Current Issue : January - March Volume : 2020 Issue Number : 1 Articles : 5 Articles
Nearest neighbor (NN) models play an important role in the intrusion detection system (IDS). However, with the advent of the era\nof big data, the NN model has the disadvantages of low efficiency, noise sensitivity, and high storage requirement. This paper\npresents a neighbor prototype selection method based on CCHPSO for intrusion detection. In the model, the prototype selection\nand feature weight adjustment are performed simultaneously and k-nearest neighbor (KNN) is used as the basic classifier. To deal\nwith large-scale optimization problems, a cooperative coevolving algorithm based on hybrid standard particle swarm and binary\nparticle swarm optimization, which employs the divide-and-conquer strategy, is proposed in this paper. Meanwhile, a fitness\nfunction based on the accuracy and data reduction rate is defined in the CCHPSO to obtain a set of appropriate prototypes and\nfeature weights. The KDD99 and NSL datasets are used to assess the effectiveness of the method. The empirical results indicate that\nthe data reduction rate of the proposed method is very high, ranging from 82.32% to 92.01%. Compared with all the data used, the\nproposed method can not only achieve comparable accuracy performance but also save a lot of storage and computing resources....
Internet Protocol (IP) multicasting is a method for one-to-many and many-to-many\ncommunication between hosts in an IP network. This communication happens in a real-time synchronous\nfashion. It is a useful mechanism for distributing management data in a Local Area Network (LAN).\nManagement data includes frequent updating of host Operating System (OS), security patches, OS update\nfor network hardware, new configuration updates, etc. In the absence of any admission control or a source\nidentification, any host with malicious intent can disseminate malicious codes or rootkits exploiting\nthe underlying multicast framework. Routing protocols like RIPv2 and OSPF use a certain form of\nauthentication to exchange routing information with their peer routers. However, their authentication and\nthe distribution of routing information in its present form has several security and performance-related\nissues. Motivated through these problems, in this paper, we propose an efficient and scalable multicast\narchitecture for distributing management and routing information in a LAN.We use Core-based Tree\n(CBT) for constructing the multicast delivery tree and the pseudo identity-based encryption of the\nunderlying cryptosystem. We also demonstrate that our proposed multicast architecture is immune to a\nnumber of popular attacks....
With the rapid development of Internet of things technology, the application of intelligent devices in the medical industry has become\nubiquitous. Connected devices have revolutionized clinicians and patient care but also made modern hospitals vulnerable to cyber\nattacks. Among the security risks, botnets are of particular concern, which can be used to control thousands of devices for remote data\ntheft and equipment destruction. In this paper, we propose a non-Markovian spread dynamics model to understand the effects of\nbotnet propagation, which can characterize the hybrid contagion situation in reality. Based on the Susceptible-Adopted-Recovered\nmodel, we introduce nonredundant memory spread mechanism for global propagation, as a tuner to adjust spreading rate difference.\nFor describing the proposed model, we extend a heterogeneous edge-based compartmental theory. Through extensive numerical\nsimulations, we reveal that the growth pattern of the final adoption size versus the information transmission probability is discontinuous\nand how the final adoption size is affected by hybrid ratio alpha, global scope control factor ......
This paper presents G-DCF, a MAC protocol for wireless LANs that can improve system spectral efficiency of wireless LANs by\nallowing more concurrent transmissions. The 802.11 DCF creates exposed terminals which are nodes that can transmit successfully\nbut are blocked by carrier sensing. More potential exposed terminals are created when APs are densely placed, limiting\nspatial reuse of channels and thus system throughput. In order to allow concurrent transmissions from exposed terminals, G-DCF\nestablishes groups in the network. Members of a group are nodes located within the carrier sense range of each other but can\ntransmit packets concurrently. Whenever one member of a group wins the channel and transmits its packet, other nodes in the\ngroup also start transmission, triggered by the group ID included in the preamble. Contention window is adjusted according to the\ngroup size for fair share of the channel. Performance evaluations show that G-DCF can significantly improve system throughput\nand fairness over 802.11 DCF, especially when the APs are densely deployed....
Vehicular networks is a key technology for efficiently communicating both userâ??s devices and cars for timely information regarding\nsafe driving conditions and entertaining applications like social media, video streaming, and gaming services, among\nothers. In view of this, mobile communications making use of cellular resources may not be an efficient and cost-effective\nalternative. In this context, the implementation of light-fidelity (LiFi) in vehicular communications could be a low-cost, high-datarate,\nand efficient-bandwidth usage solution. In this work, we propose a mathematical analysis to study the average throughput in\na road intersection equipped with a traffic light that operates as a server, which is assumed to have LiFi communication links with\nthe front lights of the vehicles waiting for the green light. We further assume that the front vehicle (the car next to the traffic light)\nis able to communicate to the car immediately behind it by using its own tail lights and the front lights of such vehicle, and so on\nand so forth. The behavior of the road junction is modeled by a Markov chain, applying the Queueing theory with an M/M/1\nsystem in order to obtain the average queue length. Then, Littleâ??s theorem is applied to calculate the average waiting delay when\nthe red light is present in the traffic light. Finally, the mathematical expression of the data throughput is derived....
Loading....