Bryan Parno

Distributed detection of node replication attacks in sensor networks

The low-cost, off-the-shelf hardware components in unshielded sensor-network nodes leave them vulnerable to compromise. With little effort, an adversary may capture nodes, analyze and replicate them, and surreptitiously insert these replicas at strategic locations within the network. Such attacks may have severe consequences; they may allow the adversary to corrupt network data or even disconnect significant parts of the network. Previous node replication detection schemes depend primarily on centralized mechanisms with single points of failure, or on neighborhood voting protocols that fail to detect distributed replications. To address these fundamental limitations, we propose two new algorithms based on emergent properties (Gligor (2004)), i.e., properties that arise only through the collective action of multiple nodes. Randomized multicast distributes node location information to randomly-selected witnesses, exploiting the birthday paradox to detect replicated nodes, while line-selected multicast uses the topology of the network to detect replication. Both algorithms provide globally-aware, distributed node-replica detection, and line-selected multicast displays particularly strong performance characteristics. We show that emergent algorithms represent a promising new approach to sensor network security; moreover, our results naturally extend to other classes of networks in which nodes can be captured, replicated and re-inserted by an adversary.

Flicker: an execution infrastructure for tcb minimization

We present Flicker, an infrastructure for executing security-sensitive code in complete isolation while trusting as few as 250 lines of additional code. Flicker can also provide meaningful, fine-grained attestation of the code executed (as well as its inputs and outputs) to a remote party. Flicker guarantees these properties even if the BIOS, OS and DMA-enabled devices are all malicious. Flicker leverages new commodity processors from AMD and Intel and does not require a new OS or VMM. We demonstrate a full implementation of Flicker on an AMD platform and describe our development environment for simplifying the construction of Flicker-enabled code.

Pinocchio: Nearly Practical Verifiable Computation

To instill greater confidence in computations outsourced to the cloud, clients should be able to verify the correctness of the results returned. To this end, we introduce Pinocchio, a built system for efficiently verifying general computations while relying only on cryptographic assumptions. With Pinocchio, the client creates a public evaluation key to describe her computation; this setup is proportional to evaluating the computation once. The worker then evaluates the computation on a particular input and uses the evaluation key to produce a proof of correctness. The proof is only 288 bytes, regardless of the computation performed or the size of the inputs and outputs. Anyone can use a public verification key to check the proof. Crucially, our evaluation on seven applications demonstrates that Pinocchio is efficient in practice too. Pinocchios verification time is typically 10ms: 5-7 orders of magnitude less than previous work; indeed Pinocchio is the first general-purpose system to demonstrate verification cheaper than native execution (for some apps). Pinocchio also reduces the workers proof effort by an additional 19-60x. As an additional feature, Pinocchio generalizes to zero-knowledge proofs at a negligible cost over the base protocol. Finally, to aid development, Pinocchio provides an end-to-end toolchain that compiles a subset of C into programs that implement the verifiable computation protocol.

Quadratic Span Programs and Succinct NIZKs without PCPs

We introduce a new characterization of the NP complexity class, called Quadratic Span Programs (QSPs), which is a natural extension of span programs defined by Karchmer and Wigderson. Our main motivation is the quick construction of succinct, easily verified arguments for NP statements.

User-Driven Access Control: Rethinking Permission Granting in Modern Operating Systems

Modern client platforms, such as iOS, Android, Windows Phone, Windows 8, and web browsers, run each application in an isolated environment with limited privileges. A pressing open problem in such systems is how to allow users to grant applications access to user-owned resources, e.g., to privacy- and cost-sensitive devices like the camera or to user data residing in other applications. A key challenge is to enable such access in a way that is non-disruptive to users while still maintaining least-privilege restrictions on applications. In this paper, we take the approach of user-driven access control, whereby permission granting is built into existing user actions in the context of an application, rather than added as an afterthought via manifests or system prompts. To allow the system to precisely capture permission-granting intent in an applications context, we introduce access control gadgets (ACGs). Each user-owned resource exposes ACGs for applications to embed. The users authentic UI interactions with an ACG grant the application permission to access the corresponding resource. Our prototyping and evaluation experience indicates that user-driven access control is a promising direction for enabling in-context, non-disruptive, and least-privilege permission granting on modern client platforms.

Pinocchio: nearly practical verifiable computation

To instill greater confidence in computations outsourced to the cloud, clients should be able to verify the correctness of the results returned. To this end, we introduce Pinocchio, a built system for efficiently verifying general computations while relying only on cryptographic assumptions. With Pinocchio, the client creates a public evaluation key to describe her computation; this setup is proportional to evaluating the computation once. The worker then evaluates the computation on a particular input and uses the evaluation key to produce a proof of correctness. The proof is only 288 bytes, regardless of the computation performed or the size of the inputs and outputs. Anyone can use a public verification key to check the proof. Crucially, our evaluation on seven applications demonstrates that Pinocchio is efficient in practice too. Pinocchios verification time is typically 10ms: 5-7 orders of magnitude less than previous work; indeed Pinocchio is the first general-purpose system to demonstrate verification cheaper than native execution (for some apps). Pinocchio also reduces the workers proof effort by an additional 19-60x. As an additional feature, Pinocchio generalizes to zero-knowledge proofs at a negligible cost over the base protocol. Finally, to aid development, Pinocchio provides an end-to-end toolchain that compiles a subset of C into programs that implement the verifiable computation protocol.

Portcullis: protecting connection setup from denial-of-capability attacks

Systems using capabilities to provide preferential service to selected flows have been proposed as a defense against large-scale network denial-of-service attacks. While these systems offer strong protection for established network flows, the Denial-of-Capability (DoC) attack, which prevents new capability-setup packets from reaching the destination, limits the value of these systems. Portcullis mitigates DoC attacks by allocating scarce link bandwidth for connection establishment packets based on per-computation fairness. We prove that a legitimate sender can establish a capability with high probability regardless of an attackers resources or strategy and that no system can improve on our guarantee. We simulate full and partial deployments of Portcullis on an Internet-scale topology to confirm our theoretical results and demonstrate the substantial benefits of using per-computation fairness.

How to delegate and verify in public: verifiable computation from attribute-based encryption

The wide variety of small, computationally weak devices, and the growing number of computationally intensive tasks makes it appealing to delegate computation to data centers. However, outsourcing computation is useful only when the returned result can be trusted, which makes verifiable computation (VC) a must for such scenarios. In this work we extend the definition of verifiable computation in two important directions: public delegation and public verifiability, which have important applications in many practical delegation scenarios. Yet, existing VC constructions based on standard cryptographic assumptions fail to achieve these properties. As the primary contribution of our work, we establish an important (and somewhat surprising) connection between verifiable computation and attribute-based encryption (ABE), a primitive that has been widely studied. Namely, we show how to construct a VC scheme with public delegation and public verifiability from any ABE scheme. The VC scheme verifies any function in the class of functions covered by the permissible ABE policies (currently Boolean formulas). This scheme enjoys a very efficient verification algorithm that depends only on the output size. Efficient delegation, however, requires the ABE encryption algorithm to be cheaper than the original function computation. Strengthening this connection, we show a construction of a multi-function verifiable computation scheme from an ABE scheme with outsourced decryption, a primitive defined recently by Green, Hohenberger and Waters (USENIX Security 2011). A multi-function VC scheme allows the verifiable evaluation of multiple functions on the same preprocessed input. In the other direction, we also explore the construction of an ABE scheme from verifiable computation protocols.

Phoolproof phishing prevention

Phishing, or web spoofing, is a growing problem: the Anti-Phishing Working Group (APWG) received almost 14,000 unique phishing reports in August 2005, a 56% jump over the number of reports in December 2004 [3]. For financial institutions, phishing is a particularly insidious problem, since trust forms the foundation for customer relationships, and phishing attacks undermine confidence in an institution. Phishing attacks succeed by exploiting a users inability to distinguish legitimate sites from spoofed sites. Most prior research focuses on assisting the user in making this distinction; however, users must make the right security decision every time. Unfortunately, humans are ill-suited for performing the security checks necessary for secure site identification, and a single mistake may result in a total compromise of the users online account. Fundamentally, users should be authenticated using information that they cannot readily reveal to malicious parties. Placing less reliance on the user during the authentication process will enhance security and eliminate many forms of fraud. We propose using a trusted device to perform mutual authentication that eliminates reliance on perfect user behavior, thwarts Man-in-the-Middle attacks after setup, and protects a users account even in the presence of keyloggers and most forms of spyware.We demonstrate the practicality of our system with a prototype implementation.

Memoir: Practical State Continuity for Protected Modules

To protect computation, a security architecture must safeguard not only the software that performs it but also the state on which the software operates. This requires more than just preserving state confidentiality and integrity, since, e.g., software may err if its state is rolled back to a correct but stale version. For this reason, we present Memoir, the first system that fully ensures the continuity of a protected software modules state. In other words, it ensures that a modules state remains persistently and completely inviolate. A key contribution of Memoir is a technique to ensure rollback resistance without making the system vulnerable to system crashes. It does this by using a deterministic module, storing a concise summary of the modules request history in protected NVRAM, and allowing only safe request replays after crashes. Since frequent NVRAM writes are impractical on modern hardware, we present a novel way to leverage limited trusted hardware to minimize such writes. To ensure the correctness of our design, we develop formal, machine-verified proofs of safety. To demonstrate Memoirs practicality, we have built it and conducted evaluations demonstrating that it achieves reasonable performance on real hardware. Furthermore, by building three useful Memoir-protected modules that rely critically on state continuity, we demonstrate Memoirs versatility.