Biometric Systems, Privacy Enhancing Techniques And Wireless Sensor Networks

Biometric Systems

1.Biometric system can be defined as a technological system that makes use of certain information about a person in order to identify the person. Biometric system therefore mainly relies on specific data mostly associated with the unique biological traits of a person. The most commonly used biometrics include Fingerprint, hand geometry and iris recognition along with face recognition, DNA matching and so on (Hasan & Abdul-Kareem, 2013). A typical biometric system involves the running of data through different algorithms to identify an individual. Biometric systems are mainly used s an access control system which allows only an authorized individual to access a particular space or device. The three different types of biometric systems are discussed in the following sections.

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Biometric is mainly defined as an automated method of verifying the authenticity of an individual with the help of their unique physiological characteristics and behaviors. It is therefore considered to be a very strong authentication mechanism (Kaur & Juneja, 2014).  One of the most commonly used biometric techniques is fingerprint recognition.

Fingerprint recognition is a biometric technique that looks for different unique patterns present in the fingerprint of an individual. Since these patterns are unique for every individual, it forms a basic aspect of identifying and individual from the entire population. Fingerprint is a characteristic of an individual that can neither be stolen nor lost and thus it is one highly accurate and reliable biometrics. The two techniques that are used for fingerprint are histogram equalization and Image Binarization. The technologies used for fingerprint are optical and ultrasonic technology.


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The main advantages of fingerprint biometric are as follows-

  1. This technique is highly reliable due to its accuracy.  
  2. Fingerprint is unique for every individual and therefore it cannot be replicated.
  3. Requires a very small storage space and is easy to use
  4. It is one of the most economical techniques.


The significant disadvantages of fingerprint are as follows-  

  1. In most of the cases, a fingerprint scanner does not take into consideration when a person physically changes.
  2. Fingerprint scanners are often affected by the dirt which in turn might lead to false rejection.

Hand Geometry

Han geometry is a type of biometrics that recognizes the shape of an individual’s hand. It is simple and easy to use biometric option as the data of hand geometry is easier to collect. Hand Geometry biometric devices make  use of basic concept of recording the length, along with the thickness and the total surface area of hand to authenticate his/her identity (Ren et al., 2013). The technologies used for hand geometry are palm technology and hand geometry technology. The techniques used for hand geometry include measuring the shape and size of hand and measuring the unique features of the hand. The advantages and the disadvantages of hand geometry are discussed in the following sections.


The advantages of hand geometry are as follows-

  1. It is one simple and inexpensive biometric option.
  2. Data related to hand geometry is easier to collect.
  3. It is less intrusive than fingerprint.

Fingerprint Recognition


The disadvantages of hand geometry are as follows-

  1. It is not ideal for growing children
  2. Data size is large and therefore requires huge storage space.
  3. It is not unique and therefore less secure. Furthermore, it can be replicated quite easily.

Iris Recognition 

It can be defined as an automated process of identification of biometrics that make use of mathematical pattern-recognition technique based on the data collected from the ring shaped region surrounding the pupil of the eye which is known as iris (Bowyer & Burge, 2016). This biometric technique is based on high resolution and distortion free image of the iris of human eye. The techniques used for iris recognition are segmentation and normalization. The technologies behind iris recognition are Iris scanning and retinal scanning. The advantages along with the disadvantages of iris recognition are discussed in the sections following.


The advantages of iris recognition are as follows (Bhatia, 2013)-

  1. It is one of the most accurate biometric technologies.
  2. It is highly scalable and can be used for both small and large scale programs.
  3. It is easy to use.


The disadvantages of iris recognition are as follows-

  1. It is one of the most expensive biometric systems.
  2. It does not work if the distance between iris and scanner is large.
  3. Constant use of this biometric system may harm the eyes due to continuous exposure to infrared light.

2.Privacy enhancing techniques refers to certain specific methods that act in accordance to the laws of data protection. It measures the information protection by minimizing or eliminating the need for processing of unnecessary data (Rhodes-Ousley, 2013). The objective of privacy enhancing technique is to protect and ensure the privacy of the users. The privacy enhancing technique enforces legal privacy principles for ensuring protection of privacy of the users of information technology.

The three different forms of privacy enhancing techniques are encryption, Data minimization and Control. The detailed illustration of these privacy enhancing techniques are discussed in the following sections.


Encryption is one of most widely used PET across internet. Encryption provides security as well as the proportionality principles associated with the data protection laws. In the recent years, there have been a considerable advancements and an increasing trend in protection of data through the process of encryption. Encryption enables only the authorized individuals in accessing the data. Encryption is relatively simple in its implementation approach and makes use of public and private keys in encryption and decryption of the data. Encryption enables only the person having access to private key in decryption of the data and in this way encryption prevents any sorts of unauthorized use and access to the data over internet. Examples of encryption include digital signature and data end to end encrypted messages.

Data minimization 

It is one of the mostly used privacy enhancing techniques that enables the different services and the applications over internet to make use of a minimum amount of information that is necessary for a particular transaction. The objective of this data minimization technique is to minimize the use of personal data as much as possible in a particular transaction. This Privacy Enhancing technique helps in protection of the privacy of the individuals while they are browsing over the internet. Private browsing is an example of this type of PET.  Example of data minimization is making use of private browser and proxy.

Iris Recognition


Control is another privacy enhancing technique that allows the users in exercising more control on the data that is being shared over internet. This technique enables the users to have a control on the information that is sent to or used by the online service providers. Control ensures only the necessary information is shared over internet during an online transaction. This in turn helps in protecting the privacy of the users making use of internet. The examples of control include end users licensing and data privacy policies.

3.Wireless sensor network is a network of nodes that consist of spatially distributed devices which use sensors to monitor the surrounding environment. Wireless sensor technology has a number of advantages due to its flexible software architecture (Yang, 2014). The architecture of WSN consists of application layer, network layer, transport layer, physical layer and data link layer. The picture below represents the diagrammatic representation of WSN.

Figure 1: Representing WSN Architecture

(Source:  Yang, 2014)

The application layer of the WSN is in charge of management of the traffic while the transport layer is in charge of delivering the congestion avoidance and reliability in the architecture. Transport layer offers a reliable loss recovery mechanism and can be segregated into packet driven and event driven. Network layer of the WSN architecture is in charge of the routing and performs different tasks based on application. Data link layer is used for multiplexing data frame detection and error control (El Emary & Ramakrishnan, 2013). The physical layer on the other hand provides an edge for transferring a stream of bits and is in charge for selection of frequency, data encryption and signal detection.

Threats and Vulnerabilities 

There are a number of advantages of making use of wireless sensor networks. In WSNs network arrangements can be easily carried out without the need of any immovable infrastructure. The set up and execution pricing associated with WSNs are inexpensive and is quite flexible as well. This is one of the significant reasons behind the increase in the use of WSNs across different applications. It is used in smart devices and buildings, transportation and industrial applications as well. However, there are a number of risks and threats associated with the use of WSN which are needed to be addressed. The risks and threats associated with the use of WSNs are discussed below (Park et al., 2013).

  1. Denial of Service Attack- This attack is a security issues associated with the use of wireless sensor network. It is formed by unintentional failure of the nodes and certain malicious actions (Zhang et al., 2016). The aim behind DOS attacks is to exhaust the resources of the victim node by sending unwanted packets and requests. The different types of denial of service attacks include jamming, tampering, collisions, exhaustions and so on.
  2. The Sybil Attack: In WSN, the sensors often needs to work together in order to achieve a task and in such cases, one node might duplicate in multiple locations (Jan et al., 2015). The Sybil attack harms the integrity of data security along with the utilization of the resources thereby preventing the actual functionalities of the nodes.
  3. Black hole Attack: In this type of attack, a malicious node attacks the entire traffic and drops the packets coming from specific sources thus tampering with the normal operation of WSN. Once a malicious device comes in between the communicating nodes, it infuses the black hole attack.


The above discussed threats are needed to be mitigated in order to ensure normal operation of the wireless sensor networks. The issue of DOS can be prevented by limiting the number of request in a limited time interval (Zhang et al., 2016). For prevention of Sybil and black hole attack encryption and cryptography should be used.


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Bhatia, R. (2013). Biometrics and face recognition techniques. International Journal of Advanced Research in Computer Science and Software Engineering, 3(5).

Bowyer, K. W., & Burge, M. J. (Eds.). (2016). Handbook of iris recognition. Springer London.

El Emary, I. M., & Ramakrishnan, S. (2013). Wireless Sensor Networks. CRC Press.

Hasan, H., & Abdul-Kareem, S. (2013). Fingerprint image enhancement and recognition algorithms: a survey. Neural Computing and Applications, 23(6), 1605-1610.

Jan, M. A., Nanda, P., He, X., & Liu, R. P. (2015, August). A sybil attack detection scheme for a centralized clustering-based hierarchical network. In Trustcom/BigDataSE/ISPA, 2015 IEEE (Vol. 1, pp. 318-325). IEEE.

Kaur, N., & Juneja, M. (2014, March). A review on iris recognition. In Engineering and Computational Sciences (RAECS), 2014 Recent Advances in (pp. 1-5). IEEE.

Park, S., Aslam, B., Turgut, D., & Zou, C. C. (2013). Defense against Sybil attack in the initial deployment stage of vehicular ad hoc network based on roadside unit support. Security and Communication Networks, 6(4), 523-538.

Ren, Z., Yuan, J., Meng, J., & Zhang, Z. (2013). Robust part-based hand gesture recognition using kinect sensor. IEEE transactions on multimedia, 15(5), 1110-1120.

Rhodes-Ousley, M. (2013). Information security: the complete reference. McGraw Hill Education.

Yang, K. (2014). Wireless sensor networks. Principles, Design and Applications.

Zhang, H., Cheng, P., Shi, L., & Chen, J. (2016). Optimal DoS attack scheduling in wireless networked control system. IEEE Trans. Contr. Sys. Techn., 24(3), 843-852