1.  

Wireless networking protocols are increasingly being designed to exploit a user’s measured channel condition; we call such protocols channel-aware. Each user reports the measured channel condition to a manager of wireless resources and a channel-aware protocol uses these reports to determine how resources are allocated to users. In a channel-aware protocol, each user’s reported channel condition affects the performance of every other user. The deployment of channel-aware protocols increases the risks posed by false channel-condition feedback. In this paper, we study what happens in the presence of an attacker that falsely reports its channel condition. We perform case studies on channel-aware network protocols to understand how an attack can use false feedback and how much the attack can affect network performance. The results of the case studies show that we need a secure channel condition estimation algorithm to fundamentally defend against the channel-condition misreporting attack. We design such an algorithm and evaluate our algorithm through analysis and simulation. Our evaluation quantifies the effect of our algorithm on system performance as well as the security and the performance of our algorithm.

1.2 INTRODUCTION

Many protocols in modern wireless networks treat a link’s channel condition information as a protocol input parameter; we call such protocols channel-aware. Examples include cooperative relaying network architectures, efficient ad hoc network routing metrics, and opportunistic schedulers. While work on channel-aware protocols has mainly focused on how channel condition information can be used to more efficiently utilize wireless resources, security aspects of channel-aware protocols have only recently been studied. These works on security of channel-aware protocols revealed new threats in specific network environments by simulation or measurement. However, understanding the effect of possible attacks across varied network environments is still an open area for study. In particular, we consider the effect of a user equipment’s reporting false channel condition. This issue is partially addressed in the work of Racic et al.  in a limited network setting. They consider a particular scheduler in a cellular network with handover process and propose a secure handover algorithm. In contrast, we reveal the possible effects of false channel condition reporting in various channel-aware network protocols and propose a primitive defense mechanism that provides secure channel condition estimation. Our contributions are:

 • We analyze specific attack mechanisms and evaluate the effects of misreporting channel condition on various channel-aware wireless network protocols including cooperative relaying protocols, routing metrics in wireless ad-hoc network and opportunistic schedulers.

• We propose a secure channel condition estimation algorithm that can be used to construct a secure channel-aware protocol in single-hop settings.

• We analyze our algorithm in the respects of performance and security, and we perform a simulation study to understand the impact of our algorithm on system performance.

The false channel condition reporting attack that we introduce in this paper is difficult to identify by existing mechanisms, since our attack is mostly protocol compliant; only the channel-condition measurement mechanism need to be modified. Our attack can thus be performed using modified user equipment legitimately registered to a network.

1.3 LITRATURE SURVEY

A STUDY ON FALSE CHANNEL CONDITION REPORTING ATTACKS IN WIRELESS NETWORKS

PUBLICATION: Dongho Kim and Yih-Chun Hu, IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 13, NO. 5, MAY 2014.

EXPLOITING AND DEFENDING OPPORTUNISTIC SCHEDULING IN CELLULAR DATA NETWORKS

PUBLICATION: R. Racic, D. Ma, H. Chen, and X. Liu, IEEE Trans. Mobile Comput., vol. 9, no. 5, pp. 609–620, May 2010.

ON THE VULNERABILITY OF THE PROPORTIONAL FAIRNESS SCHEDULER TO RETRANSMISSION ATTACKS

PUBLICATION: U. Ben-Porat, A. Bremler-Barr, H. Levy, and B. Plattner, in Proc. IEEE INFOCOM, Shanghai, China, Apr. 2011, pp. 1431–1439.

A MEASUREMENT STUDY OF SCHEDULER-BASED ATTACKS IN 3G WIRELESS NETWORKS

PUBLICATION: S. Bali, S. Machiraju, H. Zang, and V. Frost, in Proc. PAM, Berlin, Germany, 2007.

CHAPTER 2

2.0 SYSTEM ANALYSIS

2.1 EXISTING SYSTEM:

Many protocols in modern wireless networks treat a link’s channel condition information as a protocol input parameter; we call such protocols channel-aware. Examples include cooperative relaying network architectures, efficient ad hoc network routing metrics, and opportunistic schedulers. While work on channel-aware protocols has mainly focused on how channel condition information can be used to more efficiently utilize wireless resources, security aspects of channel-aware protocols have only recently been studied. These works on security of channel-aware protocols revealed new threats in specific network environments by simulation or measurement. However, under-standing the effect of possible attacks across varied network environments is still an open area for study.

2.1.1 DISADVANTAGES:

• Difficult to guarantee QoS in MANETs due to their unique features including user mobility, channel variance errors, and limited bandwidth.
• Although these protocols can increase the QoS of the MANETs to a certain extent, they suffer from invalid reservation and race condition problems.

2.2 PROPOSED SYSTEM:

The false channel condition reporting attack that we introduce in this paper is difficult to identify by existing mechanisms, since our attack is mostly protocol compliant; only the channel-condition measurement mechanism need to be modified. Our attack can thus be performed using modified user equipment legitimately registered to a network.

2.2.1 ADVANTAGES:

• The source node schedules the packet streams to neighbors based on their queuing condition, channel condition, and mobility, aiming to reduce transmission time and increase network capacity.
• Taking full advantage of the two features, QOD transforms the packet routing problem into a dynamic resource scheduling problem.

SYSTEM ARCHITECTURE:

2.3 HARDWARE & SOFTWARE REQUIREMENTS:

2.3.1 HARDWARE REQUIREMENT:

v    Processor                                 –    Pentium –IV

• Speed                                      –    1.1 GHz
  • RAM                                       –    256 MB (min)
  • Hard Disk                               –   20 GB
  • Floppy Drive                           –    1.44 MB
  • Key Board                              –    Standard Windows Keyboard
  • Mouse                                     –    Two or Three Button Mouse
  • Monitor                                   –    SVGA

 

2.3.2 SOFTWARE REQUIREMENTS:

• Operating System                   :           Windows XP
• Front End                                :           Microsoft Visual Studio .NET 2008
• Back End                                :           MS-SQL Server 2005
• Document                               :           MS-Office 2007