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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:

Mixed-mode malware contains user-mode and kernel-mode components that are interdependent. Such malware exhibits its main malicious payload only after it succeeds at corrupting the OS kernel. Such malware may further actively attack or subvert malware analysis components. Current malware analysis techniques are not effective against mixedmode malware. To overcome the limitations of current techniques, we present an approach that combines whole-system analysis with outside-the-guest virtual machine introspection. We implement this approach in the SEMU tool for Windows. In our experiments SEMU could successfully analyze several mixed-mode malware samples that evade current analysis approaches. The runtime overhead of SEMU is in line with the most closely related dynamic analysis tools TEMU and Ether.

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