ADHOC NETWORKS EYE – SECURE

        ADHOC NETWORKS

EYE – SECURE

B.OBULIRAJ

ABSTRACT:

In this paper I have identified the challenges faced by most of the people in sending data secretly and securely through airborne network, which has now become a basic requirement. We are here going to generate a password which is unbreakable for the application through which the information is being transferred from ground station to the one who is controlling the entire activities of aircraft and vice versa. Airborne Internet has the potential to change the way aircraft receive and send data, or more appropriately, information. Airborne Internet consortium will provide an interconnected digital data network aircraft and from the ground. Airborne Internet has the potential to change how aircraft are monitored and tracked by the air traffic control system, how they exchange information with and about other aircraft. In this paper I going to discuss how to generate a living password which need not be remembered by any one for which an iris code is generated from a given iris image and be utilized by the system to improve the security of the data and help in maintaining information being passed from ground station or from other aircraft to reach properly at its destination. Here in this paper I have discussed the strength of generating password through Iris and other passwords through other techniques. Also I have identified the unique patterns of the iris and the method of generating a 512 byte code is explained to improve the systems security. Here the identification of errors has been drastically reduced and the probability value for detection is 1/2 (512*8) .On seeing the probability value I could find that it’s very difficult to hack the password being generated.

Introduction to Airborne n/w & Iris Recognition:

The Objective of airborne network is the use of heterogeneous set of physical links (RF, Optical/Laser and SATCOM) to interconnect terrestrial, space and highly mobile airborne platforms themselves, which will self form into a network with a dynamic topology – i.e., a mobile ad hoc network. The iris is a protected internal organ whose random texture is stable throughout like, it can serve as a kind of living passport or a living password that one need not remember but can always present. The randomness of iris patterns has very high dimensionality; recognition decisions are made with confidence levels high enough to support rapid and reliable exhaustive searches through national-sized databases. Here using this security measure we can make aircrafts to receive correct information. Its purpose is real-time, high confidence recognition of a person’s identity by mathematical of a random patterns that are visible with in the iris of an eye from some distance.

Iris texture is stable over decades and even the eyes of the same person or even for monocular twins are greatly different. So this could provide a way for transmitting the signals from the base station and the air crafts with more security.

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What airborne network is?

As a war-fighting asset, the objective of airborne network is to provide commanders the capability to ascertain the network’s operational health and status – i.e., network situational awareness. Additionally, airborne network communications resources should be configurable to meet the commanders’ operational objectives. These operational requirements are typically satisfied in terrestrial, wire-line networks by network management and policy based network management capabilities. However, management of mobile ad hoc networks is an emerging research area facing many challenges. This paper deals with the framework for critical research and technological need for military communications very secretly for airborne networks. Here we have to use dynamic wireless protocols with high security to pass the information through airborne network. Protocols which could be used here are AODV on table driven protols.

Need for Security

As Network has now become a part of our life. We send a huge amount of data over the available networks. But we find Hackers all through these areas trying to hack the informations that are to be sent very secretly or securely. For which in Olden days we used various encryption algorithms to save our data from hackers. But those algorithms were also easily be broken by these hackers. So we need to have a secured network which provides a path for sending the data secretly.

Strong encryption makes data private, but not necessarily secure. To be secure, the recipient of the data must be positively identified as being the approved party. This is usually accomplished online using digital signatures or certificates. So here we are going to design a pure network with complete security.

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Phase I

Iris Recognition

Compared with biometric techniques such as fingerprints and face recognition, iris recognition has great advantage in uniqueness in stableness. A classic iris recognition algorithm includes the following stages,

v  Image processing

v  Feature extraction

v   extraction

v  Pattern matching

v  Classifierdesign

The patterns of human iris differ from person to person, even between monocular twins. Because iris reacts with such a sensitive to light, causing the size and shape to change continuously, counterfeiting based on iris patterns is extremely difficult. Iris detection needs to follow some of the steps as follows,

v  Iris radius approximation

v  Iris translation

v  Iris information extraction

v  Gabor filtering

v  Generating an iris code

v  Comparing iris code

v  Error approximation

The original image after running through a median filter works by assigning to a pixel the median value of its neighbors. Then the image is prepped the edge detection can be done. Since there is such a noticeable rising edge in luminescence at the edge of the iris, filtering with a haar wavelet should act as a simple edge detector. The area of interest is not just the single horizontal line through the iris, but the portion of that line to the left of the pupil. This is so that the rising luminescence from the transition from iris to white is the only major step.

Having decided on where to attempt to detect the iris edge, the question of how to do it arises. It seems obvious that some type of edge detection should be used. It happens that for any edge detection it is good idea to blur the image to subtract any noise prior to running the algorithm, but too much blurring can dilate the boundaries of an edge, or make it very difficult to detect. Consequently, a special smoothing filter such as the median filter should be used on the original image.

CORE PART OF IRIS RECOGNITION

Iris Detection

This is the process for detecting center and radius of an iris given the pupil center and radius. Not at all time pupil and iris are not concentric. So the pupil information does not help directly to determine the parameters of the iris. Having the starting point of the pupil, we guess the potential iris centers and radii. They then integrate over the circumference in order to determine if it is on the border of the iris..

 

Iris Radius Approximation

The first step in finding the actual iris radius is to find an approximation of the iris radius. This approximation can then be fine tuned to find the actual iris parameters. In order to find this approximation a single edge of the iris must be found. Knowing that eyes are most likely to be distorted in the top and bottom parts due to eyelashes and eyelids, the best choice for finding an unobstructed edge is along the horizontal line through the pupil center.

Having decided on where to attempt to detect the iris edge, the question of how to do it arises. It seems obvious that some type of edge detection should be used. It happens that for any edge detection it is good idea to blur the image to subtract any noise prior to running the algorithm, but too much blurring can dilate the boundaries of an edge, or make it very difficult to detect. Consequently, a special smoothing filter such as the median filter should be used on the original image. This type of eliminates sparse noise while preserving image boundaries. The image may need to have its contrast increased after the median filter.

The original image after running through a median filter works by assigning to a pixel the median value of its neighbors. Then the image is prepped the edge detection can be done. Since there is such a noticeable rising edge in luminescence at the edge of the iris, filtering with a haar wavelet should act as a simple edge detector. The area of interest is not just the single horizontal line through the iris, but the portion of that line to the left of the pupil. This is so that the rising luminescence from the transition from iris to white is the only major step.

                                                                                   Iris Patterns

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The iris should represent the steepest luminance change in the area of interest. Consequently, this area of the image should correspond to the highest valued component of the output from the filter. By finding this maximal value the edge of the iris to the right of the pupil should be found. It should be noted that since the iris may not be concentric with the pupil the distance from the center to this edge may not correspond to the iris’ radius.

Iris Translation

Having acquired an approximate radius, a small pad of this value should produce a circle centered on the pupil which contains the entire iris. Furthermore, with the perimeter of the pupil known, an annuals may be formed which should have the majority of its area filled by the iris. This annual can then be unrolled into Cartesian coordinates through a straight discretized transformation.

If the iris is perfectly centered on the pupil, the unrolled image should have a perfectly straight line along its top. However, if the iris is off centered even a little this line is wavy. The line represents the overall distance the iris is at from the pupil center. It is this line which will help to determine the iris’ center and radius. Consequently, an edge detection algorithm must be run on the strip in order to lines’ exact location. Once again canny edge detection is used. However, before the edge detection can run the image should undergo some simple pre-processing to increase the contrast of the line. This will allow for a higher thresholding on the edge detection to eliminate extraneous data.

Iris Information Extraction

In order to extrapolate the iris’ center and the radius, two chords of the actual iris through the pupil must be found. This can be easily accomplished with the information gained in the previous step. Thus easily the information could be retrieved and used for further proceedings.

Generating an Iris code

We only want to store a small number of bits for each iris code, so the real and imaginary parts are each quantized. If a given value in the resultant vector is greater than zero, a one stored; otherwise zero is stored.

Phase II

Password for application

Now the obtained code is going to be used as password for the application from which the signals are to be transmitted to the pilot under emergency cases. Thus these applications could not be accede by unauthorized persons and thus high security in transmitting the information could be obtained. We can also provide master and slave codes and this could be used if the master is not available at the time of emergency. For the security in transmitting channel we have got lot of dynamic on table wireless protocols with high security. So thus in this paper we mainly concentrate on the password for the application. Thus this paper would give a high security for applications used in airborne networks for the transferring information…

Comparing Iris codes

The Hamming distance between any two equal length binary vectors is simply the number of bit positions in which they differ divided by the length of the vectors. This way, two identical vectors have distance 0 while two completely different vectors have distance 1.

D= (A xor B)/length (A)

Error Approximation

In theory, two iris codes independently generated from the same iris will be exactly the same. In reality though, this doesn’t happen vary often for reasons such as imperfect cameras, lighting or small rotational errors. To account for these slight inconsistencies, two iris codes are compared and if the distance between them is below a certain threshold we’ll call them a match. This is based on the idea of the statistical independence.

Survey

The largest single current deployment of this algorithm is in the United Arab Emirates, where every day about 2 billion iris comparisons is performed.

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Iris Code

This iris code generated from iris serves as the password for our system. This password provides a very high security for the system and it seems to be highly unbreakable…

Other Applications

v  Aviation security, and controlling access to restricted areas at airports

v  Substituting for passports(automated international border crossing)

v  Information security

v  Entitlements authorization

v  Forensic and Military applications

v  Network access

Conclusion

Thus in this paper I have clearly stated the importance of the password being generated from iris and their usage in transmitting signals secretly in airborne networks…