Friday 23 October 2015

Privacy-Preserving and Truthful Detection of Packet Dropping Attacks in Wireless Ad Hoc Networks

Abstract
Link error and malicious packet dropping are two sources for packet losses in multi-hop wireless ad hoc network. In this paper, while observing a sequence of packet losses in the network, we are interested in determining whether the losses are caused by link errors only, or by the combined effect of link errors and malicious drop. We are especially interested in the insider-attack case, whereby malicious nodes that are part of the route exploit their knowledge of the communication context to selectively drop a small amount of packets critical to the network performance. Because the packet dropping rate in this case is comparable to the channel error rate, conventional algorithms that are based on detecting the packet loss rate cannot achieve satisfactory detection accuracy. To improve the detection accuracy, we propose to exploit the correlations between lost packets. Furthermore, to ensure truthful calculation of these correlations, we develop a homomorphic linear authenticator (HLA) based public auditing architecture that allows the detector to verify the truthfulness of the packet loss information reported by nodes. This construction is privacy preserving, collusion proof, and incurs low communication and storage overheads. To reduce the computation overhead of the baseline scheme, a packet-block-based mechanism is also proposed, which allows one to trade detection accuracy for lower computation complexity. Through extensive simulations, we verify that the proposed mechanisms achieve significantly better detection accuracy than conventional methods such as a maximum-likelihood based detection.
Aim
The aim is to achieve significantly better detection accuracy.
Scope
The scope is to develop a homomorphic linear authenticator (HLA) based public auditing architecture that allows the detector to verify the truthfulness of the packet loss information reported by nodes.
Existing System
The malicious node may understate its packet-loss bitmap, i.e., some packets may have been dropped by the node but the node reports that these packets have been forwarded. Therefore, some auditing mechanism is needed to verify the truthfulness of the reported information. Considering that a typical wireless device is resource-constrained, we also require that a user should be able to delegate the burden of auditing and detection to some public server to save its own resources.
Disadvantages
·      Link error and malicious packet dropping are two sources for packet losses in multi-hop wireless ad hoc network. While observing a sequence of packet losses in the network, we should determine whether the losses are caused by link errors only, or by the combined effect of link errors and malicious drop.

·      We are especially interested in the insider-attack case, whereby malicious nodes that are part of the route exploit their knowledge of the communication context to selectively drop a small amount of packets critical to the network performance.

·      Because the packet dropping rate in this case is comparable to the channel error rate, conventional algorithms that are based on detecting the packet loss rate cannot achieve satisfactory detection accuracy
Proposed System
In this project, we develop an accurate algorithm for detecting selective packet drops made by insider attackers. Our algorithm also provides a truthful and publicly verifiable decision statistics as a proof to support the detection decision. The high detection accuracy is achieved by exploiting the correlations between the positions of lost packets, as calculated from the auto-correlation function (ACF) of the packet-loss bitmap–a bitmap describing the lost/received status of each packet in a sequence of consecutive packet transmissions. The basic idea behind this method is that even though malicious dropping may result in a packet loss rate that is comparable to normal channel losses, the stochastic processes that characterize the two phenomena exhibit different correlation structures (equivalently, different patterns of packet losses). Therefore, by detecting the correlations between lost packets, one can decide whether the packet loss is purely due to regular link errors, or is a combined effect of link error and malicious drop. Our algorithm takes into account the cross-statistics between lost packets to make a more informative decision, and thus is in sharp contrast to the conventional methods that rely only on the distribution of the number of lost packets.
The main challenge in our mechanism lies in how to guarantee that the packet-loss bitmaps reported by individual nodes along the route are truthful, i.e., reflect the actual status of each packet transmission. Such truthfulness is essential for correct calculation of the correlation between lost packets. This challenge is not trivial, because it is natural for an attacker to report false information to the detection algorithm to avoid being detected.
 Advantages
Our solution to the problem is constructed based on the homomorphic linear authenticator (HLA) cryptographic primitive, which is basically a signature scheme widely used in cloud computing and storage server systems to provide a proof of storage from the server to entrusting clients.
To reduce the computation overhead of the baseline scheme, a packet-block-based mechanism is also proposed, which allows one to trade detection accuracy for lower computation complexity.
Privacy-preserving
The public auditor should not be able to decern the content of a packet delivered on the route through the auditing information submitted by individual hops, no matter how many independent reports of the auditing information are submitted to the auditor.
Second, our construction incurs low communication and storage overheads at intermediate nodes. This makes our mechanism applicable to a wide range of wireless devices, including low-cost wireless sensors that have very limited bandwidth and memory capacities. This is also in sharp contrast to the typical storage server scenario, where bandwidth/storage is not considered an issue.

System Architecture
 

System configuration

Hardware Requirements
  • Speed                  -    1.1 Ghz
  • Processor              -    Pentium IV
  • RAM                    -    512 MB (min)
  • Hard Disk            -    40 GB
  • Key Board                    -    Standard Windows Keyboard
  • Mouse                  -    Two or Three Button Mouse
  • Monitor                -     LCD/LED
 Software requirements
  • Operating System              : Windows 7             
  •  Front End                           : ASP.Net and C#
  • Database                             : MSSQL
  • Tool                                    : Microsoft Visual studio

References
Krunz. M, Tao Shu " PRIVACY-PRESERVING AND TRUTHFUL DETECTION OF PACKET DROPPING ATTACKS IN WIRELESS AD HOC NETWORKS", IEEE Transactions on  Mobile Computing (Volume:14 ,  Issue: 4 ) June 2014

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