Srinivas Devadas

Bio: Srinivas Devadas is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Sequential logic & Combinational logic. The author has an hindex of 88, co-authored 480 publications receiving 31897 citations. Previous affiliations of Srinivas Devadas include University of California, Berkeley & Cornell University.

Automatic Verification of Pipelined Microprocessors

Abstract: We address the problem of automatically verifying large digital designs at the logic level, against high-level specifications. In this paper, we present a methodology which allows for the verification of a specific class of synchronous machines, namely pipelined microprocessors. The specification is the instruction set of the microprocessor with respect to which the correctness property is to be verified. A relation, namely the β-relation, is established between the input/output behavior of the implementation and specification. The relation corresponds to changes in the input/output behavior that result from pipelining, and takes into account data hazards and control transfer instructions that modify pipelined execution. The correctness requirement is that the β-relation hold between the implementation and specification. We use symbolic simulation of the specification and implementation to verify their functional equivalence. We characterize the pipelined and unpipelined microprocessors as definite machines (i.e. a machine in which for some constant k, the output of the machine depends only on the last k inputs) for verification purposes. We show that only a small number of cycles, rather than exhaustive state transition graph traversal and state enumeration, have to be simulated for each machine to verify whether the implementation is in β-relation with the specification. Experimental results are presented.

PUF Authentication and Key-Exchange by Substring Matching

Abstract: Mechanisms for operating a prover device and a verifier device so that the verifier device can verify the authenticity of the prover device. The prover device generates a data string by: (a) submitting a challenge to a physical unclonable function (PUF) to obtain a response string, (b) selecting a substring from the response string, (c) injecting the selected substring into the data string, and (d) injecting random bits into bit positions of the data string not assigned to the selected substring. The verifier: (e) generates an estimated response string by evaluating a computational model of the PUF based on the challenge; (f) performs a search process to identify the selected substring within the data string using the estimated response string; and (g) determines whether the prover device is authentic based on a measure of similarity between the identified substring and a corresponding substring of the estimated response string.

Synthesis of hazard-free multilevel logic under multiple-input changes from binary decision diagrams

Abstract: We describe a new method for directly synthesizing a hazard-free multilevel logic implementation from a given logic specification. The method is based on free/ordered Binary Decision Diagrams (BDD's), and is naturally applicable to multiple-output logic functions. Given an incompletely-specified (multiple-output) Boolean function, the method produces a multilevel logic network that is hazard-free for a specified set of multiple-input changes. We assume an arbitrary (unbounded) gate and wire delay model under a pure delay (PD) assumption, we permit multiple-input changes, and we consider both static and dynamic hazards under the fundamental-mode assumption. Our framework is thus general and powerful. While it is not always possible to generate hazard-free implementations using our technique, we show that in some cases hazard-free multilevel implementations can be generated when hazard-free two-level representations cannot be found. This problem is generally regarded as a difficult problem and it has important applications in the field of asynchronous design. The method has been automated and applied to a number of examples. >

FPGA Implementation of a Cryptographically-Secure PUF Based on Learning Parity with Noise

Abstract: Herder et al. (IEEE Transactions on Dependable and Secure Computing, 2017) designed a new computational fuzzy extractor and physical unclonable function (PUF) challenge-response protocol based on the Learning Parity with Noise (LPN) problem. The protocol requires no irreversible state updates on the PUFs for security, like burning irreversible fuses, and can correct for significant measurement noise when compared to PUFs using a conventional (information theoretical secure) fuzzy extractor. However, Herder et al. did not implement their protocol. In this paper, we give the first implementation of a challenge response protocol based on computational fuzzy extractors. Our main insight is that “confidence information” does not need to be kept private, if the noise vector is independent of the confidence information, e.g., the bits generated by ring oscillator pairs which are physically placed close to each other. This leads to a construction which is a simplified version of the design of Herder et al. (also building on a ring oscillator PUF). Our simplifications allow for a dramatic reduction in area by making a mild security assumption on ring oscillator physical obfuscated key output bits.

TaintDroid: An Information-Flow Tracking System for Realtime Privacy Monitoring on Smartphones

Abstract: Today’s smartphone operating systems frequently fail to provide users with visibility into how third-party applications collect and share their private data. We address these shortcomings with TaintDroid, an efficient, system-wide dynamic taint tracking and analysis system capable of simultaneously tracking multiple sources of sensitive data. TaintDroid enables realtime analysis by leveraging Android’s virtualized execution environment. TaintDroid incurs only 32p performance overhead on a CPU-bound microbenchmark and imposes negligible overhead on interactive third-party applications. Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, in our 2010 study we found 20 applications potentially misused users’ private information; so did a similar fraction of the tested applications in our 2012 study. Monitoring the flow of privacy-sensitive data with TaintDroid provides valuable input for smartphone users and security service firms seeking to identify misbehaving applications.

TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones

Abstract: Today's smartphone operating systems frequently fail to provide users with adequate control over and visibility into how third-party applications use their private data. We address these shortcomings with TaintDroid, an efficient, system-wide dynamic taint tracking and analysis system capable of simultaneously tracking multiple sources of sensitive data. TaintDroid provides realtime analysis by leveraging Android's virtualized execution environment. TaintDroid incurs only 14% performance overhead on a CPU-bound micro-benchmark and imposes negligible overhead on interactive third-party applications. Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, we found 68 instances of potential misuse of users' private information across 20 applications. Monitoring sensitive data with TaintDroid provides informed use of third-party applications for phone users and valuable input for smartphone security service firms seeking to identify misbehaving applications.

Symbolic Boolean manipulation with ordered binary-decision diagrams

Abstract: Ordered Binary-Decision Diagrams (OBDDs) represent Boolean functions as directed acyclic graphs. They form a canonical representation, making testing of functional properties such as satisfiability and equivalence straightforward. A number of operations on Boolean functions can be implemented as graph algorithms on OBDD data structures. Using OBDDs, a wide variety of problems can be solved through symbolic analysis. First, the possible variations in system parameters and operating conditions are encoded with Boolean variables. Then the system is evaluated for all variations by a sequence of OBDD operations. Researchers have thus solved a number of problems in digital-system design, finite-state system analysis, artificial intelligence, and mathematical logic. This paper describes the OBDD data structure and surveys a number of applications that have been solved by OBDD-based symbolic analysis.

Physical unclonable functions for device authentication and secret key generation

Abstract: Physical Unclonable Functions (PUFs) are innovative circuit primitives that extract secrets from physical characteristics of integrated circuits (ICs). We present PUF designs that exploit inherent delay characteristics of wires and transistors that differ from chip to chip, and describe how PUFs can enable low-cost authentication of individual ICs and generate volatile secret keys for cryptographic operations.