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Development of a Modified Bacterial Foraging Optimization Algorithm Based Black Hole Attack Mitigation Model for Wireless Sensor Networks

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Development of a Modified Bacterial Foraging Optimization Algorithm Based Black Hole Attack Mitigation Model for Wireless Sensor Networks.

ABSTRACT

This study is aimed at the development of a mechanism for black hole attack mitigation in Wireless Sensor Network (WSN) using a modified Bacterial Foraging Optimization Algorithm (BFOA). A total of 200 randomly generated bacterial sensor nodes with a communication range of 20m were deployed in a 100mx100m network coverage area, consisting of four base stations. The radii 20m, 30m and 40m were chosen for the black hole region.

The algorithm was implemented in MATLAB R2015b. In all tests carried out, the results obtained at 40m radius showed the effect of the black hole attack better than those at 20m and 30m. Successful packet delivery probabilities of 83.52%, 95.78%, 97.26% and 99.78% respectively were achieved at 40m radius for one, two, three and four base stations respectively. Significant reduction in false positive was observed when the base stations were increased.

A negligible value of about 0.003% false positive was observed with four base stations using 40m radius of black hole region. Average delivery times of 31sec, 37sec, 43sec and 49sec were achieved at 40m radius for one, two, three and four base stations respectively. The times indicated that the routing complexity increased as the number of base stations increased.

The performance of the modified BFOA based method showed packet delivery probability improvement of 5.48%, 9.67%, 0.18% and 1.01% over the standard BFOA based method as the base stations were increased from one to four respectively. As the base stations were increased to five, six, seven and eight, successful packet delivery probabilities of 99.39%, 99.69%, 99.79% and 99.82% respectively were achieved using 40m radius of black hole region.

TABLE OF CONTENT

CHAPTER ONE: INTRODUCTION

  • Background……………………………………………………………………….. 1
  • Statement of Problem……………………………………………………………………….. 4
  • Motivation……………………………………………………………………….. 5
  • Aim and Objectives……………………………………………………………………….. 5
  • Justification……………………………………………………………………….. 6
  • Methodology……………………………………………………………………….. 6
  • Dissertation Organization……………………………………………………………………….. 7

CHAPTER TWO: LITERATURE REVIEW

  • Introduction……………………………………………………………………….. 9
  • Review of Fundamental Concepts……………………………………………………………………….. 9
    • Wireless sensor networks……………………………………………………………………….. 9
    • Characteristics and constraints of wireless sensor network…………………………….. 10
    • Security goals……………………………………………………………………….. 11
    • Types of attack in wireless sensor networks………………………………………………………………………. 12
    • Bacterial foraging optimization algorithm……………………………………………………………………….. 14
    • Modified step size……………………………………………………………………….. 19
    • Objective function formulation……………………………………………………………………….. 20
    • Performance metrics……………………………………………………………………….. 21
  • Review of Similar Works……………………………………………………………………….. 24

CHAPTER THREE: MATERIALS AND METHODS

  • Introduction……………………………………………………………………….. 31
  • Initialization of BFOA and Network Parameters………………………………………………………. 31
  • Standard Bacterial Foraging Optimization Algorithm……………………………………………………………………….. 33
    • Chemotactic and swarming Step……………………………………………………………………….. 33
    • Reproduction step……………………………………………………………………….. 34
    • Elimination and dispersal step……………………………………………………………………….. 34
  • Development of the Modified Bacterial Foraging Algorithm………………………………………………………… 35
  • Optimized Positioning of Base Station and Detection of Black hole………………………………………….. 38
  • Performance Evaluation……………………………………………………………………….. 39
    • Packet delivery success and failure……………………………………………………………………….. 39
    • False positive……………………………………………………………………….. 40
    • Convergence speed……………………………………………………………………….. 40
  • Comparison of the Results obtained from the Modified BFOA with the Results of the Standard BFOA…….. 40
  • Extended Eight Base Stations……………………………………………………………………….. 40

CHAPTER FOUR: RESULTS AND DISCUSSION

  • Introduction……………………………………………………………………….. 41
  • Packet Delivery Success Results of Modified BFOA……………………………………………. 41
  • Packet Delivery Failure Results of Modified BFOA…………………………………………………. 43
  • False Positive Results of Modified BFOA………………………………………………………………… 44
  • Convergence Speed Results of Modified BFOA……………………………………………………………………….. 46
  • Comparison between the Results of the Modified BFOA and the Standard BFOA……………………….. 47
  • Result of Extended Eight Base Stations……………………………………………………………………….. 53

CHAPTER FIVE: CONCLUSION AND RECOMMENDATION

  • Conclusion……………………………………………………………………….. 57
  • Limitations……………………………………………………………………….. 58
  • Significant Contributions……………………………………………………………………….. 58
  • Recommendations for Further Works……………………………………………………………………….. 59

REFERENCES……………………………………………………………………….. 60

INTRODUCTION

According to Annu and Chaudhary (2015), “Wireless Sensor Network (WSN) is an interconnection of a large number of nodes deployed for monitoring a system by means of measurement of its parameters”. Due to its wide range of applications in both the military and civilian domain, it is emerging as a prevailing technology for the future. It is used in industrial process control and monitoring, healthcare monitoring, environment and habitat monitoring, disaster management, structural monitoring and lots more (Arya & Raina, 2014).

Wireless Sensor Networks are prone to security attacks due to severe constraints such as broadcast nature of transmission medium, limited battery power, small memory and susceptibility to physical capture because they are deployed in hostile and physically non-protected areas. As such, security is a major concern in WSN. There are many possible attacks on sensor networks such as Denial of Service (DoS) attack, selective forwarding, sybil attack, sink hole attack, black hole attack, hello flood attack and wormhole attack (Sharma & Thakur, 2014; Sharma & Ghose, 2010).

One of the most severe attacks is the black hole attack, which drops the entire packet. It is a type of routing attack whereby an intruder captures and reprograms a set of sensor nodes in a network so that they do not transmit the generated or received data packets to their original destinations. Black hole attack prevention techniques proposed in literature either use neighbourhood interactions and message overhearing (Karakehayov, 2005; Roy et al., 2008), or secret sharing and path diversity (Ketel et al., 2005; Lou & Kwon, 2006).

REFERENCES

Annu, S., & Chaudhary, J. (2015). A review of BFOA applications to WSN. International Journal of Advanced Foundation and Research in Computer (IJAFRC), 2(5), 1-15.

Arya, M., & Raina, E. J. P. S. (2014). BFO based optimized positioning for black hole attack mitigation in WSN. International Journal of Engineering Trends and Technology (IJETT), 14(1), 29-34.

Atakli, I. M., Hu, H., Chen, Y., Ku, W. S., & Su, Z. (2008). Malicious node detection in wireless sensor networks using weighted trust evaluation.Symposium on Simulation of Systems Security (SSSS ’08), 836-843.

Bermejo, E., Cordón, O., Damas, S., & Santamaría, J. (2013). Quality time-of-flight range imaging for feature-based registration using bacterial foraging. Journal of Applied Soft Computing (ASOC), 13(6), 3178-3189.

Das, S., Biswas, A., Dasgupta, S., & Abraham, A. (2009). Bacterial foraging optimization algorithm: theoretical foundations, analysis, and applications. In book: Foundations of Computational Intelligence, Springer, 3, 23- 55.

Dasgupta, S., Das, S., Abraham, A., & Biswas, A. (2009). Adaptive computational chemotaxis in bacterial foraging optimization: an analysis. IEEE Transactions on Evolutionary Computation,, 13(4), 919-941.

CSN Team.

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