12,722 research outputs found
Identifying Security-Critical Cyber-Physical Components in Industrial Control Systems
In recent years, Industrial Control Systems (ICS) have become an appealing
target for cyber attacks, having massive destructive consequences. Security
metrics are therefore essential to assess their security posture. In this
paper, we present a novel ICS security metric based on AND/OR graphs that
represent cyber-physical dependencies among network components. Our metric is
able to efficiently identify sets of critical cyber-physical components, with
minimal cost for an attacker, such that if compromised, the system would enter
into a non-operational state. We address this problem by efficiently
transforming the input AND/OR graph-based model into a weighted logical formula
that is then used to build and solve a Weighted Partial MAX-SAT problem. Our
tool, META4ICS, leverages state-of-the-art techniques from the field of logical
satisfiability optimisation in order to achieve efficient computation times.
Our experimental results indicate that the proposed security metric can
efficiently scale to networks with thousands of nodes and be computed in
seconds. In addition, we present a case study where we have used our system to
analyse the security posture of a realistic water transport network. We discuss
our findings on the plant as well as further security applications of our
metric.Comment: Keywords: Security metrics, industrial control systems,
cyber-physical systems, AND-OR graphs, MAX-SAT resolutio
Attack-Graph Threat Modeling Assessment of Ambulatory Medical Devices
The continued integration of technology into all aspects of society stresses the need to identify and understand the risk associated with assimilating new technologies. This necessity is heightened when technology is used for medical purposes like ambulatory devices that monitor a patient’s vital signs. This integration creates environments that are conducive to malicious activities. The potential impact presents new challenges for the medical community. \ \ Hence, this research presents attack graph modeling as a viable solution to identifying vulnerabilities, assessing risk, and forming mitigation strategies to defend ambulatory medical devices from attackers. Common and frequent vulnerabilities and attack strategies related to the various aspects of ambulatory devices, including Bluetooth enabled sensors and Android applications are identified in the literature. Based on this analysis, this research presents an attack graph modeling example on a theoretical device that highlights vulnerabilities and mitigation strategies to consider when designing ambulatory devices with similar components.
A Comprehensive Analysis of Swarming-based Live Streaming to Leverage Client Heterogeneity
Due to missing IP multicast support on an Internet scale, over-the-top media
streams are delivered with the help of overlays as used by content delivery
networks and their peer-to-peer (P2P) extensions. In this context,
mesh/pull-based swarming plays an important role either as pure streaming
approach or in combination with tree/push mechanisms. However, the impact of
realistic client populations with heterogeneous resources is not yet fully
understood. In this technical report, we contribute to closing this gap by
mathematically analysing the most basic scheduling mechanisms latest deadline
first (LDF) and earliest deadline first (EDF) in a continuous time Markov chain
framework and combining them into a simple, yet powerful, mixed strategy to
leverage inherent differences in client resources. The main contributions are
twofold: (1) a mathematical framework for swarming on random graphs is proposed
with a focus on LDF and EDF strategies in heterogeneous scenarios; (2) a mixed
strategy, named SchedMix, is proposed that leverages peer heterogeneity. The
proposed strategy, SchedMix is shown to outperform the other two strategies
using different abstractions: a mean-field theoretic analysis of buffer
probabilities, simulations of a stochastic model on random graphs, and a
full-stack implementation of a P2P streaming system.Comment: Technical report and supplementary material to
http://ieeexplore.ieee.org/document/7497234
DrAGON: A Framework for Computing Preferred Defense Policies from Logical Attack Graphs
Attack graphs provide formalism for modelling the vulnerabilities using a compact representation scheme. Two of the most popular attack graph representations are scenario attack graphs, and logical attack graphs. In logical attack graphs, the host machines present in the network are represented as exploit nodes, while the configurations (IDS rules, firewall policies etc.) running on them are represented as fact nodes. The actual user privileges that are possible on each of these hosts are represented as privilege nodes.
Existing work provides methods to analyze logical attack graphs and compute attack paths of varying costs. In this thesis we develop a framework for analyzing the attack graph from a defender perspective. Given an acyclic logical dependency attack graph we compute defense policies that cover all known exploits that can be used by the attacker and also are preferred with respect to minimizing the impacts. In contrast to previous work on analysis of logical attack graphs where quantitative costs are assigned to the vulnerabilities (exploits), our framework allows attack graph analysis using descriptions of vulnerabilities on a qualitative scale. We develop two algorithms for computing preferred defense policies that are optimal with respect to defender preferences. Our research to the best of our knowledge is the first fully qualitative approach to analyzing these logical attack graphs and formulating defense policies based on the preferences and priorities of the defender.
We provide a prototype implementation of our framework that allows logical attack graphs to be input using a simple text file (custom language), or using a GUI tool in graphical markup language (GML) format. Our implementation uses the NVD (National Vulnerability Database) as the source of CVSS impact metrics for vulnerabilities in the attack graph. Our framework generates a preferred order of defense policies using an existing preference reasoner. Preliminary experiments on various attack graphs show the correctness and efficiency of our approach
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