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.

A Formal Foundation for Secure Remote Execution of Enclaves

Abstract: Recent proposals for trusted hardware platforms, such as Intel SGX and the MIT Sanctum processor, offer compelling security features but lack formal guarantees. We introduce a verification methodology based on a trusted abstract platform (TAP), a formalization of idealized enclave platforms along with a parameterized adversary. We also formalize the notion of secure remote execution and present machine-checked proofs showing that the TAP satisfies the three key security properties that entail secure remote execution: integrity, confidentiality and secure measurement. We then present machine-checked proofs showing that SGX and Sanctum are refinements of the TAP under certain parameterizations of the adversary, demonstrating that these systems implement secure enclaves for the stated adversary models.

Circuit fingerprinting attacks: passive deanonymization of tor hidden services

Abstract: This paper sheds light on crucial weaknesses in the design of hidden services that allow us to break the anonymity of hidden service clients and operators passively. In particular, we show that the circuits, paths established through the Tor network, used to communicate with hidden services exhibit a very different behavior compared to a general circuit. We propose two attacks, under two slightly different threat models, that could identify a hidden service client or operator using these weaknesses. We found that we can identify the users' involvement with hidden services with more than 98% true positive rate and less than 0.1% false positive rate with the first attack, and 99% true positive rate and 0.07% false positive rate with the second. We then revisit the threat model of previous website fingerprinting attacks, and show that previous results are directly applicable, with greater efficiency, in the realm of hidden services. Indeed, we show that we can correctly determine which of the 50 monitored pages the client is visiting with 88% true positive rate and false positive rate as low as 2.9%, and correctly deanonymize 50 monitored hidden service servers with true positive rate of 88% and false positive rate of 7.8% in an open world setting.

Statistical timing analysis of combinational logic circuits

Abstract: Efficient methods for computing an exact probability distribution of the delay of a combinational circuit, given probability distributions for the gate and wire delays, are developed. The derived distribution can give the probability that a combinational circuit will achieve a certain performance, across the possible range. This information can then be used to predict the expected performance of the entire circuit. The techniques presented target fast analysis as well as reduced memory requirements. The notion of a correct approximation, based on convex inequality, which never overestimates the percentage of circuits that will achieve any given performance is defined. It is shown that given the assumption that all the topologically longest paths are responsible for the delay, the computation technique provides a correct probabilistic measure in the sense given above. Methods are given to identify and to ignore false paths in the probabilistic analysis, so as to obtain correct and less pessimistic answers to the performance prediction question. Some practical results are given for a number of benchmark combinational circuits. >

Decomposition and factorization of sequential finite state machines

Abstract: Algorithms are proposed for decomposing a finite-state machine into smaller interacting machines so as to optimize area and performance of the eventual logic implementation Cascade decomposition algorithms, which decompose a given machine into independent and dependent components, have been proposed in the past The authors propose a more powerful form of decomposition where both components of the decomposed machine interact with each other Experimental results indicate that this decomposition technique for state machine decomposition is superior to cascade decomposition techniques It is the premise of this study that optimal state assignment corresponds to finding an optimal multiple general decomposition of a finite-state machine State assignment techniques that target two-level and multilevel implementations based on state machine factorization algorithms followed by state assignment algorithms are presented It is rigorously proved that one-hot encoding a nontrivially factored machine is guaranteed to produce a better result than one-hot encoding the original machine for the two-level case >

Synthesis of robust delay-fault-testable circuits: theory

Abstract: The authors give a comprehensive theoretical framework for the analysis and synthesis of delay-fault-testable combinational logic circuits. For each of the common models of delay-fault testability, robust gate-delay faults and robust path-delay faults, they provide the necessary and sufficient conditions for complete testability under that model for two-level circuits. The authors describe the conditions in terminology common to two-level minimization and show their relationship to properties produced by two-level minimizers. Similar conditions for multilevel networks are presented. It is shown that constrained algebraic factorization is required to retain complete gate-delay-fault testability beginning from a two-level network. The authors present preliminary experimental results using these synthesis techniques. >

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.