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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

IEEE Dot Net Project- BECAN: A Bandwidth-Efficient Cooperative Authentication Scheme for Filtering Injected False Data in Wireless Sensor Networks

  • Thursday, December 27, 2012
  • prakash chalumuri

  • 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
    Fig. 1

    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

    IEEE Dot Net Project - Automatic Reconfiguration for Large-Scale Reliable StorageSystems

  • prakash chalumuri

  • 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 Reconfiguration
    2. 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

    IEEE Dot Net Project - AMPLE: An Adaptive Traffic Engineering System Based on Virtual Routing Topologies

  • prakash chalumuri


  • 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

    IEEE Dot Net Project - A Secure Intrusion detection system against DDOS attack in Wireless Mobile Ad-hoc Network

  • prakash chalumuri


  • 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