Performance Analysis of Privacy Protection System During Data Transfer in MANETs

The openness of a Mobile Adhoc network (MANET) makes it vulnerable to various attacks that can breach privacy, and this demands a privacy protection system. In this paper, we propose a privacy protection system with flexible and adaptable policies to protect privacy during data transfer based on application and context attributes. We also provide the performance analysis model to test the suitability of policies for maintaining privacy, which is essential for the real-time implementation of this system in a resource-limited MANET. Finally, the proposed privacy protection system is compared with previous works using simulations, and the results obtained show the effectiveness of the proposed privacy protection system.     

Honeypot Based Black-Hole Attack Confirmation in a MANET

Many solutions are proposed to identify or prevent the attacks in a Mobile Ad hoc Network. However, sometimes these systems detect false attacks. This could lead to loss of resources in a mobile ad hoc network and cause a downgrade in quality of service. Hence mobile ad hoc networks need a system to confirm the attack before taking further actions. In our work presented in this paper, we propose an attack confirm system for a malicious attacker, called the Black-hole attacker. We present our Black-hole attack Confirmation System, which identifies and confirms the black-hole attack in a mobile ad hoc network using honeypot. The honeypot intelligently identifies all the possible types of black-hole attack using the Black-hole Attack tree, and confirms the attack using the Attack History Database. Together, the Black-hole Attack tree, and Attack History Database aid the honeypot in reducing the false alarms in the mobile ad hoc network. We have simulated the proposed system in several mobile ad hoc network environments of varying sizes of nodes and applications. On several occasions the results have demonstrated that the proposed system is efficient in confirming the black-hole attack and saving the resources and minimizing the path re-establishment.     

Performance of a wireless access protocol on correlatedRayleigh-fading channels with capture

The throughput performance of a wireless media access protocol taking into account the effect of correlated channel fading, capture, and propagation delay is analyzed. For efficient access on the uplink (mobile-to-base-station link), the protocol makes use of the uplink channel status information which is conveyed to the mobiles through a busy/idle flag broadcast on the downlink (base-station-to-mobile link). A first-order Markov model is used to describe the correlation in the packet success/failure process on a Rayleigh-fading channel. The analytical results obtained through the first-order Markov approximation of the channel are compared to those obtained from an independent and identically distributed (i.i.d.) channel model. The Markovian-fading channel model is shown to provide better performance results than the i.i.d. channel model. Simulations show that a first-order Markov approximation of the Rayleigh-fading process is quite accurate. An enhanced version of the access protocol to take advantage of the memory in the fading channel behavior is proposed and analyzed. The effect of retransmission of erroneous data packets and propagation delay on the throughput is also analyzed. It is shown that the access protocol with an error detect (ED) feature is efficient in slow fading (e.g., pedestrian user speeds), whereas a retransmission protocol is more efficient in fast fading (e.g., vehicular user speeds)     

Network fault diagnosis using a realistic abductive reasoning model

This paper proposes a method to solve the network fault diagnosis problem using the Realistic Abductive Reasoning Model. This model uses an abductive inference mechanism based on the parsimonious covering theory, and adds some new features to the general model of diagnostic problem-solving. The network fault-diagnosis knowledge is assumed to be represented in the form of causal chaining, namely, a hyper-bipartite graph. A layered graph is constructed from the given hyper-bipartite graph by the addition of a few dummy nodes. Then the diagnostic problem is solved, starting from the lowest layer of the layered graph, as a series of bipartite graphs, until the top-most layer is reached. The inference mechanism uses a Realistic Abductive Reasoning Model to diagnose the faults in a communication network, which is symptom-driven, based on some application programs. The hypothesis-test paradigm is used to refine the solution space. The fault-diagnostic capability of the proposed inference model is demonstrated by considering one node of a given network where the management information would be used to diagnose its local problems and the connectivity of the node in the network. The results obtained by the proposed model substantiate its effectiveness in solving network fault-diagnostic problems.     

Preserving Data Privacy During Data Transfer in MANETs

Mobile adhoc networks consists of large number of mobile nodes, and is usually deployed to transfer data from a sender to a receiver using multi-hop routing. The data being transmitted may contain sensitive information, and undesired disclosure of information can lead to launching of various attacks, thus breaching the data privacy. Earlier works achieve data privacy by using approaches such as data transformation and data perturbation. However, these approaches introduce higher overheads and delays. We propose a computational intelligence based data privacy preserving scheme, where rough set theory is used to anonymize the data during data transfer. Data packets are enclosed within capsules that can be opened only by the designated node, thus preventing the undesired leakage of the data. Also, route between a sender and a receiver is changed dynamically by selecting more than one trusted 1-hop neighbor nodes in each routing step. The proposed data privacy preserving scheme is tested by considering different case studies in a MANET deployed for stock market. Theoretical analysis for data privacy is presented in terms of Information Gain by an attacker and Attacker Overhead, and the performance of proposed scheme against some of the attacks is also discussed. The simulation results show the effectiveness of proposed scheme.

     

Mobile agent based approach for QoS routing

A mobile agent based on-demand quality of service (QoS) unicast routing scheme for supporting multimedia applications is proposed that considers bandwidth, delay and packet loss as QoS metrics for feasible path computation. A mobile agent is employed to find multiple QoS paths and select a best path among them to preserve resources so as to increase call success ratio and network bandwidth utilisation as well as adapt to network dynamics. The scheme is simulated in various network scenarios (sparse and dense networks) to verify performance and operation effectiveness, and compared with RSVP-based QoS routing by using an internet routing protocol. The results demonstrate significant improvements in call success ratio and network bandwidth utilisation compared with RSVP-based QoS routing, both in case of sparse and dense networks. Benefits of the agent-based scheme are adaptability, flexibility, and support for component-based software engineering features such as software reuse, customisation and maintainability     

Effect of sugars on freeze-thaw and lyophilization of liposomes

Various sugars were investigated for their ability to protect liposomes against fusion and leakage during freeze-and-thaw or lyophilization processes. Size of liposome was measured before and after the events with a light scattering technique. Leakage of the content of the sulfate, was encapsulated in the liposome which was made of egg phosphatidylcholine (EPC)/egg phosphatidylglycerol (EPG)/cholesterol (5:1:2). Addition of 1% lactose to the liposome suspension prevented the fusion between liposome but not the leakage of the content. Freeze-thawing caused more damage to the liposomes than the freeze-drying/reconstitution. After freeze-thawing, one-third of the encapsulated drug leaked out from the liposome. The freeze-drying did not cause additional leakage.     

Controlled Release of Griseofulvin from Coprecipitates with Phospholipids

The release of griseofulvin from griseofulvin: phospholipid coprecipitates has been studied as a function of 1) the fatty ester chain length of phosphatidylcholine, 2) the choice of solvent in forming coprecipitates, and 3) the ratio of phospholipid: cholesterol in the lipid component. Only coprecipitates containing 95%w/w and 80%w/w griseofulvin were examined. The release kinetics and total release after 60 min correlates with the phase transition temperatures of the various phosphatidylcholines. The addition of cholesterol diminishes the initial release rates but increases the total amount released after 60 min when the phospholipid:cholesterol mole ratio is greater than unity. The role of chloroform as an enhancer of the release process and the phospholipid as a solubilizer of griseofulvin is demonstrated.     

A Method for Resource and Service Discovery in MANETs

The paper presents a novel resource and service discovery mechanism for MANETs using Routing Intelligent Mobile Agents(RIMAs). RIMAs periodically collect routing, resource and service availability information and index the same in appropriate RIMA nodes. Every mobile node is close to atleast one RIMA node. The mobile node running an application in need of a resource or a service dispatches a Discovery agent to its nearest RIMA node. The index available at the RIMA node will guide the Discoverer agent to the resource or service node. Analysis of the method reveals the computational complexity to be of the order of square of number of RIMA nodes. Communication overheads are the product of number of generated agents, agent size and number of hops travelled by an agent. The method has been simulated and tested on MANETs of varying sizes from 50 to 800 nodes. Simulation snapshots and results show the proper working and success of the algorithm. Basavaraj Talwar is a Research Assistant at the Protocol Engineering & Technology Unit in Electrical Communication and Engineering department in Indian Institute of Science, Bangalore, India. He is research interests include Applications of mobile agents in MANETs and mobile commerce security. Prof. Pallapa Venkataram is the Chief Programming Executive of Protocol Engineering & Technology Unit, Electrical Communication and Engineering department in Indian Institute of Science, Bangalore, India. He has over 160 publications at various levels. His research interests include Protocol Engineering, Mobile Agents, Mobile Commerce, Wireless Networks, Mobile Computing, Artificial Intelligence. He is a senior member of IEEE and has received numerous awards and other fellowships for his contributions. Prof. Lalit M. Patnaik is currently associated with Computer Science and Automation department in Indian Institute of Science, Bangalore, India. He has currently over 400 publications at various levels. His research interests include Computer Architecture, Parallel & Distributed Computing, CAD of VLSI Systems, Real-Time Systems, Soft Computing, Engineering Applications of Information Technology, Mobile Computing, Computational Neuroscience. He is a fellow of IEEE and has received numerous awards and other fellowships for his contributions.     

A Neural Network-Based Connectivity Management for Mobile Computing Environment

The mobile computing environment experiences wireless problems and suffers from limited bandwidth, which leads to frequent disconnections. This has posed a challenge in maintaining user-to-user connectivity in the mobile computing environment. In this paper, we propose a neural network (NN) based connectivity management for mobile computing environment to maintain the mobile user-to-user connectivity throughout the transaction. Here the connectivity management maintains the status information of mobile hosts at the base station to handle frequent disconnection of mobile hosts (MHs), which occur because of hand-offs and interruptions. The disconnection of an MH because of wireless problems is called interruption, and the disconnection due to MH crossing the cell boundary is called hand-off. The neural networks are trained with respect to the status information to provide an intelligent decision for the connectivity management. The simulation results demonstrate that the proposed technique performs well in terms of percentage acceptance of disconnections and resource utilization (bandwidth and buffer) for the volatile mobile computing environment. It is also observed that the intelligent decision by neural network has improved the performance of the system.