Showing posts with label IEEE Dot Net Projects. Show all posts
Showing posts with label IEEE Dot Net Projects. Show all posts
Thursday, December 27, 2012
2
Thursday, December 27, 2012
prakash chalumuri
IEEE Dot Net Project- BECAN: A Bandwidth-Efficient Cooperative Authentication Scheme for Filtering Injected False Data in Wireless Sensor Networks
BECAN: A Bandwidth-Efficient
Cooperative Authentication Scheme for Filtering Injected False Data in Wireless
Sensor Networks
Abstract
Injecting false data attack is a well
known serious threat to wireless sensor network, for which an adversary reports
bogus information to sink causing error decision at upper level and
energy waste in en-route nodes. In this paper, we propose a novel
bandwidth-efficient cooperative authentication (BECAN) scheme for filtering
injected false data. Based on the random graph characteristics of sensor node
deployment and the cooperative bit-compressed authentication technique, the
proposed BECAN scheme can save energy by early detecting and filtering
the majority of injected false data with minor extra overheads at the en-route
nodes. In addition, only a very small fraction of injected false data needs to
be checked by the sink, which thus largely reduces the burden of the sink.
Both theoretical and simulation results are given to demonstrate the
effectiveness of the proposed scheme in terms of high filtering probability and
energy saving.
Architecture
Existing System
Wireless sensor networks are usually
deployed at unattended or hostile environments. Therefore, they are very
vulnerable to various security attacks, such as selective forwarding,
wormholes, and sybil attacks. In addition, wireless sensor networks may also
suffer from injecting false data attack. For an injecting false data attack, an
adversary first compromises several sensor nodes, accesses all keying materials
stored in the compromised nodes, and then controls these compromised nodes to
inject bogus information and send the false data to the sink to cause
upper level error decision, as well as energy wasted in en-route nodes.
Disadvantages
1. Energy
wasted in en-route nodes.
2. Heavy
verification burdens.
3. Gang
injecting false data attack.
4. No
Cooperative Authentication.
Proposed
System
In this paper, we propose a novel
bandwidth-efficient cooperative authentication (BECAN) scheme for filtering
injected false data. Based on the random graph characteristics of sensor node
deployment and the cooperative bit-compressed authentication technique, the
proposed BECAN scheme can save energy by early detecting and filtering
the majority of injected false data with minor extra overheads at the en-route
nodes. In addition, only a very small fraction of injected false data needs to
be checked by the sink, which thus largely reduces the burden of the sink.
Both theoretical and simulation results are given to demonstrate the
effectiveness of the proposed scheme in terms of high filtering probability and
energy saving.
Advantages
1.
High filtering
probability and energy saving.
2.
Detect injecting false
data attack.
3.
BECAN Scheme in terms
of en-routing filtering probability and false negative rate on true reports.
4.
Early detecting the injected false data by the en-route sensor nodes.
5.
Sink Verification
6.
Prevent/Mitigate the gang
injecting false data attack from mobile compromised sensor nodes.
Modules
1. BECAN Scheme
A
novel bandwidth-efficient cooperative authentication (BECAN) scheme for
filtering injected false data in wireless sensor networks. Compared with the
previously reported mechanisms, the BECAN scheme achieves not only high
filtering probability but also high reliability.
•) First, we study the random graph characteristics of
wireless sensor node deployment, and estimate the probability of k-neighbors, which provides the necessary
condition for BECAN authentication;
•) Second, we propose the
BECAN scheme to filter the injected false data with cooperative bit-compressed authentication
technique. With the proposed mechanism, injected false data can be early
detected and filtered by the en-route sensor nodes. In addition, the
accompanied authentication information is bandwidth-efficient; and
•) Third, we develop a custom simulator to demonstrate
the effectiveness of the proposed BECAN scheme in terms of en-routing filtering
probability and false negative rate on true reports.
2. Early detecting the injected false data by the en-route sensor nodes
The
sink is a powerful data collection device. Nevertheless, if all
authentication tasks are fulfilled at the sink, it is undoubted that the
sink becomes a bottleneck. At the same time, if too many injected false
data flood into the sink, the sink will surly suffer from the
Denial of Service (DoS) attack. Therefore, it is critical to share the authentication
tasks with the en-route sensor nodes such that the injected false data can be
detected and discarded early. The earlier the injected false data are detected,
the more energy can be saved in the whole network.
3.
Gang Injecting False
Data Attack
We
introduce a new stronger injecting false data attack, called gang injecting
false data attack, in wireless sensor networks. This kind of attack is usually launched
by a gang of compromised sensor nodes controlled and moved by an adversary A. As shown in Fig.
2, when a compromised source node is ready to send a false data, several
compromised nodes will first move and aggregate at the source node, and then
collude to inject the false data. Because of the mobility, the gang injecting
false data attack is more challenging and hard to resist.
Fig.
4. Reliability
of the BECAN scheme
In
addition to the high (en-routing) filtering probability, the BECAN scheme also
has high reliability, i.e., even though some sensor nodes are compromised, the
true event reports still can reach the sink with high probability. Let
FNR be the false negative rate on the true reports and tested as
If
FNR is small, the BECAN scheme is demonstrated high reliability.
HARDWARE & SOFTWARE
REQUIREMENTS
HARDWARE REQUIREMENTS
·
System : Pentium IV 2.4 GHz.
·
Hard Disk : 40 GB.
·
Floppy Drive : 1.44 Mb.
·
Monitor : 15 VGA Color.
SOFTWARE REQUIREMENTS
·
Operating system : Windows XP Professional.
·
Coding Language : C#.NET
1
prakash chalumuri
2. Tracking membership Service
3. Byzantine Fault Tolerance
4. Dynamic Replication Reliable Automatic Reconfiguration
IEEE Dot Net Project - Automatic Reconfiguration for Large-Scale Reliable StorageSystems
Automatic Reconfiguration for Large-Scale
Reliable StorageSystems
Abstract
Byzantine-fault-tolerant replication enhances the availability and reliability of
Internet services that store critical state and preserve it despite attacks or software errors.
However, existing Byzantine-fault-tolerant storage systems either assume a static set of
replicas, or have limitations in how they handle reconfigurations (e.g., in terms of the
scalability of the solutions or the consistency levels they provide). This can be
problematic in long-lived, large-scale systems where system membership is likely to
change during the system lifetime. In this paper, we present a complete solution for
dynamically changing system membership in a large-scale Byzantine-fault-tolerant
system. We present a service that tracks system membership and periodically notifies
other system nodes of membership changes. The membership service runs mostly
automatically, to avoid human configuration errors; is itself Byzantine fault- tolerant and
reconfigurable; and provides applications with a sequence of consistent views of the
system membership. We demonstrate the utility of this membership service by using it in
a novel distributed hash table called dBQS that provides atomic semantics even across
changes in replica sets. dBQS is interesting in its own right because its storage algorithms
extend existing Byzantine quorum protocols to handle changes in the replica set, and
because it differs from previous DHTs by providing Byzantine fault tolerance and
offering strong semantics. We implemented the membership service and dBQS. Our
results show that the approach works well, in practice: the membership service is able to
manage a large system and the cost to change the system membership is low.
Existing System
In Existing System, replication enhanced the reliability of internet services to
store the data’s. The preserved data to be secured from software errors. But, existing
Byzantine-fault tolerant systems is a static set of replicas. It has no limitations. So,
scalability is inconsistency. So, these data’s are not came for long-lived systems.
The existence of the following cryptographic techniques that an adversary cannot
subvert: a collision resistant hash function, a public key cryptography scheme, and
forward-secure signing key and the existence of a proactive threshold signature protocol.
Proposed System
In Proposed System, has two parts. The first is a membership service (MS) that
tracks and responds to membership changes. The MS works mostly automatically, and requires only minimal human intervention; this way we can reduce manual configuration
errors, which are a major cause of disruption in computer systems periodically, the MS
publishes a new system membership; in this way it provides a globally consistent view of
the set of available servers. The choice of strong consistency makes it easier to
implement applications, since it allows clients and servers to make consistent local
decisions about which servers are currently responsible for which parts of the service.
The second part of our solution addresses the problem of how to reconfigure
applications automatically as system membership changes. We present a storage system,
dBQS that provides Byzantine-fault-tolerant replicated storage with strong consistency.
Modules
1. Reliable Automatic Reconfiguration2. Tracking membership Service
3. Byzantine Fault Tolerance
4. Dynamic Replication Reliable Automatic Reconfiguration
In this Module, it provides the abstraction of a globally consistent view of the
system membership. This abstraction simplifies the design of applications that use it,
since it allows different nodes to agree on which servers are responsible for which subset
of the service. It is designed to work at large scale, e.g., tens or hundreds of thousands of
servers. Support for large scale is essential since systems today are already large and we
can expect them to scale further.
It is secure against Byzantine (arbitrary) faults. Handling Byzantine faults is
important because it captures the kinds of complex failure modes that have been reported
for our target deployments.
Tracking membership Service
In this Module, is only part of what is needed for automatic reconfiguration. We
assume nodes are connected by an unreliable asynchronous network like the Internet,
where messages may be lost, corrupted, delayed, duplicated, or delivered out of order.
While we make no synchrony assumptions for the system to meet its safety guarantees, it
is necessary to make partial synchrony assumptions for liveness.
The MS describes membership changes by producing a configuration, which
identifies the set of servers currently in the system, and sending it to all servers. To allow
the configuration to be exchanged among nodes without possibility of forgery, the MS
authenticates it using a signature that can be verified with a well-known public key.
Byzantine Fault Tolerance
In this Module, to provide Byzantine fault tolerance for the MS, we implement it
with group replicas executing the PBFT state machine replication protocol.
These MS replicas can run on server nodes, but the size of the MS group is small
and independent of the system size. So, to implement from tracking service,
1. Add – It takes a certificate signed by the trusted authority describing the node
adds the node to the set of system members.
2. Remove – It also takes a certificate signed by the trusted authority that identifies
the node to be removed. And removes this node from the current set of members.
3. Freshness – It receives a freshness challenge, the reply contains the nonce and
current epoch number signed by the MS.
4. PROBE – The MS sends probes to servers periodically. It serves respond with a
simple ack, or, when a nonce is sent, by repeating the nonce and signing the
response.
5. New EPOCH – It informs nodes of a new epoch. Here certificate vouching for the
configuration and changes represents the delta in the membership.
Dynamic Replication
In this Module, to prevent attacker from predicting
1. Choose the random number.
2. Sign the configuration using the old shares
3. Carry out a resharing of the MS keys with the new MS members.
4. Discard the old shares
System Configuration
Hardware Requirements
· System : Pentium IV 2.4 GHz.
· Hard Disk : 40 GB.
· Floppy Drive : 1.44 Mb.
· Monitor : 15 VGA Color.
· Mouse : Logitech.
· Ram : 512 Mb
Software Requirements
· Operating system : Windows XP.
· Coding Language : C#.Net
· Database : Sql Server 2005
5
prakash chalumuri
IEEE Dot Net Project - AMPLE: An Adaptive Traffic Engineering System Based on Virtual Routing Topologies
AMPLE: An Adaptive
Traffic Engineering System Based on
Virtual Routing
Topologies
Abstract
Handling traffic dynamics in order
to avoid network congestion and subsequent service disruptions is one of the
key tasks performed by contemporary network management systems. Given the
simple but rigid routing and forwarding functionalities in IP base
environments, efficient resource management and control solutions against
dynamic traffic conditions is still yet to be obtained. In this article, we
introduce AMPLE — an efficient traffic engineering and management system that
performs adaptive traffic control by using multiple virtualized routing
topologies. The proposed system consists of two complementary components: offline
link weight optimization that takes as input the physical network
topology and tries to produce maximum routing path diversity across multiple
virtual routing topologies for long term operation through the optimized
setting of link weights. Based on these diverse paths, adaptive traffic control
performs intelligent traffic splitting across individual routing topologies
in reaction to the monitored network dynamics at short timescale. According to
our evaluation with real network topologies and traffic traces, the proposed
system is able to cope almost optimally with unpredicted traffic dynamics and,
as such, it constitutes a new proposal for achieving better quality of service
and overall network performance in IP networks.
Architecture
Existing system
In Existing System, IGP-based TE
mechanisms are only confined to offline operation and hence cannot cope
efficiently with significant traffic dynamics. There are well known reasons for
this limitation: IGP-based TE only allows for static traffic delivery through
native IGP paths, without flexible traffic splitting for dynamic load
balancing. In addition, changing IGP link weights in reaction to emerging
network congestion may cause routing re-convergence problems that potentially
disrupt ongoing traffic sessions. In effect, it has been recently argued that
dynamic/online route re computation is to be considered harmful even in the
case of network failures, let alone for dealing with traffic dynamics.
Proposed System
In
proposed system consists of two complementary components: offline link
weight optimization that takes as input the physical network topology and tries
to produce maximum routing path diversity across multiple virtual routing topologies
for long term operation through the optimized setting of link weights. Based on
these diverse paths, adaptive traffic control performs
intelligent traffic splitting across individual routing topologies in reaction to
the monitored network dynamics at short timescale.
According to our evaluation with
real network topologies and traffic traces, the proposed system is able to cope
almost optimally with unpredicted traffic dynamics and, as such, it constitutes
a new proposal for achieving better quality of service and overall network
performance in IP networks.
Modules
1. Virtual traffic allocation
2.
Offline Link Weight Optimization
3.
Network Monitoring
4.
Adaptive Traffic Control
Virtual Traffic Allocation
In
this Module, the diverse MT-IGP paths according to the link weights computed by
OLWO. Monitored network and traffic data such as incoming traffic volume and
link utilizations. At each short-time interval, ATC computes a new traffic
splitting ratio across individual VRTs for re-assigning traffic in an optimal
way to the diverse IGP paths between each S-D pair. This functionality is handled
by a centralized TE manager who has complete knowledge of the network topology
and periodically gathers the up-to-date monitored traffic conditions of the operating
network. These new splitting ratios are then configured by the TE manager to
individual source PoP nodes, who use this configuration for remarking the
multi-topology identifiers (MTIDs) of their locally originated traffic
accordingly.
Offline Link Weight
Optimization
In
this module, to determine the definition of “path diversity” between PoPs for traffic
engineering. Let’s consider the following two scenarios of MT-IGP link weight configuration.
In the first case, highly diverse paths (e.g. end-to-end disjoint ones) are available
for some Pop-level S-D pairs, while for some other pairs individual paths are completely
overlapping with each other across all VRTs. In the second case, none of the S-D
pairs have disjoint paths, but none of them are completely overlapping either. Obviously,
in the first case if any “critical” link that is shared by all paths becomes congested,
its load cannot be alleviated through adjusting traffic splitting ratios at the
associated sources, as their traffic will inevitably travel through this link
no matter which VRT is used. Hence, our strategy targets the second scenario by
achieving “balanced” path diversity across all S-D pairs.
Network Monitoring
In
this Module, Network monitoring is responsible for collecting up-to-date
traffic conditions in real-time and plays an important role for supporting the
ATC operations. AMPLE adopts a hop-by-hop based monitoring mechanism that is
similar to the proposal.
The
basic idea is that a dedicated monitoring agent deployed at every PoP node is responsible
for monitoring:
ü The volume of the traffic originated by the
local customers toward other PoPs (intra- PoP traffic is ignored).
ü The utilization of the directly attached inter-PoP
links
Adaptive Traffic Control
In this Module, Measure the incoming traffic volume
and the network load for the current interval as compute new traffic splitting
ratios at individual PoP source nodes based on the splitting ratio
configuration in the previous interval, according to the newly measured traffic
demand and the network load for dynamic load balancing.
System
Requirements:
Hardware
Requirements:
·
System : Pentium IV 2.4 GHz.
·
Hard Disk : 40 GB.
·
Floppy Drive : 1.44 Mb.
·
Monitor : 15 VGA Color.
·
Mouse : Logitech.
·
Ram : 512 Mb.
Software
Requirements:
·
Operating system : - Windows XP.
·
Coding Language : C#.Net
0
prakash chalumuri
IEEE Dot Net Project - A Secure Intrusion detection system against DDOS attack in Wireless Mobile Ad-hoc Network
A
Secure Intrusion detection system against DDOS attack in Wireless Mobile Ad-hoc
Network
ABSTRACT:
Wireless Mobile ad-hoc network (MANET) is an
emerging technology and have great strength to be applied in critical
situations like battlefields and commercial applications such as building,
traffic surveillance, MANET is infrastructure less, with no any centralized
controller exist and also each node contain routing capability, Each device in
a MANET is independently free to move in any direction, and will therefore
change its connections to other devices frequently. So one of the major
challenges wireless mobile ad-hoc networks face today is security, because no
central controller exists. MANETs are a kind of wireless ad hoc networks that
usually has a routable networking environment on top of a link layer ad hoc
network. Ad hoc also contains wireless sensor network so the problems is facing
by sensor network is also faced by MANET. While developing the sensor nodes in
unattended environment increases the chances of various attacks. There are many
security attacks in MANET and DDoS (Distributed denial of service) is one of
them. Our main aim is seeing the effect of DDoS in routing load, packet drop
rate, end to end delay, i.e. maximizing due to attack on network. And with
these parameters and many more also we build secure IDS to detect this kind of
attack and block it. In this paper we discussed some attacks on MANET and DDOS
also and provide the security against the DDOS attack.
EXISTING
SYSTEM:
In existing system, Mobile ad-hoc networks
devices or nodes or terminals with a capability of wireless communications and
networking which makes them able to communicate with each other without the aid
of any centralized system. This is an autonomous
system in which nodes are connected by wireless links and send data to each
other. As we know that there is no any
centralized system so routing is done by node itself. Due to its mobility and
self routing capability nature, there are many weaknesses in its security. One of the serious attacks to be
considered in ad hoc network is DDoS attack. A DDoS attack is launched by sending huge
amount of packets to the target node through
the co-ordination of large amount of hosts which are distributed all over in
the network. At the victim side this
large traffic consumes the bandwidth and not allows any other important packet reached to the victim.
PROPOSED
SYSTEM:
In proposed system, to solve the
security issues we need an intrusion detection system. This can be categorized into two
models:
1. Signature-based intrusion detection
2. Anomaly-based intrusion detection
The benefits of this IDS technique are
that it can be able to detect attack without prior knowledge of attack.
Intrusion attack is very easy in wireless network as compare to wired network.
One of the serious attacks to be considered in ad hoc network is DDoS attack.
MODULES:
1. User Registration
2. Upload & Send files to users
3. Attack on Ad-Hoc Network
4. Criteria for Attack detection
5. Simulation Results
MODULES
DESCRIPTION:
User
Registration:
In this module, user registers his/her
personal details in database.
Each user has unique id, username and
password and digital signature.
After using these details he can request
file from server.
Upload
& Send files to users:
In this module, server can upload the
files in the database. After verify user digital signature file could be
transfer to correct user via mobile ad-hoc network. Attack on Ad-Hoc Network. In this module, to
see what the attack on ad-hoc is network is
Distributed
Denial of Services (DDoS):
A DDoS attack is a form of DoS attack
but difference is that DoS attack is performed by only one node and DDoS is
performed by the combination of many nodes. All nodes simultaneously attack on
the victim node or network by sending them huge packets, this will totally
consume the victim bandwidth and this will not allow victim to receive the
important data from the network.
Criteria
for Attack detection :
In this module, we use multiple nodes
and simulate through different criteria
are NORMAL, DDoS and IDS (intrusion detection case). Normal Case We set number of sender and
receiver nodes and transport layer mechanism as TCP and UDP with routing
protocol as AODV (ad-hoc on demand distance vector) routing. After setting all
parameter simulate the result through our simulator.
IDS
Case
In IDS (Intrusion detection system) we
set one node as IDS node, that node watch the all radio range mobile nodes if
any abnormal behavior comes to our network, first check the symptoms of the
attack and find out the attacker node , after finding attacker node, IDS block
the attacker node and remove from the DDOS attack. In our simulation result we
performed some analysis in terms of routing load , UDP analysis , TCP
congestion window, Throughput Analysis and overall summery. Simulation Results In this module, we
implement the random waypoint movement model for the simulation, in which a
node starts at a random position, waits for the pause time, and then moves to
another random position with a velocity.
a. Throughput
b. Packet delivery fraction
c. End to End delay
d. Normalized routing load
SYSTEM
REQUIREMENTS
Hardware
Requirements:
•
System :
Pentium IV 2.4 GHz.
•
Hard Disk : 40 GB.
•
Floppy Drive : 1.44 Mb.
•
Monitor : 15
VGA Colour.
•
Mouse : Logitech.
•
Ram : 512 Mb.
Software
Requirements:
•
Operating system : Windows XP.
•
Coding Language : C#.NET
•
TOOL :
VISUAL STUDIO 2008
REFERENCE:
Prajeet Sharma, Niresh Sharma, Rajdeep
Singh, “A Secure Intrusion detection
system against DDOS attack in Wireless Mobile Ad-hoc Network”, International
Journal of Computer Applications (0975 – 8887) Volume 41– No.21, March 2012
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