Essay Example on IoT: Benefits, Risks, and Phishing Challenges

Introduction

IoT is a very useful invention in the history of human existence, but the dangers associated with it are extremely risky. Atlam and Wills (2020) cite phishing attacks as resulting from unethical use of internet space (Atlam and Wills, 2020, pp. 123-149). The improvement of interaction and communication between human beings through technological inventions. have led to many risks and security challenges that never existed before. Phishing is one of the challenges that have evolved despite the efforts by the cybersecurity enforcers and developers to stop it. Smart IoT devices are able to connect to the internet, appliance's such as watches and mobile devices makes life easier, but makes the owner vulnerable to cybercriminals.

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The Current System in Stopping Phishing Attacks

The advancement in technology and mining of knowledge data is making the systems put in place by the software developers and security teams to fight against phishing. The attacks are occurring through the security loopholes. The current security system has only applied the installation of security devices such as the anti-virus software. The move is still advisable, but the advancing nature of the attacks, calls for a broader system that can deal with it permanently (Holland and Shey, 2015). It can involve the incorporation of online education to the users on the importance of becoming cautious while using internet platforms, and be aware of malicious sites and requests for confidential information.

How to Improve Detection of Phishing Attacks?

The understanding of the existing problem in the current detection and prevention systems traces back to the first phishing attack in the American networks systems in the year 1990s.The validity tests were passed finally to be discovered to be fake and fraudulent.

Phishing on IoT devices occurs, through several methods including, the embedding of links in an email that redirects the victim to an unsecured website that harvests sensitive information.

Visual appearance can be used in detecting the attack earlier before it can harm the user. It is a system that makes the use of visual appearances, based on the exploitation of the clone features by the attackers. (Jain and Gupta, 2017). The attackers have advanced their methods by installing Trojan, through an email attachment, or even an advertisement, enabling the attacker to access the information via loopholes. Latest methods include the faking of sites or emails to look exactly like trusted ones or reputable and request the information. The modern impersonation has led to the current detection strategies to fail in countering phishing.

Development of a system that can easily fight to phish includes the consideration of the ethical and work-life of employees. An analysis of the various methods in which the attacks occurred led to the conclusion that the targeted victims can be in charge of any attempts to hack into their systems. (Deogirikar and Vidhate, 2017, pp. 32-37) The best way of detecting phishing attacks on any IoT network is by always avoiding clicking on malicious links, especially if the link does not match the one purported by the company or the sender. Installation spam filter for emails puts a person at an advantage, of recognizing credible emails and the suspicious ones before it reaches inbox. In case the hackers access the mailbox. Two-step verification of all mails is important in doubling the security even when the security is already compromised. Browser add-ons and the other extensions are useful in identifying a potential site that is likely to be hackers bait

Contributions to The Field of Technology

The research involves the analysis of studies, and previous researches on the nature of phishing throughout the development of technology, and how the attackers have always utilized the loopholes in the cybersecurity (Hassanzadeh et al., 2015, pp. 795-800). The research is useful in the development of a comprehensive security system that can address detection and prevention of the attacks by a large scale and possibly permanently, after the understanding of the recurring, attacks and the common methods used by the attackers.

References

Andrea, I., Chrysostomou, C. and Hadjichristofi, G., 2015, July. Internet of Things: Security vulnerabilities and challenges. In 2015 IEEE Symposium on Computers and Communication (ISCC) (pp. 180-187). IEEE.https://ieeexplore.ieee.org/abstract/document/7405513/.

Atlam, H.F. and Wills, G.B., 2020. IoT Security, privacy, safety and ethics. In Digital Twin Technologies and Smart Cities (pp. 123-149). Springer, Cham.https://link.springer.com/chapter/10.1007/978-3-030-18732-3_8

Chaudhary, P. and Gupta, B.B., 2019, October. DDoS Detection Framework in Resource-Constrained Internet of Things Domain. In 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE) (pp. 675-678). IEEE

Chaudhry, J.A., Chaudhry, S.A. and Rittenhouse, R.G., 2016. Phishing attacks and defences. International Journal of Security and Its Applications, 10(1), pp.247-256.https://www.researchgate.net/profile/Robert_Rittenhouse/publication/296916234_Phishing_attacks_and_defenses/links/573e7afb08ae9f741b300e23.pdf

Deogirikar, J. and Vidhate, A., 2017, February. Security attacks in IoT: A survey. In 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC) (pp. 32-37). IEEE

Gupta, B.B., Arachchilage, N.A. and Psannis, K.E., 2018. Defending against phishing attacks: the taxonomy of methods, current issues and future directions. Telecommunication Systems, 67(2), pp.247-267.

Hassanzadeh, A., Modi, S. and Mulchandani, S., 2015, December. Towards effective security control assignment in the Industrial Internet of Things. In 2015 IEEE 2nd World Forum on the Internet of Things (WF-IoT) (pp. 795-800). IEEE.

Holland, R. and Shey, H., 2015. Predictions 2016: Cybersecurity Swings to Prevention. https://informationsecurity.report/Resources/Whitepapers/f35e8ca6-a389-43e1-819b-2e2836cc9e9b_forrester-predictions-2016-cybersecurity-swings-to-prevention-report-pdf-10-w-2114.pdf

Iqbal, S., Kiah, M.L.M., Dhaghighi, B., Hussain, M., Khan, S., Khan, M.K. and Choo, K.K.R., 2016. On cloud security attacks: A taxonomy and intrusion detection and prevention as a service. Journal of Network and Computer Applications, 74, pp.98-120.

Jain, A.K. and Gupta, B.B., 2017. Phishing detection: analysis of visual similarity-based approaches. Security and Communication Networks, 2017.

Lam, T. and Kettani, H., 2019, April. PhAttApp: A Phishing Attack Detection Application. In Proceedings of the 2019 3rd International Conference on Information System and Data Mining (pp. 154-158).

Shaikh, A.N., Shabut, A.M. and Hossain, M.A., 2016, December. A literature review on phishing crime, prevention review and investigation of gaps. In 2016 10th International Conference on Software, Knowledge, Information Management & Applications (SKIMA) (pp. 9-15). IEEE