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A Study on False Channel Condition Reporting Attacks in Wireless Networks




A Study on False Channel Condition Reporting Attacks in Wireless Networks

ABSTRACT:
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.

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-awareprotocols 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.

DISADVANTAGES OF EXISTING SYSTEM:
·        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.

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.

ADVANTAGES OF PROPOSED SYSTEM:
·        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:

SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:

Ø System                          :         Pentium IV 2.4 GHz.
Ø Hard Disk                      :         40 GB.
Ø Floppy Drive                 :         1.44 Mb.
Ø Monitor                         :         15 VGA Colour.
Ø Mouse                            :         Logitech.
Ø Ram                               :         512 Mb.

SOFTWARE REQUIREMENTS:

Ø Operating system           :         Windows XP/7/LINUX.
Ø Implementation    :         NS2
Ø NS2 Version        :         NS2.2.28
Ø Front End             : OTCL (Object Oriented Tool Command  Language)
Ø Tool                     :         Cygwin (To simulate in Windows OS)


REFERENCE:
Dongho Kim and Yih-Chun Hu, “A Study on False Channel Condition Reporting Attacks in Wireless Networks”, IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 13, NO. 5, MAY 2014.