Biometric System
Biometric system is a scheme that uses and gives data about a person; it is used to show the identity of people. Biometric system depends on exact data about distinctive biological traits for it to function effectively (Jain, 2004). The components of biometric systems are:
Fingerprint this involves the use of fingerprints to identify, this is done by the use of hardware scanner and a software that records unique fingerprints features, saves data in a template and recall the model when the same fingerprints are used to allow access of data (Gupta, 2018).
Techniques and technologies used for fingerprint (Dror, 2010).
- AFIT- it refers to advance fingerprint technology which boosts fingerprint and show print service processing. AFIT improves the precision of fingerprint matching to almost 100%
- Metal objects prints – scientist have developed a technique that allows fingerprints on metal objects from a few shell casing to larger once. They prove that chemical forms that give fingerprints unique characteristics have electrical slighting characteristics which can resist electric current despite the thinness of the material. The use of this method enables fingerings
- Color-changing fluorescent film- this came from the advancement of metal object prints, the plan was improved by adding fluorophore particles to a film which is sensitive to ultra-violet rays and light. Primarily this an extra tool for developing conflicting colors of fingerprints
- .MXRF- stands for Micro-x-ray florescence-. MXRF was developed to detect minerals such as potassium, sodium and chloride elements that are contained in salt and other. This makes it possible to view fingerprints where the spices settle.
- Non-invasive procedure- compared to traditional methods this method has many advantages because much more accessible to detect prints that are contained in different substances such as human skin, plastic, fibrous papers and multi-coloured backgrounds.
- Advances in forensic science- many advances have been realized in forensic evidence field, science has continued to make process in fingerprinting advancement. The area has helped in identifying evidence of criminals who are in court.
- Acceptance- it is generally accepted method of identifying people because most people are familiar with the use of fingerprints for identification.
- Accuracy- with the use of fingerprints, there is minimal chances of rejection because the method is accurate.
- Easy to use- it needs very little time and knowledge to use, this is made possible by the availability of fingerprint scanning system.
- Installation- most. Fingerprint scanners are portable, and the technologies available have to make it easy to install (Lin, 2018).
- Security- fingers prints cannot be lost or stolen by fraudsters because of its difficulty to produce unique identifiers.
- Injury- injury can interfere with the scanning process of fingerprinting biometric system because it is difficult for people who are injured cannot access the system.
- Acceptance – with the use of fingerprints acceptance is always guaranteed this because some people take it as an invasion of privacy.
- Fraud- hackers may find the target’s fingerprints from objects like utensils and tries to use them to access the required resource.
1.131. Example application of fingerprints
- It has been applied in providing biometric security for instance to secure sensitive areas of system
- In hospitals it is used to identify amnesia victims
It is a technique that is used to identify a person by measuring the hand geometry (Sanchez,et. al 2000).
Hand geometry uses hand recognition to identify people. It is based on the number of measures that are taken from the human hand; it measures the size of the palm, length and the width of fingers and the shape of the side. This system uses a device that captures the bottom and the top view of a user’s hand.
- It is simple, inexpensive and relatively easy to use
- The data used in hand geometry is secure to collect
- It is not affected by environmental factors like the dry weather which causes the dryness of the skin
- It is not unique and therefore cannot be used for identification systems
- It is not recommended for growing children
- Cannot be used in embedded systems because of large data size
Iris recognition is the use of an eye of a person to show identity
- Image capture- the image is captured by the camera by the use of visible radiation and infrared. The camera automatically locates the face and the iris in the middle.
- Location of iris and image enhancement- the image is examined, the purpose of this is to determined external boundary of the iris to determine the location of the iris.
- Accuracy – iris recognition is best regarding efficiency, it’s false acceptance, and false rejection is very low, this ensures high accuracy of results
- Distance- scanning can be done from an average distance like a photo.
- Scalability- the technology used is highly scalable, and it is applied in both large and small programs.
- Stability- it is stable because it is located inside a human body and protected by body mechanism (Al-Waisy,et al 2018)
- Expensive – scanners of iris recognition are costly it can only be afforded by large companies but not the general public.
- Distance- the small size of iris make it difficult to be located within a short distance.
- Movement- iris recognition device are affected by movements because it requires an object to be steady.
- Eyelids- sometimes iris recognition is prevented by eyelids which is hard to control since it frequently blinks.
- Airport technology- it is used to very international airports
- Time and attendance- it use used to reduce fraudulent employees, this is done by applying biometric time clock on their working department.
- Low enforcement- organizations like FBI use biometrics to investigate Criminals.
- Access control- many organization use biometric technology to for access control and single sign on secure socket layer
Introduction on PET used on the internet the increase of the application to everyday application is bringing threats to personal privacy. The Internet has seen tremendous advancement with the range of new users entering into the market. Therefore, there is a need to look at technologies that will help users to preserve their privacy (Bennett, 2017)
- The use of anonymity and pseudonymity systems- analysing systems to enable anonymity and pseudonymity of email. With the use pseudonymous systems, clients can participate in current email and be maintaining their privacy, for instance with the use of Type-III remailers have help to protect users in the email systems allow the clients to use mail without revealing the identity.
- Interactive anonymity and pseudonymity- communication today’s are real-time and increasingly interactive for example the use of instant messaging and emails. Guarding these types of communication and other internet applications are like the, and remote access causes more challenge than email. An example of this is anonymizer.com that anonymize proxy service.
- Communication privacy system- communicating over the internet has been guarded by various technologies private information from falling in the wrong hands. For instance, PGP (pretty good privacy) encrypt data and validate signatures on the other side.
It is a self-configuring link of small sensor nodes that converse among each other using radio signals, and arrayed in quantity to intellect, monitor and apprehend the physical world (Yang, 2014).
- The Sybil attack- it is a single node that is present in multiple identifiers to other nodes in a system. They give an important threat to physical routing protocol where it sufficiently routes the physical address packets.
- Jamming – it is a refusal of service attacks in which it attempts to disrupt how a network works by passing high energy signals.
- De-synchronization attacks- in this attack there is consistent message forging to either one or both the sender or the receiver, it needs missed frames transmission preventing the exchange of useful information ( Bonnin,et al 2014).
Wireless sensor network has developed and is used in many applications. Weaknesses can minimize by addressing the following (Pathan,2016).
- Data encryption – many wireless sensor networks are held in an open area location which may be dangerous and is susceptible to add messages. Wireless sensor network must come up with critical features that crucial cryptography and symmetric key encryption.
- Data partitioning — when data is split into several parts it gives the resolution to make sure the fraudsters cannot catch the information.
- Shared keys- the types of key management such as the crucial pairwise node, global key, essential pairwise group, and individual are the fundamental solution to block fraud in a wireless sensor network (Yang, 2014)
References
Al-Waisy, A. S., Qahwaji, R., Ipson, S., Al-Fahdawi, S., & Nagem, T. A. (2018). A multi-biometric iris recognition system based on a deep learning approach. Pattern Analysis and Applications, 21(3), 783-802
Bennett, C. J., & Raab, C. D. (2017). The governance of privacy: Policy instruments in global perspective. Routledge
Bowyer, K. W., & Burge, M. J. (Eds.). (2016). Handbook of iris recognition. Springer London
Dror, I. E., & Mnookin, J. L. (2010). The use of technology in human expert domains: challenges and risks arising from the use of automated fingerprint identification systems in forensic science. Law, Probability and Risk, 9(1)
Gupta, P., & Gupta, P. (2018). Multi-biometric Authentication System using Slap Fingerprints, Palm Dorsal Vein and Hand Geometry. IEEE Transactions on Industrial Electronics.
Jain, A. K., Ross, A., & Prabhakar, S. (2004). An introduction to biometric recognition. IEEE Transactions on circuits and systems for video technology, 14(1), 4-20.
Lin, C., & Kumar, A. (2018). Contactless and Partial 3D Fingerprint Recognition using Multi-view Deep Representation. Pattern Recognition
Pathan, A. S. K. (Ed.). (2016). Security of self-organizing networks: MANET, WSN, WMN, VANET. CRC press.
Rawat, P., Singh, K. D., Chaouchi, H., & Bonnin, J. M. (2014). Wireless sensor networks: a survey on recent developments and potential synergies. The Journal of supercomputing, 68(1), 1-48.
Rawat, P., Singh, K. D., Chaouchi, H., & Bonnin, J. M. (2014). Wireless sensor networks: a survey on recent developments and potential synergies. The Journal of supercomputing, 68(1), 1-48.
Sanchez-Reillo, R., Sanchez-Avila, C., & Gonzalez-Marcos, A. (2000). Biometric identification through hand geometry measurements. IEEE Transactions on Pattern Analysis & Machine Intelligence, (10), 1168-1171.
Yang, K. (2014). Wireless sensor networks. Principles, Design and Applications.
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