18,346 research outputs found
Trick or Heat? Manipulating Critical Temperature-Based Control Systems Using Rectification Attacks
Temperature sensing and control systems are widely used in the closed-loop
control of critical processes such as maintaining the thermal stability of
patients, or in alarm systems for detecting temperature-related hazards.
However, the security of these systems has yet to be completely explored,
leaving potential attack surfaces that can be exploited to take control over
critical systems.
In this paper we investigate the reliability of temperature-based control
systems from a security and safety perspective. We show how unexpected
consequences and safety risks can be induced by physical-level attacks on
analog temperature sensing components. For instance, we demonstrate that an
adversary could remotely manipulate the temperature sensor measurements of an
infant incubator to cause potential safety issues, without tampering with the
victim system or triggering automatic temperature alarms. This attack exploits
the unintended rectification effect that can be induced in operational and
instrumentation amplifiers to control the sensor output, tricking the internal
control loop of the victim system to heat up or cool down. Furthermore, we show
how the exploit of this hardware-level vulnerability could affect different
classes of analog sensors that share similar signal conditioning processes.
Our experimental results indicate that conventional defenses commonly
deployed in these systems are not sufficient to mitigate the threat, so we
propose a prototype design of a low-cost anomaly detector for critical
applications to ensure the integrity of temperature sensor signals.Comment: Accepted at the ACM Conference on Computer and Communications
Security (CCS), 201
Collective behaviours: from biochemical kinetics to electronic circuits
In this work we aim to highlight a close analogy between cooperative
behaviors in chemical kinetics and cybernetics; this is realized by using a
common language for their description, that is mean-field statistical
mechanics. First, we perform a one-to-one mapping between paradigmatic
behaviors in chemical kinetics (i.e., non-cooperative, cooperative,
ultra-sensitive, anti-cooperative) and in mean-field statistical mechanics
(i.e., paramagnetic, high and low temperature ferromagnetic,
anti-ferromagnetic). Interestingly, the statistical mechanics approach allows a
unified, broad theory for all scenarios and, in particular, Michaelis-Menten,
Hill and Adair equations are consistently recovered. This framework is then
tested against experimental biological data with an overall excellent
agreement. One step forward, we consistently read the whole mapping from a
cybernetic perspective, highlighting deep structural analogies between the
above-mentioned kinetics and fundamental bricks in electronics (i.e.
operational amplifiers, flashes, flip-flops), so to build a clear bridge
linking biochemical kinetics and cybernetics.Comment: 15 pages, 6 figures; to appear on Scientific Reports: Nature
Publishing Grou
Experimental observation of extreme multistability in an electronic system of two coupled R\"{o}ssler oscillators
We report the first experimental observation of extreme multistability in a
controlled laboratory investigation. Extreme multistability arises when
infinitely many attractors coexist for the same set of system parameters. The
behavior was predicted earlier on theoretical grounds, supported by numerical
studies of models of two coupled identical or nearly identical systems. We
construct and couple two analog circuits based on a modified coupled
R\"{o}ssler system and demonstrate the occurrence of extreme multistability
through a controlled switching to different attractor states purely through a
change in initial conditions for a fixed set of system parameters. Numerical
studies of the coupled model equations are in agreement with our experimental
findings.Comment: to be published in Phys. Rev.
Understanding and Design of an Arduino-based PID Controller
This thesis presents research and design of a Proportional, Integral, and Derivative (PID) controller that uses a microcontroller (Arduino) platform. The research part discusses the structure of a PID algorithm with some motivating work already performed with the Arduino-based PID controller from various fields. An inexpensive Arduino-based PID controller designed in the laboratory to control the temperature, consists of hardware parts: Arduino UNO, thermoelectric cooler, and electronic components while the software portion includes C/C++ programming. The PID parameters for a particular controller are found manually. The role of different PID parameters is discussed with the subsequent comparison between different modes of PID controllers. The designed system can effectively measure the temperature with an error of ± 0.6℃ while a stable temperature control with only slight deviation from the desired value (setpoint) is achieved. The designed system and concepts learned from the control system serve in pursuing inexpensive and precise ways to control physical parameters within a desired range in our laboratory
A walk in the statistical mechanical formulation of neural networks
Neural networks are nowadays both powerful operational tools (e.g., for
pattern recognition, data mining, error correction codes) and complex
theoretical models on the focus of scientific investigation. As for the
research branch, neural networks are handled and studied by psychologists,
neurobiologists, engineers, mathematicians and theoretical physicists. In
particular, in theoretical physics, the key instrument for the quantitative
analysis of neural networks is statistical mechanics. From this perspective,
here, we first review attractor networks: starting from ferromagnets and
spin-glass models, we discuss the underlying philosophy and we recover the
strand paved by Hopfield, Amit-Gutfreund-Sompolinky. One step forward, we
highlight the structural equivalence between Hopfield networks (modeling
retrieval) and Boltzmann machines (modeling learning), hence realizing a deep
bridge linking two inseparable aspects of biological and robotic spontaneous
cognition. As a sideline, in this walk we derive two alternative (with respect
to the original Hebb proposal) ways to recover the Hebbian paradigm, stemming
from ferromagnets and from spin-glasses, respectively. Further, as these notes
are thought of for an Engineering audience, we highlight also the mappings
between ferromagnets and operational amplifiers and between antiferromagnets
and flip-flops (as neural networks -built by op-amp and flip-flops- are
particular spin-glasses and the latter are indeed combinations of ferromagnets
and antiferromagnets), hoping that such a bridge plays as a concrete
prescription to capture the beauty of robotics from the statistical mechanical
perspective.Comment: Contribute to the proceeding of the conference: NCTA 2014. Contains
12 pages,7 figure
Complete integrability of information processing by biochemical reactions
Statistical mechanics provides an effective framework to investigate
information processing in biochemical reactions. Within such framework
far-reaching analogies are established among (anti-) cooperative collective
behaviors in chemical kinetics, (anti-)ferromagnetic spin models in statistical
mechanics and operational amplifiers/flip-flops in cybernetics. The underlying
modeling -- based on spin systems -- has been proved to be accurate for a wide
class of systems matching classical (e.g. Michaelis--Menten, Hill, Adair)
scenarios in the infinite-size approximation. However, the current research in
biochemical information processing has been focusing on systems involving a
relatively small number of units, where this approximation is no longer valid.
Here we show that the whole statistical mechanical description of reaction
kinetics can be re-formulated via a mechanical analogy -- based on completely
integrable hydrodynamic-type systems of PDEs -- which provides explicit
finite-size solutions, matching recently investigated phenomena (e.g.
noise-induced cooperativity, stochastic bi-stability, quorum sensing). The
resulting picture, successfully tested against a broad spectrum of data,
constitutes a neat rationale for a numerically effective and theoretically
consistent description of collective behaviors in biochemical reactions.Comment: 24 pages, 10 figures; accepted for publication in Scientific Report
Developing a framework of non-fatal occupational injury surveillance for risk control in palm oil mills
Non-fatal occupational injury (NFOI) and its risk factors have become a current global
concern. The need of research towards the relationship between occupational injury
and its risk factor is essential, to fulfil the purpose and setting the priority of
implementing safety preventive approaches at workplace. This research intended to
develop a framework of NFOI surveillance by using epidemiological data, noise
exposure data and NFOI data among palm oil mills’ workers. A total of 420
respondents who assigned in operation and processing areas (OP) (n=333) and general
or office workers (n=87) had voluntary participated in this research. A questionnaire
session with respondents was held to obtain epidemiological data and NFOI
information via validated questionnaire. Noise hazard monitoring was executed by
using Sound Level Meter (SLM) for environmental noise monitoring and Personal
Sound Dosimeter for personal noise monitoring. Gathered data were analysed in
quantitative method by using statistical software IBM SPSS Statistic version 21 and a
risk matrix table for injury risk rating evaluation. It was discovered that high noise
exposure level (≥ 85 dB[A]) was significantly associated with non-fatal occupational
injury among OP workers (φ=0.123, p<0.05) with OR=1.87 (95% CI, 1.080-3.235,
p<0.05). Risk rating for reported NFOI was at moderate level, with minor cuts and
scratches were the dominant type of injury (42.6%). Analysis of logistic regression
indicated that working in shift, not wearing protective gloves, health problems such as
shortness of breath and ringing in ears, and excessive noise level (≥ 85 dB[A]) were
the risk factors of NFOI in palm oil mills among OP workers. A framework of nonfatal
injury surveillance in palm oil mills was developed based on the findings with
integration of risk management process and injury prevention principles. This
framework is anticipated to help the management in decision making for preventive
actions and early detection of occupational health effects among workers
- …