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.

Estimation of average switching activity in combinational and sequential circuits

Abstract: The authors address the problem of estimating the average power dissipated in VLSI combinational and sequential circuits, under random input sequences. Switching activity is strongly affected by gate delays and for this reason a general delay model is used in estimating switching activity. The method takes into account correlation caused at internal gates in the circuit due to reconvergence of input signals. In sequential circuits, the input sequence applied to the combinational portion of the circuit is highly correlated because some of the inputs to the combinational logic are flip-flop outputs representing the state of the circuit. Methods are presented to probabilistically estimate switching activity in sequential circuits. These methods automatically compute the switching rates and correlations between flip-flop outputs. >

Sanctum: Minimal Hardware Extensions for Strong Software Isolation

Abstract: Sanctum offers the same promise as Intel’s Software Guard Extensions (SGX), namely strong provable isolation of software modules running concurrently and sharing resources, but protects against an important class of additional software attacks that infer private information from a program’s memory access patterns. Sanctum shuns unnecessary complexity, leading to a simpler security analysis. We follow a principled approach to eliminating entire attack surfaces through isolation, rather than plugging attack-specific privacy leaks. Most of Sanctum’s logic is implemented in trusted software, which does not perform cryptographic operations using keys, and is easier to analyze than SGX’s opaque microcode, which does. Our prototype targets a Rocket RISC-V core, an open implementation that allows any researcher to reason about its security properties. Sanctum’s extensions can be adapted to other processor cores, because we do not change any major CPU building block. Instead, we add hardware at the interfaces between generic building blocks, without impacting cycle time. Sanctum demonstrates that strong software isolation is achievable with a surprisingly small set of minimally invasive hardware changes, and a very reasonable overhead.

PUF Modeling Attacks on Simulated and Silicon Data

Abstract: We discuss numerical modeling attacks on several proposed strong physical unclonable functions (PUFs). Given a set of challenge-response pairs (CRPs) of a Strong PUF, the goal of our attacks is to construct a computer algorithm which behaves indistinguishably from the original PUF on almost all CRPs. If successful, this algorithm can subsequently impersonate the Strong PUF, and can be cloned and distributed arbitrarily. It breaks the security of any applications that rest on the Strong PUF's unpredictability and physical unclonability. Our method is less relevant for other PUF types such as Weak PUFs. The Strong PUFs that we could attack successfully include standard Arbiter PUFs of essentially arbitrary sizes, and XOR Arbiter PUFs, Lightweight Secure PUFs, and Feed-Forward Arbiter PUFs up to certain sizes and complexities. We also investigate the hardness of certain Ring Oscillator PUF architectures in typical Strong PUF applications. Our attacks are based upon various machine learning techniques, including a specially tailored variant of logistic regression and evolution strategies. Our results are mostly obtained on CRPs from numerical simulations that use established digital models of the respective PUFs. For a subset of the considered PUFs-namely standard Arbiter PUFs and XOR Arbiter PUFs-we also lead proofs of concept on silicon data from both FPGAs and ASICs. Over four million silicon CRPs are used in this process. The performance on silicon CRPs is very close to simulated CRPs, confirming a conjecture from earlier versions of this work. Our findings lead to new design requirements for secure electrical Strong PUFs, and will be useful to PUF designers and attackers alike.

Controlled physical random functions

Abstract: A physical random function (PUF) is a random function that can only be evaluated with the help of a complex physical system. We introduce controlled physical random functions (CPUFs) which are PUFs that can only be accessed via an algorithm that is physically bound to the PUF in an inseparable way. CPUFs can be used to establish a shared secret between a physical device and a remote user. We present protocols that make this possible in a secure and flexible way, even in the case of multiple mutually mistrusting parties. Once established, the shared secret can be used to enable a wide range of applications. We describe certified execution, where a certificate is produced that proves that a specific computation was carried out on a specific processor. Certified execution has many benefits, including protection against malicious nodes in distributed computation networks. We also briefly discuss a software licensing application.

Dynamic Partitioning of Shared Cache Memory

Abstract: This paper proposes dynamic cache partitioning amongst simultaneously executing processes/threads. We present a general partitioning scheme that can be applied to set-associative caches. Since memory reference characteristics of processes/threads can change over time, our method collects the cache miss characteristics of processes/threads at run-time. Also, the workload is determined at run-time by the operating system scheduler. Our scheme combines the information, and partitions the cache amongst the executing processes/threads. Partition sizes are varied dynamically to reduce the total number of misses. The partitioning scheme has been evaluated using a processor simulator modeling a two-processor CMP system. The results show that the scheme can improve the total IPC significantly over the standard least recently used (LRU) replacement policy. In a certain case, partitioning doubles the total IPC over standard LRU. Our results show that smart cache management and scheduling is essential to achieve high performance with shared cache memory.

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.