Maha Abdelhaq

A local intrusion detection routing security over MANET network

Mobile Adhoc Network (MANET) is a group of wireless nodes that are distributed without relying on any standing network infrastructure. MANET routing protocols were designed to accommodate the properties of a self-organized environment without protection against any inside or outside network attacks. In this paper, we propose a Local Intrusion Detection (LID) security routing mechanism to detect Black Hole Attack (BHA) over Ad hoc On Demand Distance Vector (AODV) MANET routing protocol. In LID security routing mechanism, the intrusion detection is performed locally using the previous node of the attacker node instead of performing the intrusion detection via the source node as in Source Intrusion Detection (SID) security routing mechanism. By performing LID security routing mechanism, the security mechanism overhead would be decreased. Simulation results using the GloMoSim simulator show that the improvement ratio of the throughput gained by LID security routing mechanism and overall improvement reduction in the end-to-end delay and routing overhead.

Dynamic packet beaconing for GPSR mobile ad hoc position-based routing protocol using fuzzy logic

Greedy perimeter stateless routing (GPSR) is a well-known position-based routing protocol in mobile ad hoc network (MANET). In GPSR, nodes use periodic beaconing (PB) strategy in broadcasting beacon packets to maintain up-to-date information on the geographical position of their neighbor nodes within their transmission boundary range. The nodes that receive beacon packets save all known neighbor nodes, along with their geographical position information, in their neighbor list to make effective routing decisions. Most recent studies on position-based routing protocols assume that the position information in the neighbor list of a node is accurate, although only a rough estimate of such position information is actually available to the node. Node mobility causes frequent network topology changes in MANETs. Thus, neighbor-to-neighbor relationships change frequently. Using the PB strategy leads to inaccurate node position information in the neighbor list of a node. In addition, it may cause the routing protocol to make suboptimal decisions and not route packets through the best-located neighbor within the transmission range of the node. This study presents an analysis of the influence of position information inaccuracy caused by network parameters such as beacon packet interval time (BPIT) and node moving speed (NMS) on the performance of GPSR position-based routing protocols. To overcome the effect of position information inaccuracy in the neighbor list of a node, we proposed a fuzzy logic dynamic beaconing (FLDB) strategy to improve the reliability of the neighbor list of a node by optimizing time between transmissions of beacon packets in position-based routing protocols. Optimization is based on the correlation between NMS, number of neighboring nodes (NoNNs) and BPIT using fuzzy logic control (FLC) mechanism. The simulation experiment shows the effectiveness of the FLC mechanism in improving overall performance of GPSR position-based routing protocol in terms of beacon packet control overhead, end-to-end delay, non-optimal hop, and false node position.

Enhanced binary exponential backoff algorithm for fair channel access in the ieee 802.11 medium access control protocol

The medium access control protocol determines system throughput in wireless mobile ad hoc networks following the ieee 802.11 standard. Under this standard, asynchronous data transmissions have a defined distributed coordination function that allows stations to contend for channel usage in a distributed manner via the carrier sensing multiple access with collision avoidance protocol. In distributed coordination function, a slotted binary exponential backoff BEB algorithm resolves collisions of packets transmitted simultaneously by different stations. The BEB algorithm prevents packet collisions during simultaneous access by randomizing moments at stations attempting to access the wireless channels. However, this randomization does not eliminate packet collisions entirely, leading to reduced system throughput and increased packet delay and drop. In addition, the BEB algorithm results in unfair channel access among stations. In this paper, we propose an enhanced binary exponential backoff algorithm to improve channel access fairness by adjusting the manner of increasing or decreasing the contention window based on the number of the successfully sent frames. We propose several configurations and use the NS2 simulator to analyze network performance. The enhanced binary exponential backoff algorithm improves channel access fairness, significantly increases network throughput capacity, and reduces packet delay and drop. Copyright

Using dendritic cell algorithm to detect the resource consumption attack over MANET

Artificial Immune Systems (AISs) and Mobile Ad Hoc Networks (MANETs) are two up to date attractive technologies. AIS is utilized to introduce efficient intrusion detection algorithms to secure both host based and network based systems, whilst MANET is defined as a collection of mobile, decentralized, and self organized nodes. Securing MANET is a problem which adds more challenges on the research. This is because MANET properties make it harder to be secured than the other types of static networks. We claim that AIS properties as robust, self-healing, and self-organizing system can meet the challenges of securing MANET environment. This paper objective is to utilize the benefits of one of the Danger Theory based AIS intrusion detection algorithms, namely the Dendritic Cell Algorithm (DCA) to detect a type of Denial of Service (DoS) attack called Resource Consumption Attack (RCA) and also called sleep deprivation attack over MANET. The paper introduces a Mobile Dendritic Cell Algorithm (MDCA) architecture in which DCA plugged to be applied by each MANET node.

Energy Efficient Multipath Routing Protocol for Mobile Ad-Hoc Network Using the Fitness Function

Mobile ad hoc network (MANET) is a collection of wireless mobile nodes that dynamically form a temporary network without the reliance of any infrastructure or central administration. Energy consumption is considered as one of the major limitations in MANET, as the mobile nodes do not possess permanent power supply and have to rely on batteries, thus reducing network lifetime as batteries get exhausted very quickly as nodes move and change their positions rapidly across MANET. This paper highlights the energy consumption in MANET by applying the fitness function technique to optimize the energy consumption in ad hoc on demand multipath distance vector (AOMDV) routing protocol. The proposed protocol is called AOMDV with the fitness function (FF-AOMDV). The fitness function is used to find the optimal path from source node to destination node to reduce the energy consumption in multipath routing. The performance of the proposed FF-AOMDV protocol has been evaluated by using network simulator version 2, where the performance was compared with AOMDV and ad hoc on demand multipath routing with life maximization (AOMR-LM) protocols, the two most popular protocols proposed in this area. The comparison was evaluated based on energy consumption, throughput, packet delivery ratio, end-to-end delay, network lifetime and routing overhead ratio performance metrics, varying the node speed, packet size, and simulation time. The results clearly demonstrate that the proposed FF-AOMDV outperformed AOMDV and AOMR-LM under majority of the network performance metrics and parameters.

Reliable Buffering Management Algorithm Support for Multicast Protocol in Mobile Ad-hoc Networks

Multicasting is one of the relevant issues of communication in infrastructure or centralized administration networks. The reliable delivery of multicast data packets needs feedback from all multicast receivers to indicate whether a retransmission is necessary. A reliable multicast delivery in the wireless Ad-hoc network requires a multicast packet to be received by all multicast receiver nodes. Thus, one or all members need to buffer data packet for possible error recovery. Furthermore, different buffer strategies are essentially used in existing reliable multicast protocols towards support error recovery and reducing buffer overflow. This study proposed two algorithms to improve the performance of the source tree reliable multicast (STRM) protocol. The first algorithm was developed to avoid buffer overflow in the sender node as the forward server (FS) nodes of STRM. This reduction is achieved by managing the buffer of the FS nodes, i.e., selecting the FS nodes depending on its empty buffer size and reducing the feedback sent from the receiver nodes to their FS node. The second algorithm was developed to decrease duplicated packets in the multicast members of the local group, which may be achieved by sending the repair packets to the requesting member. The FS in the local group should create a dynamic and temporary subgroup whose members are only those that requested the repair packet retransmission. The algorithms were tested using detailed discrete event simulation models encompassing messaging systems including error, delay, and mobility models to characterize the performance benefits of the proposed algorithms compared with the existing wireless Ad-hoc network protocols. Several experiments were conducted, revealing numerous results that verify the superior performance of the proposed algorithms over the existing algorithms.

Securing Mobile Ad Hoc Networks Using Danger Theory-Based Artificial Immune Algorithm

A mobile ad hoc network (MANET) is a set of mobile, decentralized, and self-organizing nodes that are used in special cases, such as in the military. MANET properties render the environment of this network vulnerable to different types of attacks, including black hole, wormhole and flooding-based attacks. Flooding-based attacks are one of the most dangerous attacks that aim to consume all network resources and thus paralyze the functionality of the whole network. Therefore, the objective of this paper is to investigate the capability of a danger theory-based artificial immune algorithm called the mobile dendritic cell algorithm (MDCA) to detect flooding-based attacks in MANETs. The MDCA applies the dendritic cell algorithm (DCA) to secure the MANET with additional improvements. The MDCA is tested and validated using Qualnet v7.1 simulation tool. This work also introduces a new simulation module for a flooding attack called the resource consumption attack (RCA) using Qualnet v7.1. The results highlight the high efficiency of the MDCA in detecting RCAs in MANETs.

Mobile Ad Hoc Network Energy Cost Algorithm Based on Artificial Bee Colony

A mobile ad hoc network (MANET) is a collection of mobile nodes that dynamically form a temporary network without using any existing network infrastructure. MANET selects a path with minimal number of intermediate nodes to reach the destination node. As the distance between each node increases, the quantity of transmission power increases. The power level of nodes affects the simplicity with which a route is constituted between a couple of nodes. This study utilizes the swarm intelligence technique through the artificial bee colony (ABC) algorithm to optimize the energy consumption in a dynamic source routing (DSR) protocol in MANET. The proposed algorithm is called bee DSR (BEEDSR). The ABC algorithm is used to identify the optimal path from the source to the destination to overcome energy problems. The performance of the BEEDSR algorithm is compared with DSR and bee-inspired protocols (BeeIP). The comparison was conducted based on average energy consumption, average throughput, average end-to-end delay, routing overhead, and packet delivery ratio performance metrics, varying the node speed and packet size. The BEEDSR algorithm is superior in performance than other protocols in terms of energy conservation and delay degradation relating to node speed and packet size.

Dendritic Cell Fuzzy Logic Algorithm over Mobile Ad Hoc Networks

A mobile ad hoc network (MANET) is an open wireless network of mobile, decentralized, and self-organized nodes with limited energy and bandwidth resources. The MANET environment is vulnerable to dangerous attacks, such as flooding-based attacks, which paralyze the functionality of the whole network. This paper introduces a hybrid intelligent algorithm, which can meet the challenge of protecting MANET with effective security and network performance. This objective is fulfilled by inspiring the abstract anomaly detection of dendritic cells (DCs) in the human immune system and the accurate decision-making functionality of fuzzy logic theory to introduce a dendritic Cell Fuzzy Algorithm (DCFA). DCFA combines the relevant features of danger theory-based AISs and fuzzy logic theory-based systems. DCFA is verified using QualNet v5.0.2 to detect resource consumption attack. The results show the efficient capability of DCFA to perform the detection operation with high network and security performance.