Walmart - where automated systems could be monitoring your purchase history, behavior and working to Speech processing, is well, processing of speech. Take the word butterfly. To use this word it is not necessary to make the voice weigh less than an ounce or equip it with small dusty wings. It is not necessary to invent a sunny day or a field of daffodil What if one mobile could download software updates and then share them with other phones?
This transmission is happening via cloud server.
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Intrusion Detection System in mobile ad hoc network in MAC layer
We have high expectations together and we love to work with thesischandigarh. First, they've deep domain expertise and second, they're open to ideas. We appreciate how like minded partners we are, and have always grown into better results due to the same. Afterwards, the node just drops the packets to launch a DoS denial of service attack. If neighbor nodes that try to send packets over attacking nodes lose the connection to destination, then they may want to discover a route again by broadcasting RREQ messages [ 31 - 34 ].
Latest Topics in Network Security for research and thesis
Jayasingh and B. Swathi [ 35 ] proposed a mechanism that detects the jellyfish attacks at a single node and that can be effectively deployed at all other nodes in the ad hoc network. They gave a solution that detects the jellyfish reorder attack based on the reorder density which is a basis for developing a metric. Timothy et al. Jamming at this layer exploits AODV and TCP protocols and is shown to be very effective in simulated and real networks when it can sense victim packet types, but the encryption is assumed to mask the entire header and contents of the packet so that only packet size, timing, and sequence is available to the attacker for sensing [ 19 ].
Kurkure and Chaudhari [ 37 ] illustrated a comparative analysis of the selfish node detection methods based on detection time and message overhead. In this paper, a collaborative watchdog method was used to identify the selfish nodes and diminish the detection time and message overhead. In this paper, they described about various attacks and techniques used for intrusion detection which were proposed to provide high performance. Patel et al. Ad hoc networks have limited physical security, less infrastructure, restricted power supply, mobility network, and changing network topology [ 40 - 44 ].
Jawhar et al. Various P2P media streaming systems have been deployed successfully, and corresponding theoretical investigations have been performed on such systems [ 46 ]. In this paper, [ 47 ] thoroughly investigates the evolutionary dynamics of soft security mechanism, namely reciprocity-based incentive mechanism, in P2P systems based on evolutionary game theory EGT. Trust management plays an important role in IoT [ 48 - 54 ] for reliable data fusion and mining, qualified services with context awareness, and enhanced user privacy and information security [ 9 ].
It helps people overcome perceptions of uncertainty and risk and engages in user acceptance and consumption on IoT services and applications [ 9 , 55 , 56 ]. However, current literature still lacks a comprehensive study on trust management in IoT [ 9 ]. Authenticated key agreement protocol is a useful cryptographic primitive, which can be used to protect the confidentiality, integrity, and authenticity for transmitted data over insecure networks [ 6 ]. Built upon opportunistic routing and random linear network coding, CodePipe not only simplifies transmission coordination between nodes but also improves the multicast throughput significantly by exploiting both intra-batch and inter-batch coding opportunities [ 10 ].
In particular, four key techniques, namely LP-based opportunistic routing structure, opportunistic feeding, fast batch moving, and inter-batch coding, are proposed to offer substantial improvement in throughput, energy efficiency, and fairness [ 10 ]. In the paper, [ 11 ] proposes a multi-constrained QoS multicast routing [ 12 ] method using the genetic algorithm. The proposal will be flooding limited [ 13 ] using the available resources and minimum computation time in a dynamic environment.
By selecting the appropriate values for parameters such as crossover, mutation, and population size, the genetic algorithm improves and tries to optimize the routes. For the author of this paper [ 57 ], they consider the assignment strategy with topology preservation by organizing the mesh nodes with available channels and aim at minimizing the co-channel interference in the network.
The channel assignment with the topology preservation is proved to be NP-hard and to find the optimized solution in polynomial time is impossible. They have formulated a channel assignment algorithm named as DPSO-CA which is based on the discrete particle swarm optimization and can be used to find the approximate optimized solution [ 57 , 58 ].
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All the above schemes only try to protect the system from the attacker, but not bother about quarantining attackers [ 3 , 16 , 59 ]. The TBUT systems not only detect the mischievous nodes but also prevent their further participation in the network. The security considerations in a TBUT setting are still in their infancy phase and require a more thorough analysis by the research community.
The selfish nodes do not participate in the routing and data transmission process, which intentionally drop the packets. These misbehaviors of the selfish nodes will impact availability, efficiency, reliability, and fairness. The selfish node utilizes the resources for its own purpose, and it neglects to share the resources to other nodes. In the following, a number of potential research directions are introduced.
This approach will save the cost of communication and provide a unifying framework to address the authentication of sensing nodes as well as the sensing data, among other possibilities. Perhaps, solutions to combat attacks against TBUT schemes have been studied more than any other security issues. Still a thorough analysis to compare and contrast existing techniques, such as trust weight fusion versus consensus-based algorithms, can provides further insights into the pros and cons of each scheme and might lead future researchers toward developing more robust solutions.
We classified the agents posing security threats in a TBUT into three categories, namely adversaries, malicious nodes, and silent nodes. Each group will follow a different attack strategy. It is interesting to address the incentives for misbehaviors and attack against a TBUT so as to adopt incentive minimization schemes.