1,482 research outputs found
Intrusion Detection System for Platooning Connected Autonomous Vehicles
The deployment of Connected Autonomous Vehicles (CAVs) in Vehicular Ad Hoc Networks (VANETs) requires secure wireless communication in order to ensure reliable connectivity and safety. However, this wireless communication is vulnerable to a variety of cyber atacks such as spoofing or jamming attacks. In this paper, we describe an Intrusion Detection System (IDS) based on Machine Learning (ML) techniques designed to detect both spoofing and jamming attacks in a CAV environment. The IDS would reduce the risk of traffic disruption and accident caused as a result of cyber-attacks. The detection engine of the presented IDS is based on the ML algorithms Random Forest (RF), k-Nearest Neighbour (k-NN) and One-Class Support Vector Machine (OCSVM), as well as data fusion techniques in a cross-layer approach. To the best of the authors’ knowledge, the proposed IDS is the first in literature that uses a cross-layer approach to detect both spoofing and jamming attacks against the communication of connected vehicles platooning. The evaluation results of the implemented IDS present a high accuracy of over 90% using training datasets containing both known and unknown attacks
Fast Sequence Component Analysis for Attack Detection in Synchrophasor Networks
Modern power systems have begun integrating synchrophasor technologies into
part of daily operations. Given the amount of solutions offered and the
maturity rate of application development it is not a matter of "if" but a
matter of "when" in regards to these technologies becoming ubiquitous in
control centers around the world. While the benefits are numerous, the
functionality of operator-level applications can easily be nullified by
injection of deceptive data signals disguised as genuine measurements. Such
deceptive action is a common precursor to nefarious, often malicious activity.
A correlation coefficient characterization and machine learning methodology are
proposed to detect and identify injection of spoofed data signals. The proposed
method utilizes statistical relationships intrinsic to power system parameters,
which are quantified and presented. Several spoofing schemes have been
developed to qualitatively and quantitatively demonstrate detection
capabilities.Comment: 8 pages, 4 figures, submitted to IEEE Transaction
Satellite Navigation for the Age of Autonomy
Global Navigation Satellite Systems (GNSS) brought navigation to the masses.
Coupled with smartphones, the blue dot in the palm of our hands has forever
changed the way we interact with the world. Looking forward, cyber-physical
systems such as self-driving cars and aerial mobility are pushing the limits of
what localization technologies including GNSS can provide. This autonomous
revolution requires a solution that supports safety-critical operation,
centimeter positioning, and cyber-security for millions of users. To meet these
demands, we propose a navigation service from Low Earth Orbiting (LEO)
satellites which deliver precision in-part through faster motion, higher power
signals for added robustness to interference, constellation autonomous
integrity monitoring for integrity, and encryption / authentication for
resistance to spoofing attacks. This paradigm is enabled by the 'New Space'
movement, where highly capable satellites and components are now built on
assembly lines and launch costs have decreased by more than tenfold. Such a
ubiquitous positioning service enables a consistent and secure standard where
trustworthy information can be validated and shared, extending the electronic
horizon from sensor line of sight to an entire city. This enables the
situational awareness needed for true safe operation to support autonomy at
scale.Comment: 11 pages, 8 figures, 2020 IEEE/ION Position, Location and Navigation
Symposium (PLANS
A review of cyber threats and defence approaches in emergency management
Emergency planners, first responders and relief workers increasingly rely on computational and communication systems that support all aspects of emergency management, from mitigation and preparedness to response and recovery. Failure of these systems, whether accidental or because of malicious action, can have severe implications for emergency management. Accidental failures have been extensively documented in the past and significant effort has been put into the development and introduction of more resilient technologies. At the same time researchers have been raising concerns about the potential of cyber attacks to cause physical disasters or to maximise the impact of one by intentionally impeding the work of the emergency services. Here, we provide a review of current research on the cyber threats to communication, sensing, information management and vehicular technologies used in emergency management. We emphasise on open issues for research, which are the cyber threats that have the potential to affect emergency management severely and for which solutions have not yet been proposed in the literature
Cross Domain IW Threats to SOF Maritime Missions: Implications for U.S. SOF
As cyber vulnerabilities proliferate with the expansion of connected devices, wherein security is often forsaken for ease of use, Special Operations Forces (SOF) cannot escape the obvious, massive risk that they are assuming by incorporating emerging technologies into their toolkits. This is especially true in the maritime sector where SOF operates nearshore in littoral zones. As SOF—in support to the U.S. Navy— increasingly operate in these contested maritime environments, they will gradually encounter more hostile actors looking to exploit digital vulnerabilities. As such, this monograph comes at a perfect time as the world becomes more interconnected but also more vulnerable
Undetectable GPS-Spoofing Attack on Time Series Phasor Measurement Unit Data
The Phasor Measurement Unit (PMU) is an important metering device for smart
grid. Like any other Intelligent Electronic Device (IED), PMUs are prone to
various types of cyberattacks. However, one form of attack is unique to the
PMU, the GPS-spoofing attack, where the time and /or the one second pulse (1
PPS) that enables time synchronization are modified and the measurements are
computed using the modified time reference. This article exploits the
vulnerability of PMUs in their GPS time synchronization signal. At first, the
paper proposes an undetectable gradual GPS-spoofing attack with small
incremental angle deviation over time. The angle deviation changes power flow
calculation through the branches of the grids, without alerting the System
Operator (SO) during off-peak hour. The attacker keeps instigating slow
incremental variation in power flow calculation caused by GPS-spoofing
relentlessly over a long period of time, with a goal of causing the power flow
calculation breach the MVA limit of the branch at peak-hour. The attack is
applied by solving a convex optimization criterion at regular time interval, so
that after a specific time period the attack vector incurs a significant change
in the angle measurements transmitted by the PMU. Secondly, while the attack
modifies the angle measurements with GPS-spoofing attack, it ensures the
undetectibility of phase angle variation by keeping the attack vector less than
attack detection threshold. The proposed attack model is tested with Weighted
Least Squared Error (WLSE), Kalman Filtering, and Hankel-matrix based
GPS-spoofing attack detection models. Finally, we have proposed a gradient of
low-rank approximation of Hankel-matrix based detection method to detect such
relentless small incremental GPS-spoofing attack
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