Abstract-The attack graph is an abstraction that reveals the ways an attacker can leverage vulnerabilities in a network to violate a security policy. When used with attack graph-based security metrics, the attack graph may be used to quantitatively assess securityrelevant aspects of a network. The Shortest Path metric, the Number of Paths metric, and the Mean of Path Lengths metric are three attack graph-based security metrics that can extract security-relevant information. However, one's usage of these metrics can lead to misleading results. The Shortest Path metric and the Mean of Path Lengths metric fail to adequately account for the number of ways an attacker may violate a security policy. The Number of Paths metric fails to adequately account for the attack effort associated with the attack paths. To overcome these shortcomings, we propose a complimentary suite of attack graph-based security metrics and specify an algorithm for combining the usage of these metrics. We present simulated results that suggest that our approach reaches a conclusion about which of two attack graphs correspond to a network that is most secure in many instances.
In this paper, we discuss security problems, with a focus on collaborative attacks, in the Worldwide Interoperability for Microwave Access (WiMAX) scenario. The WiMAX protocol suite, which includes but is not limited to DOCSIS, DES, and AES, consists of a large number of protocols. We present briefly the WiMAX standard and its vulnerabilities. We pinpoint the problems with individual protocols in the WiMAX protocol suite, and discuss collaborative attacks on WiMAX systems. We present several typical WiMAX attack scenarios, including: bringing a large number of attackers to increase their computation power and break WiMAX protocols; assembling a sufficient number of attackers to influence the decision-making of core machines, which includes routing attacks and Sybil attacks; and exploiting implementations that do not conform to the WiMAX specification completely, causing interoperability problems among various protocols, including the ones in typical WiMAX/WiFi/LAN deployment scenarios. We present theoretical models and practical solutions to profile, model, and analyze collaborative attacks in WiMAX. We employ attack graphs to do vulnerability analysis. Experimental results verify our models and validate our analysis. defense mechanisms. Models for cooperation need to be studied along with defense mechanisms. We also need to characterize various types and models of attacks through studies of detailed attack logs that are available from various intrusion detection systems (IDS).In this paper, we study the impacts of collaborative attacks on throughput, data delivery, and routing in the worldwide interoperability for microwave access (WiMAX) scenarios.Traditionally users employ one of the following three approaches to access Internet:
Since ad hoc networks rely on nodes cooperation to establish communication, malicious nodes can compromise the entire network. If they collaborate the devastation is even worse. Collaborative attacks may cause more devastating impacts on wireless environments than single and uncoordinated groups of attacks, as they combine efforts of more than one attacker against the target victim. In this paper, we present the most important forms of attacks, discuss possible collaborations among attackers, show how machine learning techniques and signal processing techniques can be used to detect and defend against collaborative attacks in such environments, and discuss implementation issues.
Previous provenance models have assumed that there is complete certainty in the provenance relationships. But what if this assumption does not hold? In this work, we propose a probabilistic provenance graph (PPG) model to characterize scenarios where provenance relationships are uncertain. We describe two motivating examples. The first example demonstrates the uncertainty associated with the provenance of an email. The second example demonstrates and characterizes the uncertainty associated with the provenance of statements in documents.
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