16,373 research outputs found
Advancing Hardware Security Using Polymorphic and Stochastic Spin-Hall Effect Devices
Protecting intellectual property (IP) in electronic circuits has become a
serious challenge in recent years. Logic locking/encryption and layout
camouflaging are two prominent techniques for IP protection. Most existing
approaches, however, particularly those focused on CMOS integration, incur
excessive design overheads resulting from their need for additional circuit
structures or device-level modifications. This work leverages the innate
polymorphism of an emerging spin-based device, called the giant spin-Hall
effect (GSHE) switch, to simultaneously enable locking and camouflaging within
a single instance. Using the GSHE switch, we propose a powerful primitive that
enables cloaking all the 16 Boolean functions possible for two inputs. We
conduct a comprehensive study using state-of-the-art Boolean satisfiability
(SAT) attacks to demonstrate the superior resilience of the proposed primitive
in comparison to several others in the literature. While we tailor the
primitive for deterministic computation, it can readily support stochastic
computation; we argue that stochastic behavior can break most, if not all,
existing SAT attacks. Finally, we discuss the resilience of the primitive
against various side-channel attacks as well as invasive monitoring at runtime,
which are arguably even more concerning threats than SAT attacks.Comment: Published in Proc. Design, Automation and Test in Europe (DATE) 201
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EASe : integrating search with learned episodes
Weak methods are insufficient to solve complex problems. Constrained weak methods, like hill-climbing, search too little of the problem space. Unconstrained weak methods, like breadth-first search, are intractable. Fortunately, through the integration of multiple weak methods more powerful problem solvers can be created. We demonstrate that augmenting a weak constrained search method with episodes provides a tractable method for solving a large class of problems. We demonstrate that these episodes can be generated using an unconstrained weak method while solving simple problems from a domain. We provide an analytical model of our approach and empirical results from the logic synthesis domain of VLSI design as well as the classic tile-sliding domain
Boolean Delay Equations: A simple way of looking at complex systems
Boolean Delay Equations (BDEs) are semi-discrete dynamical models with
Boolean-valued variables that evolve in continuous time. Systems of BDEs can be
classified into conservative or dissipative, in a manner that parallels the
classification of ordinary or partial differential equations. Solutions to
certain conservative BDEs exhibit growth of complexity in time. They represent
therewith metaphors for biological evolution or human history. Dissipative BDEs
are structurally stable and exhibit multiple equilibria and limit cycles, as
well as more complex, fractal solution sets, such as Devil's staircases and
``fractal sunbursts``. All known solutions of dissipative BDEs have stationary
variance. BDE systems of this type, both free and forced, have been used as
highly idealized models of climate change on interannual, interdecadal and
paleoclimatic time scales. BDEs are also being used as flexible, highly
efficient models of colliding cascades in earthquake modeling and prediction,
as well as in genetics. In this paper we review the theory of systems of BDEs
and illustrate their applications to climatic and solid earth problems. The
former have used small systems of BDEs, while the latter have used large
networks of BDEs. We moreover introduce BDEs with an infinite number of
variables distributed in space (``partial BDEs``) and discuss connections with
other types of dynamical systems, including cellular automata and Boolean
networks. This research-and-review paper concludes with a set of open
questions.Comment: Latex, 67 pages with 15 eps figures. Revised version, in particular
the discussion on partial BDEs is updated and enlarge
Time-delayed models of gene regulatory networks
We discuss different mathematical models of gene regulatory networks as relevant to the onset and development of cancer. After discussion of alternativemodelling approaches, we use a paradigmatic two-gene network to focus on the role played by time delays in the dynamics of gene regulatory networks. We contrast the dynamics of the reduced model arising in the limit of fast mRNA dynamics with that of the full model. The review concludes with the discussion of some open problems
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