Novel Design Based Internet of Things to Counter Lone Wolf Part B: Berlin Attack

AUTHOR(S):

Hassan F. Morsi, M. I. Youssef, G. F. Sultan

TITLE

Novel Design Based Internet of Things to Counter Lone Wolf Part B: Berlin Attack

ABSTRACT

This paper proposes a new design methodology for Intelligent Transportation Systems, which uses existing smart techniques in transportation systems and human behavior detections to counter lone wolf threats and driver violations. The design can be attached to vehicles as an intelligent embedded system. In this design, the electroencephalogram analysis techniques are used to detect the irregularity in driver behavior which can be categorized into threatened or violated behavior. In threaten behavior like deliberate run-over accidents, the system will stop the vehicle as soon as possible and inform the security agency to ensure a speed response. In violated behavior like driver drowsiness, the system will alert the driver or inform the responding authorities and stop the vehicle, depending on the level of danger. To minimize the consequences of the vehicle fast stopping, it proposed to green the next traffic light signs. By applying this system in vehicles a lot of accidents can be avoided, in particular those caused by lonely wolves like deliberate run-over accidents or stolen of vehicles.

KEYWORDS

Intelligent Transportation Systems, Internet of Things, Deliberate Run-Over Accidents, Berlin Attack, Lone Wolves Threats.

REFERENCES

[1] J. Besenyo, “Low-cost attacks, unnoticeable plots? – overview on the economical character of current terrorism,” Strategic Impact, vol. 1/62, pp. 83-100, 2017.

[2] L. Kaati, A. Shrestha, and T. Sardella, “Identifying warning behaviors of violent lone offenders in written communication,” Proceedings of the 2nd International Workshop on Data Science for Social Media and Risk, Barcelona, Spain, December 2016.

[3] T. Houston, “Mass surveillance and terrorism: does PRISM keep americans safer?,” Thesis Projects, University of Tennessee Honors, 2017.

[4] Hassan F. Morsi, M. I. Youssef, and G. F. Sultan, “Novel design based internet of things to counter lone wolf, part a: Nice attack,” Proceedings of the 3rd International Conference on Advanced Intelligent Systems and Informatics, September 2017, Cairo: Advances in Intelligent Systems and Computing, Springer, in press.

[5] Wikipedia: https://en.wikipedia.org/wiki/2016 Berlin attack, Accessed 5 June 2017.

[6] W. Eichendorf, “Advanced emergency braking systems for commercial vehicles,” German Road Safety Council, 2016.

[7] IHLS news, “Police seeks mass vehicle attack solution,” 7 Jan 2017. Available at, http://ihls. com/he/archives/73974

[8] S. Talari, M. Shafie-khah, P. Siano, V. Loia, A. Tommasetti, and J.P. Catalão, “A review of smart cities based on the internet of things concept,” Energies, vol. 10, No. 421, 2017. doi:10.3390/en10040421

[9] S. Gill, P. Sahni, P. Chawla, and S. Kaur, “Intelligent transportation architecture for enhanced security and integrity in vehicles integrated internet of things,” Indian Journal of Science and Technology, vol. 10, no. 10, March 2017, doi: 10.17485/ijst/2017/v10i10/108251

[10] O. Popescu, S. Sha-Mohammad, H. Abdel- Wahab, D.C. Popescu, and S. El-Tawab, “Automatic incident detection in intelligent transportation systems using aggregation of traffic parameters collected through V2I communications,” IEEE Intelligent Transportation Systems Magazine, vol. 9, no. 2, pp. 64-75, 2017. doi: 10.1109/MITS.2017.2666578

[11] U.S. Department of Transportation, “History of intelligent transportation systems,” 2016.

[12] I. Damousis, I. Cester, S. Nikolaou, and D. Tzovaras, “Physiological indicators based sleep onset prediction for the avoidance of driving accidents,” Conf Proc IEEE Eng Med Biol Soc, 2007.

[13] I. Cester, S. Dunne, A. Riera, and G. Ruffini, “ENOBIO: wearable, wireless, 4- channel electrophysiology recording system optimized for dry electrodes,” Phealth, International Workshop on Wearable Micro and Nanosystems for Personalized Health, Barcelona, Spain, 2008.

[14] S.D. Ridwan, R. Thompson, B.T. Jap, S. Lal, and P. Fischer, “Single channel wireless EEG: proposed application in train drivers,” African Journal of Information and Communication Technology, vol. 5, no. 2, pp. 54-63, June 2009.

[15] A. Riera, A. Soria-Frisch, M. Caparrini, C. Grau, and G. Ruffini, “Unobtrusive biometric system based on electroencephalogram analysis,” EURASIP Journal on Advances in Signal Processing, vol. 2008, Article 143728, Hindawi. doi:10.1155/2008/143728

[16] M. Zhendong, H. Jianfeng, and M. Jianliang, “EEG -based person authentication using a fuzzy entropy-related approach with two electrodes,” Entropy, vol.18, no. 432, 2016. doi:10.3390/e18120432.

[17] P. Mishra, “Development of biometric verification algorithm using EEG,” PH.D thesis, Thapar University, Patiala, India, 2016.

[18] G.K. Gopika, S. Neelam, and B.J. Dinesh, “EEG signal classification in non-linear framework with filtered,” 23rd European Signal Processing Conference (EUSIPCO), IEEE, 2015.

[19] C.F. Lin, S.W. Yeh, Y.Y. Chien, T. I. Peng, J.H. Wang, and S.H. Chang, “A HHT-based time frequency analysis scheme in clinical alcoholic EEG signals,” WSEAS Transactions on Biology and Biomedicine, vol. 5, no. 10, October 2008.

[20] S. Wang, Y. Li, P. Wen, and G. Zhu, “Analyzing EEG signals using graph entropy based principle component analysis and J48 decision tree,” Int. J. Sig. Process. Syst., vol. 4, no. 1, 2016. doi: 10.12720/ijsPS .4.1.67-72.

[21] B. Ghazal, K. ElKhatib, K. Chahine, and M. Kherfan, “Smart traffic light control system,” 3rd International Conference on Electrical, Electronics, Computer Engineering and their Applications (EECEA), IEEE, 2016. doi: 10.1109/EECEA.2016.7470780

[22] K. Nellore, and G.P Hancke, “Traffic management for emergency vehicle priority based on visual sensing,” Sensors, vol.16, no.1892, 2016. doi:10.3390/s16111892

[23] Y.Y. Liu, K.E. Sanders, and J.M. Shuler, “Advances in tracking and monitoring transport and storage of nuclear material,” IAEA-CN- 244-186, 2016.

[24] H. Tsai, B. Craig, H. Lee, K. Mittal, Y. Liu, and J. Shuler, “ARG-US remote area modular monitoring for dry casks and critical facilities,” INMM 55th Annual Meeting, Atlanta, Georgia, USA, July 2014.

Cite this paper

Hassan F. Morsi, M. I. Youssef, G. F. Sultan. (2017) Novel Design Based Internet of Things to Counter Lone Wolf Part B: Berlin Attack. International Journal of Mathematical and Computational Methods, 2, 235-242