11,057 research outputs found
Secure Trajectory Planning Against Undetectable Spoofing Attacks
This paper studies, for the first time, the trajectory planning problem in
adversarial environments, where the objective is to design the trajectory of a
robot to reach a desired final state despite the unknown and arbitrary action
of an attacker. In particular, we consider a robot moving in a two-dimensional
space and equipped with two sensors, namely, a Global Navigation Satellite
System (GNSS) sensor and a Radio Signal Strength Indicator (RSSI) sensor. The
attacker can arbitrarily spoof the readings of the GNSS sensor and the robot
control input so as to maximally deviate his trajectory from the nominal
precomputed path. We derive explicit and constructive conditions for the
existence of undetectable attacks, through which the attacker deviates the
robot trajectory in a stealthy way. Conversely, we characterize the existence
of secure trajectories, which guarantee that the robot either moves along the
nominal trajectory or that the attack remains detectable. We show that secure
trajectories can only exist between a subset of states, and provide a numerical
mechanism to compute them. We illustrate our findings through several numerical
studies, and discuss that our methods are applicable to different models of
robot dynamics, including unicycles. More generally, our results show how
control design affects security in systems with nonlinear dynamics.Comment: Accepted for publication in Automatic
Smart Grid Security: Threats, Challenges, and Solutions
The cyber-physical nature of the smart grid has rendered it vulnerable to a
multitude of attacks that can occur at its communication, networking, and
physical entry points. Such cyber-physical attacks can have detrimental effects
on the operation of the grid as exemplified by the recent attack which caused a
blackout of the Ukranian power grid. Thus, to properly secure the smart grid,
it is of utmost importance to: a) understand its underlying vulnerabilities and
associated threats, b) quantify their effects, and c) devise appropriate
security solutions. In this paper, the key threats targeting the smart grid are
first exposed while assessing their effects on the operation and stability of
the grid. Then, the challenges involved in understanding these attacks and
devising defense strategies against them are identified. Potential solution
approaches that can help mitigate these threats are then discussed. Last, a
number of mathematical tools that can help in analyzing and implementing
security solutions are introduced. As such, this paper will provide the first
comprehensive overview on smart grid security
Local Cyber-physical Attack with Leveraging Detection in Smart Grid
A well-designed attack in the power system can cause an initial failure and
then results in large-scale cascade failure. Several works have discussed power
system attack through false data injection, line-maintaining attack, and
line-removing attack. However, the existing methods need to continuously attack
the system for a long time, and, unfortunately, the performance cannot be
guaranteed if the system states vary. To overcome this issue, we consider a new
type of attack strategy called combinational attack which masks a line-outage
at one position but misleads the control center on line outage at another
position. Therefore, the topology information in the control center is
interfered by our attack. We also offer a procedure of selecting the vulnerable
lines of its kind. The proposed method can effectively and continuously deceive
the control center in identifying the actual position of line-outage. The
system under attack will be exposed to increasing risks as the attack
continuously. Simulation results validate the efficiency of the proposed attack
strategy.Comment: Accepted by IEEE SmartGridComm 201
Big Data in Critical Infrastructures Security Monitoring: Challenges and Opportunities
Critical Infrastructures (CIs), such as smart power grids, transport systems,
and financial infrastructures, are more and more vulnerable to cyber threats,
due to the adoption of commodity computing facilities. Despite the use of
several monitoring tools, recent attacks have proven that current defensive
mechanisms for CIs are not effective enough against most advanced threats. In
this paper we explore the idea of a framework leveraging multiple data sources
to improve protection capabilities of CIs. Challenges and opportunities are
discussed along three main research directions: i) use of distinct and
heterogeneous data sources, ii) monitoring with adaptive granularity, and iii)
attack modeling and runtime combination of multiple data analysis techniques.Comment: EDCC-2014, BIG4CIP-201
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