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Bandwidth distributed denial of service attacks and defenses

Bandwidth distributed denial of service attacks and defenses

Distributed denial of service (DDoS) attacks pose a serious threat to the Internet. We discuss the Internet’s vulnerability to Bandwidth Distributed Denial of Service (BW-DDoS) attacks, where many hosts send a huge number of packets exceeding network capacity and causing congestion and losses, thereby disrupting legitimate traffic. TCP and other protocols employ congestion control mechanisms that respond to losses and delays by reducing network usage, hence, their performance may be degraded sharply due to such attacks. Attackers may disrupt connectivity to servers, networks, autonomous systems, or whole countries or regions; such attacks were already launched in several conflicts.

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Bandwidth distributed denial of service attacks and defenses

  1. 1. LeMeniz Infotech 36, 100 feet Road, Natesan Nagar(Near Indira Gandhi Statue, Next to Fish-O-Fish), Pondicherry-605 005 Call: 0413-4205444, +91 99625 88976, 95663 55386. For More Projects Titles Visits : www.lemenizinfotech.com | Call Us : 9962588976 /9566355386 Do Your Projects With Domain Experts APPROXIMATE SHORTEST DISTANCE COMPUTING: A QUERY-DEPENDENT LOCAL LANDMARK SCHEME ABSTRACT The factors that affect the accuracy of distance estimation in landmark embedding is analyzed. It is found that a globally selected, query independent landmark set may introduce a large relative error, especially for nearby query nodes. To address this issue, a query-dependent local landmark scheme is proposed, which identifies a local landmark close to both query nodes and provides more accurate distance estimation than the traditional global landmark approach. An efficient local landmark indexing and retrieval techniques is proposed, which achieve low offline indexing complexity and online query complexity. Two optimization techniques on graph compression and graph online search are also proposed, with the goal of further reducing index size and improving query accuracy. Furthermore, the challenge of immense graphs whose index may not fit in the memory leads us to store the embedding in relational database, so that a query of the local landmark scheme can be expressed with relational operators.
  2. 2. LeMeniz Infotech 36, 100 feet Road, Natesan Nagar(Near Indira Gandhi Statue, Next to Fish-O-Fish), Pondicherry-605 005 Call: 0413-4205444, +91 99625 88976, 95663 55386. For More Projects Titles Visits : www.lemenizinfotech.com | Call Us : 9962588976 /9566355386 Do Your Projects With Domain Experts INTRODUCTION As the size of graphs that emerge nowadays from various application domains is dramatically increasing, the number of nodes may reach the scale of hundreds of millions or even more. Due to the massive size, even simple graph queries become challenging tasks. One of them, the shortest distance query, has been extensively studied during the last four decades. Querying shortest paths or shortest distances between nodes in a large graph has important applications in many domains including road networks, social networks, communication networks, the Internet, and so on. For example, in road networks, the goal is to find shortest routes between locations; while in the Internet, the goal is to find the nearest server to reduce access latency for clients. EXISTING SYSTEM  Breadth-first search (BFS), Dijkstra’s algorithm, and A* search can compute the exact shortest paths in a network, the massive size of modern information networks and the online nature of such queries make it infeasible to apply the classical algorithms online.  It is space inefficient to precompute and store the shortest paths between all pairs of nodes, as it requires space to store the shortest paths and space to store the distances for a graph with n nodes.
  3. 3. LeMeniz Infotech 36, 100 feet Road, Natesan Nagar(Near Indira Gandhi Statue, Next to Fish-O-Fish), Pondicherry-605 005 Call: 0413-4205444, +91 99625 88976, 95663 55386. For More Projects Titles Visits : www.lemenizinfotech.com | Call Us : 9962588976 /9566355386 Do Your Projects With Domain Experts  Estimating the shortest distance between nodes based on graph embeddings. A commonly used embedding technique is landmark embedding, where a set of graph nodes is selected as landmarks and the shortest distances from a landmark to all the other nodes in a graph are precomputed. Such precomputed distances can be used online to provide an approximate distance between two graph nodes based on the triangle inequality. Disadvantages  It is hard to achieve uniformly good performance on all queries PROPOSED SYSTEM  To find a query-dependent “local landmark” which is close to both query nodes for a more accurate distance estimation.  Propose a query-dependent local landmark scheme (LLS), which identifies a local landmark specific to a pair of query nodes.  Then, the distance between the two query nodes is estimated as the sum of their shortest distances to the local landmark, which is much closer than the global one.  To propose a shortest path tree (SPT)-based local landmark scheme, where the shortest path tree rooted at node r is a tree composed of the shortest paths from r to all the other nodes.
  4. 4. LeMeniz Infotech 36, 100 feet Road, Natesan Nagar(Near Indira Gandhi Statue, Next to Fish-O-Fish), Pondicherry-605 005 Call: 0413-4205444, +91 99625 88976, 95663 55386. For More Projects Titles Visits : www.lemenizinfotech.com | Call Us : 9962588976 /9566355386 Do Your Projects With Domain Experts  The SPTs rooted at global landmarks help to select the query-dependent local landmarks between two query nodes. Advantages  More accurate distance estimation.  The query-dependent local landmark scheme is expected to reduce the distance estimation error. CHALLENGES  Cannot afford expensive online computation to find a query-specific local landmark, as it would significantly increase the query processing time.  The shortest distance from a query node to a local landmark needs to be efficiently computed. This distance should not be computed from scratch at the query time.  The embedding index should be compact. The estimation accuracy improvement and the query processing efficiency should not be achieved at the expense of an increase in the offline indexing complexity.
  5. 5. LeMeniz Infotech 36, 100 feet Road, Natesan Nagar(Near Indira Gandhi Statue, Next to Fish-O-Fish), Pondicherry-605 005 Call: 0413-4205444, +91 99625 88976, 95663 55386. For More Projects Titles Visits : www.lemenizinfotech.com | Call Us : 9962588976 /9566355386 Do Your Projects With Domain Experts Hardware requirements: Processor : Any Processor above 500 MHz. Ram : 128Mb. Hard Disk : 10 Gb. Compact Disk : 650 Mb. Input device : Standard Keyboard and Mouse. Output device : VGA and High Resolution Monitor. Software requirements: Operating System : Windows Family. Language : JDK 1.5 Database : MySQL 5.0 Tool : HeidiSQL 3.0

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