. PaperAbstract
In theory, trusted execution environments like SGX are promising approaches for isolating datacenter tenants. In practice, the associated hardware primitives suffer from three major problems: side channels induced by microarchitectural co-tenancy; weak guarantees for post-load software integrity; and opaque hardware implementations which prevent third-party security auditing. We explain why these limitations are so problematic for datacenters, and then propose a new approach for trusted execution. This approach, called IME (Isolated Monitor Execution) provides SGX-style memory encryption, but strictly prevents microarchitectural co-tenancy of secure and insecure code. IME also uses a separate, microarchitecturally-isolated pipeline to run dynamic security checks on monitored code, enabling post-load monitoring for security invariants like CFI or type safety. Finally, an IME processor exports a machine-readable description of its microarchitectural implementation, allowing tenants to reason about the security properties of a particular IME instance.
X. Han, T. Pasquier, A. Bates, J. Mickens, and M. Seltzer, “Unicorn: Runtime Provenance-Based Detector for Advanced Persistent Threats,” in NDSS, San Diego, CA, 2020. PaperAbstract
Advanced Persistent Threats (APTs) are difficult to detect due to their "low-and-slow" attack patterns and frequent use of zero-day exploits. We present UNICORN, an anomaly-based APT detector that effectively leverages data provenance analysis. From modeling to detection, UNICORN tailors its design specifically for the unique characteristics of APTs. Through extensive yet time-efficient graph analysis, UNICORN explores provenance graphs that provide rich contextual and historical information to identify stealthy anomalous activities without predefined attack signatures. Using a graph-sketching technique, it summarizes long-running system execution with space efficiency to combat slow-acting attacks that take place over a long time span. UNICORN further improves its detection capability using a novel modeling approach to understand long-term behavior as the system evolves. Our evaluation shows that UNICORN outperforms an existing state-of-the-art APT detection system and detects real-life APT scenarios with high accuracy.
2019
R. Netravali and J. Mickens, “Reverb: Speculative Debugging for Web Applications,” in SOCC 2019, Santa Cruz, CA, 2019. PaperAbstract
Bugs are common in web pages. Unfortunately, traditional debugging primitives like breakpoints are crude tools for understanding the asynchronous, wide-area data flows that bind client-side JavaScript code and server-side application logic. In this paper, we describe Reverb, a powerful new debugger that makes data flows explicit and queryable. Reverb provides three novel features. First, Reverb tracks precise value provenance, allowing a developer to quickly identify the reads and writes to JavaScript state that affected a particular variable’s value. Second, Reverb enables speculative bug fix analysis. A developer can replay a program to a certain point, change code or data in the program, and then resume the replay; Reverb uses the remaining log of nondeterministic events to influence the post-edit replay, allowing the developer to investigate whether the hypothesized bug fix would have helped the original execution run. Third, Reverb supports wide-area debugging for applications whose server-side components use event-driven architectures. By tracking the data flows between clients and servers, Reverb enables speculative replaying of the distributed application.
R. Netravali, A. Sivaraman, J. Mickens, and H. Balakrishnan, “WatchTower: Fast, Secure Mobile Page Loads Using Remote Dependency Resolution,” in MobiSys, Seoul, South Korea, 2019. PaperAbstract
Remote dependency resolution (RDR) is a proxy-driven scheme for reducing mobile page load times; a proxy loads a requested page using a local browser, fetching the page’s resources over fast proxy-origin links instead of a client’s slow last-mile links. In this paper, we describe two fundamental challenges to efficient RDR proxying: the increasing popularity of encrypted HTTPS content, and the fact that, due to time-dependent network conditions and page properties, RDR proxying can actually increase load times. We solve these problems by introducing a new, secure proxying scheme for HTTPS traffic, and by implementing WatchTower, a selective proxying system that uses dynamic models of network conditions and page structures to only enable RDR when it is predicted to help. WatchTower loads pages 21.2%–41.3% faster than state-of-the-art proxies and server push systems, while preserving end-to-end HTTPS security.
F. Wang, R. Ko, and J. Mickens, “Riverbed: Enforcing User-defined Privacy Constraints in Distributed Web Services,” in NSDI, Boston, MA, 2019. PaperAbstract
Riverbed is a new framework for building privacy-respecting web services. Using a simple policy language, users define restrictions on how a remote service can process and store sensitive data. A transparent  Riverbed proxy sits between a user's front-end client (e.g., a web browser) and the back-end server code. The back-end code remotely attests to the proxy, demonstrating that the code respects user policies; in particular, the server code attests that it executes within a  Riverbed-compatible managed runtime that uses IFC to enforce user policies. If attestation succeeds, the proxy releases the user's data, tagging it with the user-defined policies. On the server-side, the  Riverbed runtime places all data with compatible policies into the same universe (i.e., the same isolated instance of the full web service). The universe mechanism allows  Riverbed to work with unmodified, legacy software; unlike prior IFC systems,  Riverbed does not require developers to reason about security lattices, or manually annotate code with labels.  Riverbed imposes only modest performance overheads, with worst-case slowdowns of 10% for several real applications.
2018
J. Larisch, J. Mickens, and E. Kohler, “Alto: Lightweight VMs using Virtualization-aware Managed Runtimes,” in International Conference on Managed Languages & Runtimes (ManLang), Linz, Austria, 2018. PaperAbstract
Virtualization enables datacenter operators to safely run computations that belong to untrusted tenants. An ideal virtual machine has three properties: a small memory footprint; strong isolation from other VMs and the host OS; and the ability to maintain in-memory state across client requests. Unfortunately, modern virtualization technologies cannot provide all three properties at once. In this paper, we explain why, and propose a new virtualization approach, called Alto, that virtualizes at the layer of a managed runtime interface. Through careful design of (1) the application-facing managed interface and (2) the internal runtime architecture, Alto provides VMs that are small, secure, and stateful. Conveniently, Alto also simplifies VM operations like suspension, migration, and resumption. We provide several details about the proposed design, and discuss the remaining challenges that must be solved to fully realize the Alto vision.
R. Ko and J. Mickens, “DeadBolt: Securing IoT Deployments,” in Applied Networking Research Workshop, Montreal, Quebec, Canada, 2018. PaperAbstract

In an IoT deployment, network access policies are a critical determinant of security. Devices that run unpatched or insecure code should not be allowed to communicate with the outside world; furthermore, unknown external hosts should not be able to contact sensitive devices that reside within an IoT deployment.

In this paper, we introduce DeadBolt, a new security framework for managing IoT network access. DeadBolt hides all of the devices in an IoT deployment behind an access point that implements deny-by-default policies for both incoming and outgoing traffic. The DeadBolt AP also forces high-end IoT devices to use remote attestation to gain network access; attestation allows the devices to prove that they run up-to-date, trusted software. For lightweight IoT devices which lack the ability to attest, the DeadBolt AP uses virtual drivers (essentially, security-focused virtual network functions) to protect lightweight device traffic. For example, a virtual driver might provide network intrusion detection, or encrypt device traffic that is natively cleartext. Using these techniques, and several others, DeadBolt can prevent realistic attacks while imposing only modest performance costs.

R. Netravali and J. Mickens, “Remote-Control Caching: Proxy-based URL Rewriting to Decrease Mobile Browsing Bandwidth,” in HotMobile, Tempe, Arizona, 2018. PaperAbstract

Mobile browsers suffer from unnecessary cache misses. The same binary object is often named by multiple URLs which correspond to different cache keys. Furthermore, servers frequently mark objects as uncacheable, even though the objects' content is stable over time.

In this paper, we quantify the excess network traffic that mobile devices generate due to inefficient caching logic. We demonstrate that mobile page loads suffer from more redundant transfers than reported by prior studies which focused on desktop page loads. We then propose a new scheme, called Remote-Control Caching (RC2), in which web proxies (owned by mobile carriers or device manufacturers) track the aliasing relationships between the objects that a client has fetched, and the URLs that were used to fetch those objects. Leveraging knowledge of those aliases, a proxy dynamically rewrites the URLs inside of pages, allowing the client's local browser cache to satisfy a larger fraction of requests. Using a concrete implementation of RC2, we show that, for two loads of a page separated by 8 hours, RC2 reduces bandwidth consumption by a median of 52%. As a result, mobile browsers can save a median of 469 KB per warm-cache page load.

R. Netravali, V. Nathan, J. Mickens, and H. Balakrishnan, “Vesper: Measuring Time-to-Interactivity for Web Pages,” in NSDI, Renton, WA, 2018. PaperAbstract
Everyone agrees that web pages should load more quickly. However, a good definition for ``page load time'' is elusive. We argue that, in a modern web page, load times should be defined with respect to interactivity: a page is ``loaded'' when above-the-fold content is visible and the associated JavaScript event handling state is functional. We define a new load time metric, called Ready Index, which explicitly captures our proposed notion of load time. Defining the metric is straightforward, but actually measuring it is not, since web developers do not explicitly annotate the JavaScript state and the DOM elements which support interactivity. To solve this problem, we introduce Vesper, a tool which rewrites a page's JavaScript and HTML to automatically discover the page's interactive state. Armed with Vesper, we compare Ready Index to prior load time metrics like Speed Index; we find that, across a variety of network conditions, prior metrics underestimate or overestimate the true load time for a page by 24%--64%. We also introduce a tool that optimizes a page for Ready Index, decreasing the median time to page interactivity by 29%--32%.
R. Netravali and J. Mickens, “Prophecy: Accelerating Mobile Page Loads Using Final-state Write Logs,” in NSDI, Renton, WA, 2018. PaperAbstract
Web browsing on mobile devices is expensive in terms of battery drainage and bandwidth consumption. Mobile pages also frequently suffer from long load times due to high-latency cellular connections. In this paper, we introduce Prophecy, a new acceleration technology for mobile pages. Prophecy simultaneously reduces energy costs, bandwidth consumption, and page load times. In Prophecy, web servers precompute the JavaScript heap and the DOM tree for a page; when a mobile browser requests the page, the server returns a write log that contains a single write per JavaScript variable or DOM node. The mobile browser replays the writes to quickly reconstruct the final page state, eliding unnecessary intermediate computations. Prophecy's server-side component generates write logs by tracking low-level data flows between the JavaScript heap and the DOM. Using knowledge of these flows, Prophecy enables optimizations that are impossible for prior web accelerators; for example, Prophecy can generate write logs that interleave DOM construction and JavaScript heap construction, allowing interactive page elements to become functional immediately after they become visible to the mobile user. Experiments with real pages and real phones show that Prophecy reduces median page load time by 53%, energy expenditure by 36%, and bandwidth costs by 21%.
F. Wang and J. Mickens, “Veil: Private Browsing Semantics Without Browser-side Assistance,” in NDSS, San Diego, CA, 2018. PaperAbstract

All popular web browsers offer a "private browsing mode." After a private session terminates, the browser is supposed to remove client-side evidence that the session occurred. Unfortunately, browsers still leak information through the file system, the browser cache, the DNS cache, and on-disk reflections of RAM such as the swap file.

Veil is a new deployment framework that allows web developers to prevent these information leaks, or at least reduce their likelihood. Veil leverages the fact that, even though developers do not control the client-side browser implementation, developers do control 1) the content that is sent to those browsers, and 2) the servers which deliver that content. Veil web sites collectively store their content on Veil's blinding servers instead of on individual, site-specific servers. To publish a new page, developers pass their HTML, CSS, and JavaScript files to Veil's compiler; the compiler transforms the URLs in the content so that, when the page loads on a user's browser, URLs are derived from a secret user key. The blinding service and the Veil page exchange encrypted data that is also protected by the user's key. The result is that Veil pages can safely store encrypted content in the browser cache; furthermore, the URLs exposed to system interfaces like the DNS cache are unintelligible to attackers who do not possess the user's key. To protect against post-session inspection of swap file artifacts, Veil uses heap walking (which minimizes the likelihood that secret data is paged out), content mutation (which garbles in-memory artifacts if they do get swapped out), and DOM hiding (which prevents the browser from learning site-specific HTML, CSS, and JavaScript content in the first place). Veil pages load on unmodified commodity browsers, allowing developers to provide stronger semantics for private browsing without forcing users to install or reconfigure their machines. Veil provides these guarantees even if the user does not visit a page using a browser's native privacy mode; indeed, Veil's protections are stronger than what the browser alone can provide.

2017
F. Wang, Y. Joung, and J. Mickens, “Cobweb: Practical Remote Attestation Using Contextual Graphs,” in SysTEX, Shanghai, China, 2017. PaperAbstract

In theory, remote attestation is a powerful primitive for building distributed systems atop untrusting peers. Unfortunately, the canonical attestation framework defined by the Trusted Computing Group is insufficient to express rich contextual relationships between client-side software components. Thus, attestors and verifiers must rely on ad-hoc mechanisms to handle real-world attestation challenges like attestors that load executables in nondeterministic orders, or verifiers that require attestors to track dynamic information flows between attestor-side components.

In this paper, we survey these practical attestation challenges. We then describe a newattestation framework, named Cobweb, which handles these challenges. The key insight is that real-world attestation is a graph problem. An attestation message is a graph in which each vertex is a software component, and has one or more labels, e.g., the hash value of the component, or the raw file data, or a signature over that data. Each edge in an attestation graph is a contextual relationship, like the passage of time, or a parent/child fork() relationship, or a sender/receiver IPC relationship. Cobweb’s verifier-side policies are graph predicates which analyze contextual relationships. Experiments with real, complex software stacks demonstrate that Cobweb’s abstractions are generic and can support a variety of real-world policies.

2016
R. Netravali, A. Goyal, J. Mickens, and H. Balakrishnan, “Polaris: Faster Page Loads Using Fine-grained Dependency Tracking,” in NSDI, Santa Clara, CA, 2016. PaperAbstract

To load a web page, a browser must fetch and evaluate objects like HTML files and JavaScript source code. Evaluating an object can result in additional objects being fetched and evaluated. Thus, loading a web page requires a browser to resolve a dependency graph; this partial ordering constrains the sequence in which a browser can process individual objects. Unfortunately, many edges in a page’s dependency graph are unobservable by today’s browsers. To avoid violating these hidden dependencies, browsers make conservative assumptions about which objects to process next, leaving the network and CPU underutilized.

We provide two contributions. First, using a new measurement platform called Scout that tracks fine-grained data flows across the JavaScript heap and the DOM, we show that prior, coarse-grained dependency analyzers miss crucial edges: across a test corpus of 200 pages, prior approaches miss 30% of edges at the median, and 118% at the 95th percentile. Second, we quantify the benefits of exposing these new edges to web browsers. We introduce Polaris, a dynamic client-side scheduler that is written in JavaScript and runs on unmodified browsers; using a fully automatic compiler, servers can translate normal pages into ones that load themselves with Polaris. Polaris uses fine-grained dependency graphs to dynamically determine which objects to load, and when. Since Polaris’ graphs have no missing edges, Polaris can aggressively fetch objects in a way that minimizes network round trips. Experiments in a variety of network conditions show that Polaris decreases page load times by 34% at the median, and 59% at the 95th percentile.

F. Wang, J. Mickens, N. Zeldovich, and V. Vaikuntanathan, “Sieve: Cryptographically Enforced Access Control for User Data in Untrusted Clouds,” in NSDI, Santa Clara, CA, 2016. PaperAbstract

Modern web services rob users of low-level control over cloud storage—a user’s single logical data set is scattered across multiple storage silos whose access controls are set by web services, not users. The consequence is that users lack the ultimate authority to determine how their data is shared with other web services.

In this paper, we introduce Sieve, a new platform which selectively (and securely) exposes user data to web services. Sieve has a user-centric storage model: each user uploads encrypted data to a single cloud store, and by default, only the user knows the decryption keys. Given this storage model, Sieve defines an infrastructure to support rich, legacy web applications. Using attribute-based encryption, Sieve allows users to define intuitively understandable access policies that are cryptographically enforceable. Using key homomorphism, Sieve can reencrypt user data on storage providers in situ, revoking decryption keys from web services without revealing new keys to the storage provider. Using secret sharing and two factor authentication, Sieve protects cryptographic secrets against the loss of user devices like smartphones and laptops. The result is that users can enjoy rich, legacy web applications, while benefiting from cryptographically strong controls over which data a web service can access.

2015
D. Li, J. Mickens, S. Nath, and L. Ravindranath, “Domino: Understanding Wide-Area, Asynchronous Event Causality in Web Applications,” in SOCC (short paper), Kohala Coast, Hawai'i, 2015. PaperAbstract

In a modern web application, a single high-level action like a mouse click triggers a flurry of asynchronous events on the client browser and remote web servers. We introduce Domino, a new tool which automatically captures and analyzes end-to-end, asynchronous causal relationship of events that span clients and servers. Using Domino, we found uncharacteristically long event chains in Bing Maps, discovered data races in the WinJS implementation of promises, and developed a new server-side scheduling algorithm for reducing the tail latency of server responses.

T. Chajed, et al., “Amber: Decoupling User Data from Web Applications,” in HotOS, Kartause Ittingen, Switzerland, 2015. PaperAbstract

User-generated content is becoming increasingly common on the Web, but current web applications isolate their users’ data, enabling only restricted sharing and cross-service integration. We believe users should be able to share their data seamlessly between their applications and with other users. To that end, we propose Amber, an architecture that decouples users’ data from applications, while providing applications with powerful global queries to find user data. We demonstrate how multi-user applications, such as e-mail, can use these global queries to efficiently collect and monitor relevant data created by other users. Amber puts users in control of which applications they use with their data and with whom it is shared, and enables a new class of applications by removing the artificial partitioning of users’ data by application.

R. Netravali, et al., “Mahimahi: Accurate Record-and-Replay for HTTP,” in USENIX ATC, Santa Clara, CA, 2015. PaperAbstract

This paper presents Mahimahi, a framework to record traffic from HTTP-based applications, and later replay it under emulated network conditions. Mahimahi improves upon prior record-and-replay frameworks in three ways. First, it is more accurate because it carefully emulates the multi-server nature of Web applications, present in 98% of the Alexa US Top 500 Web pages. Second, it isolates its own network traffic, allowing multiple Mahimahi instances emulating different networks to run concurrently without mutual interference. And third, it is designed as a set of composable shells, providing ease-of-use and extensibility.

We evaluate Mahimahi by: (1) analyzing the performance of HTTP/1.1, SPDY, and QUIC on a corpus of 500 sites, (2) using Mahimahi to understand the reasons why these protocols are suboptimal, (3) developing Cumulus, a cloud-based browser designed to overcome these problems, using Mahimahi both to implement Cumulus by extending one of its shells, and to evaluate it, (4) using Mahimahi to evaluate HTTP multiplexing protocols on multiple performance metrics (page load time and speed index), and (5) describing how others have used Mahimahi.

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