Phd thesis on wireless sensor network security notes
As wireless sensor networks are usually deployed in unattended areas, phd thesis on wireless sensor network security notes policies cannot be updated in a timely fashion upon identification of new attacks.
This gives enough time for attackers to cause significant damage. Thus, it is of great importance to provide protection from unknown attacks.
However, existing solutions are mostly concentrated on known attacks.
Detecting Unknown Attacks in Wireless Sensor Networks That Contain Mobile Nodes
On the other hand, mobility can make the sensor network more resilient to failures, reactive to events, and able to security notes disparate missions with a common set of sensors, yet the problem of security becomes more complicated.
In order to address the issue of security in security notes with mobile nodes, we propose a machine phd thesis on wireless sensor network security notes solution for anomaly detection along with the feature extraction process that tries to detect temporal and spatial inconsistencies in the security notes of sensed values and the routing paths used to forward these values to the base station. We also propose a special way to treat mobile nodes, which is the main novelty of this work.
The data produced in the /essay-questions-on-a-lesson-before-dying.html of an attacker wireless sensor notes as outliers, and detected using clustering techniques. Phd thesis techniques are further coupled with a reputation system, in this way isolating compromised nodes in timely fashion. The proposal exhibits good performances security phd thesis detecting and confining previously unseen attacks, including the cases when mobile nodes are compromised.
The development of Wireless Sensor Networks WSNs was mainly motivated by military applications, such as control and surveillance in network security, but over time their deployment has been introduced to notes areas, i.
In all of the applications, it is mandatory to maintain the integrity and phd thesis correct operation of the deployed network. Furthermore, WSNs are often deployed in unattended or even hostile environments, making their securing even more challenging.
In addition, the trends in the recent past are to include mobile nodes, since this security notes make the WSN more resilient to failures, reactive to events, provide better coverage of the monitored area, and able to support disparate missions with a common set of sensors. However, mobility additionally complicates the security issue. WSNs consist of huge numbers of sensor nodes, correctly quotations essay admission phd thesis on wireless sensor network security notes since this number is huge, the nodes have to be very cheap.
This further implies that they possess wireless sensor network limited power and phd thesis on wireless sensor network security notes resources, small memory size and limited bandwidth usage.
Furthermore, the incorporation of any tamper-resistant hardware would assume unacceptable costs. All of this makes the master development studies of these networks very challenging, as the resource limited devices cannot support the execution of any complicated algorithms. Moreover, WSNs use a radio band that is license-free, so anybody with appropriate equipment can listen to the communication.
Finally, due to their deployment in areas that are difficult to reach makes them prone to node failures and adversaries. On the other hand, profound analysis of the state of the art has allowed us to identify the main issues of the existing writing psychology, which are their limited scope of detection, as the majority of them can detect only previously seen attacks, and the fact that any adjustment has to done by humans, which cannot be done in a timely fashion due to the deployment of the nodes in hard phd thesis on wireless sensor network security notes reach areas.
In order to overcome these issues, we have proposed an approach based on anomaly detection that is able to detect a wide range of attacks, including the previously unseen ones, without the necessity to have any previous knowledge on phd thesis on wireless sensor network security notes attacks and their way of operating.
Attacks are treated as phd thesis on wireless sensor network security notes outliers, and since outliers are defined phd thesis on wireless sensor network security notes something different from the normal, we can classify our approach as an anomaly detection one.
Thus, the basic premise of this approach is that the attacks are deviations from normality. However, not all deviations from normality are attacks, but we believe that they have to be reported and examined further. For this reason, in this work we only provide a first reaction to anomalies, which is their isolation, but it is assumed that the base station has additional technique to decide whether an anomaly can be attributed to an attack, or not.
However, this is phd thesis on wireless sensor network security notes of the scope of this work.
The existing anomaly detection solutions mainly look for the deviations in the values of phd thesis on wireless sensor network security notes parameters that capture the properties of known attacks, security notes means that they use so-called numerical features. Hence, their possibilities to detect wireless sensor attacks are limited, since it is hard to define the numerical features of the unknown attacks.
In order to overcome this issue, we have proposed a machine learning solution for anomaly phd thesis along with the feature extraction process that does not capture the properties of the attacks, but rather relies on the existing network security and spatial redundancy in sensor network security and tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station.
In this work we further propose a special way to integrate mobile nodes into this approach, given that mobility is a big issue in anomaly detection, as it can lead to observation data that have long range dependency and in this way increase its difficulty.
Detecting Unknown Attacks in Wireless Sensor Networks That Contain Mobile Nodes
Moreover, it is greatly unexplored and untreated subject in the current state of the wireless sensor. The data produced in the presence of an attacker are treated as outliers, and they are detected using clustering techniques. The techniques are further coupled with phd thesis on wireless sensor network security notes reputation can somebody do my homework i can't, which provides implicit response to the attackers, as the compromised nodes get isolated from the network.
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