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.

Maximum-likelihood decoding of device-specific multi-bit symbols for reliable key generation

Abstract: We present a PUF key generation scheme that uses the provably optimal method of maximum-likelihood (ML) detection on symbols derived from PUF response bits. Each device forms a noisy, device-specific symbol constellation, based on manufacturing variation. Each detected symbol is a letter in a codeword of an error correction code, resulting in non-binary codewords. We present a three-pronged validation strategy: i. mathematical (deriving an optimal symbol decoder), ii. simulation (comparing against prior approaches), and iii. empirical (using implementation data). We present simulation results demonstrating that for a given PUF noise level and block size (an estimate of helper data size), our new symbol-based ML approach can have orders of magnitude better bit error rates compared to prior schemes such as block coding, repetition coding, and threshold-based pattern matching, especially under high levels of noise due to extreme environmental variation. We demonstrate environmental reliability of a ML symbol-based soft-decision error correction approach in 28nm FPGA silicon, covering −65°C to 105°C ambient (and including 125°C junction), and with 128bit key regeneration error probability ≤ 1 ppm.

Heuristic minimization of Boolean relations using testing techniques

Abstract: Minimization of Boolean relations is important from the point of view of synthesis, especially in synthesis for testability. A very fast heuristic procedure for finding an optimal sum-of-products representation for a Boolean relation is described. Starting with a function compatible with the relation, a process of iterative logic improvement based on test generation techniques is used to derive a minimal function compatible with the Boolean relation. >

Tardis: Time Traveling Coherence Algorithm for Distributed Shared Memory

Abstract: A new memory coherence protocol, Tardis, is proposed. Tardis uses timestamp counters representing logical time as well as physical time to order memory operations and enforce sequential consistency in any type of shared memory system. Tardis is unique in that as compared to the widely-adopted directory coherence protocol, and its variants, it completely avoids multicasting and only requires O(log N) storage per cache block for an N-core system rather than O(N) sharer information. Tardis is simpler and easier to reason about, yet achieves similar performance to directory protocols on a wide range of benchmarks run on 16, 64 and 256 cores.

Easily testable PLA-based finite state machines

Abstract: An outline is presented of a synthesis procedure that, beginning from a state transition graph (STG) description of a sequential machine, produces an optimized easily testable programmable logic array (PLA) based logic implementation. Previous approaches to synthesizing easily testable sequential machines have concentrated on the stuck-at-fault model; for PLAs, an extended fault model called the crosspoint fault model has been used. The authors propose a procedure of constrained state assignment and logic optimization which guarantees testability for all combinationally irredundant crosspoint faults in a PLA-based finite-state machine. No direct access to the flip-flops is required. The test sequences to detect these faults can be obtained using combinational test generation techniques alone. This procedure thus represents an alternative to a scan design methodology. Results are presented which show that the area/performance penalties in return for easy testability are small. >

Time-Predictable Computer Architecture for Cyber-Physical Systems: Digital Emulation of Power Electronics Systems

Abstract: The smart grid concept is a good example of a complex cyber-physical system (CPS) that exhibits intricate interplay between control, sensing, and communication infrastructure on one side, and power processing and actuation on the other side. The more extensive use of computation, sensing, and communication, tightly coupled with power processing, calls for a fundamental reassessment of some of the prevailing paradigms in the real-time control and communication abstractions. Today these abstractions are mostly thought of as embedded systems, and the overall framework needs to be reformed in order to fully realize the potential of the emerging field of cyber-physical systems. This paper details the design and application of a new ultrahigh speed real-time emulation platform for Hardware-in-the-Loop (HiL) testing and design of high-power power electronics systems. Our real-time hardware emulation for HiL systems is based on a reconfigurable, heterogeneous, multicore processor architecture that emulates power electronics, and includes a circuit compiler that translates graphic system models into processor executable machine code. We present the hardware architecture, and describe the process of power electronic circuit compilation. This approach yields real-time execution on the order of 1µs simulation time step (including input/output latency) for a broad class of power electronics converters. To the best of our knowledge, no current academic or industrial HiL system has such a fast emulation response time. We present HiL experimental results for three representative systems: a variable speed induction motor drive, a utility grid connected photovoltaic converter system, and a hybrid electric vehicle motor drive.

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.