Ieee Research Paper On Networking

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Ieee Research Paper On Networking



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The articles are intended to be surveys or tutorials, slanted towards the practical, and comprehensible to. Larry Peterson, a leader of experimental research that evaluates new ideas through large-scale worldwide deployment studies incorporating real prototypes, has revolutionized networking research. Thesis and Research Topics in Computer Networking.

Students who find programming complex and challenging mostly go for networking field in computer science engineering. But even after indulging in this field they are often confused about which topic to choose for the project or for an M. Tech thesis. Here is the list of some of the good topics in computer networking with a basic introduction. It is considered to be the best conference in the field that attracts a large number of attendees each year. CNERT will greatly help to build a stronger and larger community who are interested in experimentation-based research and development.

The course will cover the main drivers, uses, key benefits, current trends and underlying technologies around the concept of an SDN control plane. This paper describes how the concept of distributed computing came into existence based on the advantages and disadvantages that raised in earlier networking concepts. The concept of distributed computing speaks that once data is available within the server s , it should be able to be accessed and processed from any kind of client device like computer, mobile phone, PDA, etc.

ICSCAN aims at bringing together researchers, scientists, engineers, research scholars, industrial participants and budding students around the world to a common platform to share their experiences, new ideas, and research findings on all aspects of Electrical, Electronics, Communication, Computer and Mechanical Engineering. Experimentation has played an important role in advancing research in computing and networking.

Although simulation is an important tool for studying and. Working with science teams across disciplines, we are finding new ways to fight disease, combat poverty and homelessness, grow heartier crops, and better predict natural disasters. This workshop will bring together researchers and technical experts to share experiences and advance the state of the art in experimental research in areas such as networking, distributed systems, and cloud computing. It aims to inspire researchers to use testbeds in novel and interesting ways as a means to validate research ideas. These inherent complexities and unpredictable nature of data made this research a good candidate for Artificial Neural Networks ANN.

This research analyses only 4 parameters to detect an attack. This considerably reduces the overhead of the monitoring machine whilst producing the results expected. The rest of the paper is organized as follows. Section 2 discusses the related work. Section 3 discusses the IEEE Section 4 explains the philosophy behind our research. Section 5 presents WLAN environment of the experiment and computer simulation prototype and Section 6 discusses simulation results.

Many researchers have worked in this area looking for possible solutions. For example, [7] presents a detailed review of most popular non-intelligent methods of detecting and preventing DoS attacks in MAC layer and [8] evaluates some commonly used non-cryptographic methods of MAC spoof detection in WLANs. Cryptography may be the most reliable solution. But, it is expensive, may require a protocol repair and can easily be a DoS target itself. However, this solution requires a change in the wireless card. A hardware upgrade is an unrealistic solution considering the number of wireless cards that will have to change. Ratnayake et al. Detection of spoofed frames plays a major role in detection of other attacks including probe request attacks.

They improved [12] solution by utilising transmission rate and by sending a probe request after every 9th frame. However, this solution generates an additional overhead on the network. Above discussed non-intelligent WIDS methods use statistical, rule based, expert knowledge or pattern recognition approaches on known vulnerabilities or attack signatures and therefore consumes time, lacks flexibility to adaptation to environmental changes, and eventually becomes out-dated.

This solution detects attacks only by calculating probe requests per second. It also responds to the attacker with a DoS attack in return, which can lead to attacking a own user. This large and complex system was never implemented according to our knowledge. This solution does real time monitoring, but the solution is based only on sequence number anomalies. They propose a comparatively complex architecture for WIDS using ANNs based on real time data and tests virtual carrier sense, association flood, and de-authentication attacks. The solution focuses on the behaviour of the complete network, which can be challenging in a real network which has larger number of users. Further, it is observed that some of these solutions are extremely complex and are simulated and tested without considering the practical implementation and computing power they may require.

Therefore, these solutions are limited for academic research world as implementing is too complex or expensive. In passive scan, STA listens to successive channels, waiting to hear a beacon frame from an AP, while in an active scan, the STA broadcasts a probe request message on every channel its physical layer supports, until the STA finds an AP. These frames are unprotected and information passed between the frames can be read using freely available software like Wireshark [23,24,25].

Association to a network is not required to probe and receive a response. Usually, probing is the initial phase of any other attack in computer networks [19]. The management frames establish and maintain communications. The control frames help in the delivery of data. Frame body contains information specific to the frame type and subtype. The below is a simple analysis of data captured during an attack on a test-bed.

Analysis of sequence numbers generated by a single MAC address Sequence number of the MAC frame is a bit counter that starts from 0 when a NIC starts or resets, and wraps on at the overflow. Theoretically, a NIC can generate only one set of sequence numbers at a time [24]. However, Fig. The straight sharp lines starting at These parallel sequence number patterns may have generated due to QoS or packet delays [5].

Frame sub-type of the MAC frame identifies the type of the data frame [24]. Spoofed attacker cannot associate with the network without knowing the network key. Hence, other frame- sub-types have a lower frequency. Therefore, SSI patterns are useful in detecting spoofed attacks. In Fig. Unusual SSI patterns were generated during the spoofed attack from The delta time value of a Wireshark captured frame indicates the time since the previous packet was captured. This is also useful in detecting attacks, as it gives an indication of the server response time, network round-trip time, and other delays.

Analysing frames of a WLAN test bed manually or statistically and detecting probing attacks are possible due to its controlled nature. However, a WIDS should be able to capture and analyse frames, and detect attacks automatically in a live environment that is unpredictable by nature. Therefore, after considering different models and their possible realistic and efficient application on detection of probe request attacks, the research utilised a supervised feed-forward NN architecture with 4 input neurons, 2 hidden layers with 20 sigmoid hidden neurons and an output layer with one linear output neuron which classify genuine frames from rogue frames.

WLAN including two attackers and a network monitor Fig. Wireshark network monitoring software was used for data capturing. Test3-PC was kept on promiscuous mode. Monitoring was restricted to IEEE Data capturing was performed for 75 minutes. Both user and attacker performed start-up and shut down procedures, network scans, a network connect and disconnect procedures, and a NIC repair. The captured data set consisted of K frames. Frames generated from MAC address c:fb: dd:b3 were filtered using to prepare a training sample and labelled manually as rouge or genuine. The training sample consisted of approximately K frames that were generated from MAC address c:fb:dd:b3. The network is trained using Levenberg-Marquardt back propagation algorithm.

The mean squared errors of training, validation and testing were 3. Training, validating and testing were converged outstandingly resulting overall regression value 0. The results were generated based on frame samples. Table 1. The NN is also tested against the mobility effect of an attacker and a user. The detection rate drops when a genuine user scans a network excessively which generates unusually a large number of probe requests. However, the issue can be solved within the system by setting a threshold value of warnings to be tolerated per second to suit to specific users or network.

The research considered choosing only few variables to develop a WIDS considering the large data volume and computation power required for real-world implementation. Sequence number and frame sub-type of a MAC frame and signal attributes SSI and delta time values are the 4 independent variables that were carefully chosen by the research based on the following situations; Manipulation of these variables is nearly impossible.

However, the precision and effectiveness of this technique is doubtful as they cannot predict the behaviour of the user STA, whether the STA is starting or resetting its NIC card or transmitting data or idling. Some argue that SSI can be manipulated by attackers controlling the NIC signal strength, moving close to the user STA or signal strength can simply fluctuate due to environmental factors. This is also more of a theoretical issue than a practical one as the attacker cannot perform all these activities in a WLAN without exposing itself.

Some argue that excessive probe request frames can be generated by an ill-configured STA or a genuine user repeatedly attempting to log-in to the AP. In this instance, network administrator can correct if there are any problems with a genuine STA or the user. This solution also works when the genuine user is offline. Finally, each of the individual variables has the potential of indicating the possibility of a spoofed STA and a probe request attack.

Disclaimer Notice. How to write a reflection paper? 0 What common French phrases should you learn for a vacation in Paris? Account Sign In. The growing interest in Ny bar exam essay tutor roadmaps spans a wide range Ieee research paper on networking IEEE organizational units. Unusual SSI patterns were generated during the spoofed attack from