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Journal of Intelligent Systems and Internet of Things
Volume 5 , Issue 2, PP: 77-87 , 2021 | Cite this article as | XML | Html |PDF

Title

Comparison between Saudi Arabia and USA: Prevention and Dealing with Cyber Security

  Sonia Ibrahim 1 * ,   Nada Alkenani 2 ,   Banan Alghamdi 3 ,   Amal Alfgeeh 4 ,   Salwa alghamdl 5 ,   Yusra Alzhrani 6 ,   Amani Almuntashiri 7 ,   Rawan Alghamdi 8 ,   Abeer Salawi 9 ,   Wejdan Ahmed Alghamdi 10 ,   Mohammed. I. Alghamdi 11

1  College of Computer Science and Information Technology, Department of Engineering and Computer Sciences, Al-Baha University
    (soniabrahim301@gmail.com)

2  College of Computer Science and Information Technology, Department of Engineering and Computer Sciences, Al-Baha University
    (442020945@stu.bu.edu.sa)

3  College of Computer Science and Information Technology, Department of Engineering and Computer Sciences, Al-Baha University
    (banan.s1s1@gmail.com)

4  College of Computer Science and Information Technology, Department of Engineering and Computer Sciences, Al-Baha University
    (amalalfgih@hotmail.com)

5  College of Computer Science and Information Technology, Department of Engineering and Computer Sciences, Al-Baha University
    (442021118@stu.bu.edu.sa)

6  College of Computer Science and Information Technology, Department of Engineering and Computer Sciences, Al-Baha University
    (yosra977@hotmail.com)

7  College of Computer Science and Information Technology, Department of Engineering and Computer Sciences, Al-Baha University
    (amaniabdul39@gmail.com)

8  College of Computer Science and Information Technology, Department of Engineering and Computer Sciences, Al-Baha University
    (rawanawd08@gmail.com)

9  College of Computer Science and Information Technology, Department of Engineering and Computer Sciences, Al-Baha University
    (AbeerSalawi87@gmail)

10  College of Computer Science and Information Technology, Department of Engineering and Computer Sciences, Al-Baha University
    (443040568@stu.bu.edu.sa)

11  College of Computer Science and Information Technology, Department of Engineering and Computer Sciences, Al-Baha University
    (mialmushilah@bu.edu.sa)


Doi   :   https://doi.org/10.54216/JISIoT.050203

Received: September 17, 2021 Accepted: November 30

Abstract :

Cyber security practices mainly involve the prevention of external threats to software, hardware, server data, and other assets which are connected to the internet. Organizations follow a lot of cyber security practices to protect their systems and databases from malicious cyber actors. Cybercriminals use different techniques like spear-phishing, phishing, password attack, denial of service, ransomware, etc. to cause harm to people, organizations, and governments and steal important information from them. We analyzed the use of deep learning algorithms to deal with cyber-attacks. Deep neural networks or deep learning consist of machine learning procedures to support the network to fix complex issues and learn from unmanaged data. In addition, we also analyzed some of the cyber security laws and practices implemented in the US and Saudi Arabia to work collaboratively against cyber threats. It is observed that both countries are doing well against cyberthreats, but they need to work even more to provide training and support to professionals in the public sector who handle sensitive data about cyber security.

Keywords :

Saudi Arabia , US , Cyber Security , Cyberthreats.

References :

[1]       The White House (2018). National Cyber Strategy for the USA. Retrieved https://www.whitehouse.gov/wp-content/uploads/2018/09/National-Cyber-Strategy.pdf.

 

[2]       Craig, L. (2006). S.3421 – 109th Congress (2005-2006): Veterans Benefits, Health Care, and Information Technology Act of 2006. Retrieved from https://www.congress.gov/bill/109th-congress/senate-bill/3421.

 

[3]       Is the Computer Fraud and Abuse Act Ripe for Reform? - Charles Koch Institute. (2016). Retrieved 21 September 2021, from https://charleskochinstitute.org/stories/is-the-computer-fraud-and-abuse-act-ripe-for-reform/.

[4]       McCaul, M. (2018, November 16). H.R.3359 – 115th Congress (2017-2018): Cybersecurity and Infrastructure Security Agency Act of 2018. Retrieved from https://www.congress.gov/bill/115th-congress/house-bill/3359.

[5]       Mansoor, Z. (2020). Four of five organizations in UAE faced at least one 'cyber-attack' in 2019 - study. Retrieved 21 September 2021, from https://gulfbusiness.com/four-of-five-organisations-in-uae-faced-at-least-one-cyber-attack-in-2019-study/.

 

[6]       Sanderson, D. (2020). Coronavirus: Cybercriminals launch Covid-19 attack barrage. Retrieved from https://www.thenationalnews.com/uae/coronavirus-cyber-criminals-launch-covid-19-attack-barrage-1.1009181

[7]       Nuaimi, A. A. (2021). Effectiveness of Cyberbullying prevention strategies in the UAE. In ICT Analysis and Applications (pp. 731-739). Springer, Singapore.

[8]       Alzubaidi, A. (2021). Measuring the level of cyber-security awareness for cybercrime in Saudi Arabia. Heliyon, 7(1), e06016.

[9]       Alrubaiq, A., & Alharbi, T. (2021). Developing a Cybersecurity Framework for e-Government Project in the Kingdom of Saudi Arabia. Journal of Cybersecurity and Privacy, 1(2), 302-318.

[10]    Soni, V. D. (2020). Challenges and Solution for Artificial Intelligence in Cybersecurity of the USA. Available at SSRN 3624487.

[11]    Nadikattu, R. R. (2020). New Ways of Implementing Cyber Security to Help in Protecting America. Journal of Xidian University, 14(5), 6004-6015.

[12]    Dixit, P., & Silakari, S. (2021). Deep learning algorithms for cybersecurity applications: A technological and status review. Computer Science Review, 39, 100317.

[13]    Sihag, S., & Tajer, A. (2020). Secure estimation under causative attacks. IEEE Transactions on Information Theory, 66(8), 5145-5166.

[14]    Qian, Y., Ma, D., Wang, B., Pan, J., Wang, J., Gu, Z., ... & Lei, J. (2020). Spot evasion attacks: Adversarial examples for license plate recognition systems with convolutional neural networks. Computers & Security, 95, 101826.

[15]    Wu, G., & Sun, J. (2017). Optimal switching integrity attacks in cyber-physical systems. In 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC) (pp. 709-714). IEEE.

[16]    Mahloujifar, S., Diochnos, D. I., & Mahmoody, M. (2020). Learning under p-tampering poisoning attacks. Annals of Mathematics and Artificial Intelligence, 88(7), 759-792.

[17]    Jiang, W., Li, H., Liu, S., Luo, X., & Lu, R. (2020). Poisoning and evasion attacks against deep learning algorithms in autonomous vehicles. IEEE transactions on vehicular technology, 69(4), 4439-4449.

[18]    Xu, H., Ma, Y., Liu, H. C., Deb, D., Liu, H., Tang, J. L., & Jain, A. K. (2020). Adversarial attacks and defenses in images, graphs, and text: A review. International Journal of Automation and Computing, 17(2), 151-178.

[19]    Li, D., Deng, L., Gupta, B. B., Wang, H., & Choi, C. (2019). A novel CNN-based security guaranteed image watermarking generation scenario for smart city applications. Information Sciences, 479, 432-447.

[20]    Li, Y., Ma, R., & Jiao, R. (2015). A hybrid malicious code detection method based on deep learning. International Journal of Security and Its Applications, 9(5), 205-216.

[21]    Mohamed, A. R., Dahl, G. E., & Hinton, G. (2011). Acoustic modeling using deep belief networks. IEEE transactions on audio, speech, and language processing, 20(1), 14-22.

[22]    Baldi, P. (2012). Autoencoders, unsupervised learning, and deep architectures. In Proceedings of ICML Workshop on unsupervised and transfer learning (pp. 37-49). JMLR Workshop and Conference Proceedings.

[23]    Zhang, J., Qin, Z., Yin, H., Ou, L., & Zhang, K. (2019). A feature-hybrid malware variants detection using CNN-based opcode embedding and BPNN based API embedding. Computers & Security, 84, 376-392.

[24]    Papernot, N., McDaniel, P., Swami, A., & Harang, R. (2016). Crafting adversarial input sequences for recurrent neural networks. In MILCOM 2016-2016 IEEE Military Communications Conference (pp. 49-54). IEEE.

[25]    Pascanu, R., Stokes, J. W., Sanossian, H., Marinescu, M., & Thomas, A. (2015). Malware classification with recurrent networks. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 1916-1920). IEEE.

[26]    Yang, J., Liu, K., Kang, X., Wong, E. K., & Shi, Y. Q. (2018). Spatial image steganography based on generative adversarial network. arXiv preprint arXiv:1804.07939.

[27]    Li, S., Ye, D., Jiang, S., Liu, C., Niu, X., & Luo, X. (2020). Anti-steganalysis for an image on convolutional neural networks. Multimedia Tools and Applications, 79(7), 4315-4331.

[28]    Xiao, D., Huang, Y., Zhang, X., Shi, H., Liu, C., & Li, Y. (2018). Fault diagnosis of asynchronous motors based on LSTM neural network. In 2018 prognostics and system health management conference (PHM-Chongqing) (pp. 540-545). IEEE.

[29]    Mnih, V., Badia, A. P., Mirza, M., Graves, A., Lillicrap, T., Harley, T., ... & Kavukcuoglu, K. (2016, June). Asynchronous methods for deep reinforcement learning. In International conference on machine learning (pp. 1928-1937). PMLR.

[30]    Javaid, A., Niyaz, Q., Sun, W., & Alam, M. (2016). A deep learning approach for network intrusion detection systems. EAI Endorsed Transactions on Security and Safety, 3(9), e2.

[31]    International Telecommunication Union. (2020). Global Cybersecurity Index 2020. ITU Publications. Retrieved from https://www.itu.int/dms_pub/itu-d/opb/str/D-STR-GCI.01-2021-PDF-E.pdf.

[32]    William S. (2021). Study: US, UK, and Saudi Arabia lead in commitment to cybersecurity - Atlas VPN. Retrieved 26 September 2021, from

https://atlasvpn.com/blog/study-us-uk-and-saudi-arabia-lead-in-commitment-to-cybersecurity.

[33]    Jo, H. (2021). Can the UAE emerge as a leading global defense supplier? Retrieved 26 September 2021, from https://www.defensenews.com/digital-show-dailies/idex/2021/02/15/can-the-uae-emerge-as-a-leading-global-defense-supplier/


Cite this Article as :
Style #
MLA Sonia Ibrahim, Nada Alkenani, Banan Alghamdi, Amal Alfgeeh, Salwa alghamdl, Yusra Alzhrani, Amani Almuntashiri, Rawan Alghamdi, Abeer Salawi, Wejdan Ahmed Alghamdi, Mohammed. I. Alghamdi. "Comparison between Saudi Arabia and USA: Prevention and Dealing with Cyber Security." Journal of Intelligent Systems and Internet of Things, Vol. 5, No. 2, 2021 ,PP. 77-87 (Doi   :  https://doi.org/10.54216/JISIoT.050203)
APA Sonia Ibrahim, Nada Alkenani, Banan Alghamdi, Amal Alfgeeh, Salwa alghamdl, Yusra Alzhrani, Amani Almuntashiri, Rawan Alghamdi, Abeer Salawi, Wejdan Ahmed Alghamdi, Mohammed. I. Alghamdi. (2021). Comparison between Saudi Arabia and USA: Prevention and Dealing with Cyber Security. Journal of Journal of Intelligent Systems and Internet of Things, 5 ( 2 ), 77-87 (Doi   :  https://doi.org/10.54216/JISIoT.050203)
Chicago Sonia Ibrahim, Nada Alkenani, Banan Alghamdi, Amal Alfgeeh, Salwa alghamdl, Yusra Alzhrani, Amani Almuntashiri, Rawan Alghamdi, Abeer Salawi, Wejdan Ahmed Alghamdi, Mohammed. I. Alghamdi. "Comparison between Saudi Arabia and USA: Prevention and Dealing with Cyber Security." Journal of Journal of Intelligent Systems and Internet of Things, 5 no. 2 (2021): 77-87 (Doi   :  https://doi.org/10.54216/JISIoT.050203)
Harvard Sonia Ibrahim, Nada Alkenani, Banan Alghamdi, Amal Alfgeeh, Salwa alghamdl, Yusra Alzhrani, Amani Almuntashiri, Rawan Alghamdi, Abeer Salawi, Wejdan Ahmed Alghamdi, Mohammed. I. Alghamdi. (2021). Comparison between Saudi Arabia and USA: Prevention and Dealing with Cyber Security. Journal of Journal of Intelligent Systems and Internet of Things, 5 ( 2 ), 77-87 (Doi   :  https://doi.org/10.54216/JISIoT.050203)
Vancouver Sonia Ibrahim, Nada Alkenani, Banan Alghamdi, Amal Alfgeeh, Salwa alghamdl, Yusra Alzhrani, Amani Almuntashiri, Rawan Alghamdi, Abeer Salawi, Wejdan Ahmed Alghamdi, Mohammed. I. Alghamdi. Comparison between Saudi Arabia and USA: Prevention and Dealing with Cyber Security. Journal of Journal of Intelligent Systems and Internet of Things, (2021); 5 ( 2 ): 77-87 (Doi   :  https://doi.org/10.54216/JISIoT.050203)
IEEE Sonia Ibrahim, Nada Alkenani, Banan Alghamdi, Amal Alfgeeh, Salwa alghamdl, Yusra Alzhrani, Amani Almuntashiri, Rawan Alghamdi, Abeer Salawi, Wejdan Ahmed Alghamdi, Mohammed. I. Alghamdi, Comparison between Saudi Arabia and USA: Prevention and Dealing with Cyber Security, Journal of Journal of Intelligent Systems and Internet of Things, Vol. 5 , No. 2 , (2021) : 77-87 (Doi   :  https://doi.org/10.54216/JISIoT.050203)