Examining the Craft of Social Engineering Attacks and Countermeasures

By: KUKUTLA TEJONATH REDDY, International Center for AI and Cyber Security Research and Innovations (CCRI), Asia University, Taiwan, tejonath45@gmail.com

Abstract:


Social engineering attacks, characterized by the skillful manipulation of human intelligence, represent a major threat in today’s digital environment. This comprehensive article examines the nuances of social engineering, dissecting notorious tactics such as phishing, pretexting and baiting. Through compelling examples and real-world case studies, it explores the complex web of strategies, power, reciprocity, fear and urgency of bullying individuals and organizational the consequences of these attacks are far-reaching, including financial losses, data breaches and reputational damage. However, the story doesn’t just focus on threats; It also offers quick solutions [1]. It outlines strong prevention strategies, emphasizes education, awareness, secure communications, prudent personal information practices, and strong organizational structure by fostering a culture of cybersecurity consciousness developed with the implementation of these techniques, individuals and organizations can strengthen their security and provide a secure digital environment for all [2].

Introduction:


Social engineering attacks represent a sophisticated form of fraud, in which attackers use human psychology and social dynamics to manipulate individuals into disclosing sensitive information or taking actions against their interests This article examines social technology attacks complex attacks in depth, analysing various types of phishing, targeting, baiting. It also examines the psychological theories and strategies involved [3].

Types of Social Engineering Attacks:

Phishing: Phishing is one of the most common social engineering attacks, where fraudulent attempts to obtain sensitive information such as passwords or credit card numbers masquerading as trusted companies induce attackers to send emails such as reputable organizations that ask recipients to click on malicious links and provide confidential information [1].

Pretexting: The solution is to create a simulated situation to get information from the target. Attackers typically pose as an official such as an IT professional or corporate executive, manipulating individuals into revealing sensitive information [1].

Baiting: Decoy attacks lure victims into a trap with the promise of something they want. Attackers offer free downloads of malware-infected movies or software. Once downloaded, the malware damages the victim’s system.

Techniques and Manipulation Tactics:

Authority and Trust: Social engineers exploit the trust that authorities have in individuals. They relied on their natural tendency to listen to authority figures and imitated a boss, colleague, or IT professional [4].

Reciprocity: Something as small as a fake or free survey can be created by social engineers to feel indebted, making it easier for individuals to comply with requests.

Fear and Urgency: Social engineers often create urgency or fear, forcing their victims to act immediately. Fear tactics, such as the threat of account suspension, trigger impulsive, ill-considered reactions.

Consequences and Impacts:

A social engineering attack can have serious consequences:

Financial loss: Victims of unauthorized trading or fraud can lose money.

Data breach: Attackers gain access to sensitive information, leading to identity theft or corporate spying.

Reputation damage: Individuals and organizations experience reputational damage, which affects the trust of customers and partners.

Preventive measures and best practices:

Education and Awareness: Regular training programs expose people to various social engineering techniques. Employees must learn to recognize suspicious requests and verify the identity of the requester.

Two-Factor (2FA): Use 2FA to add a layer of security, requiring additional authentication beyond passwords.

Secure Communication Channels: Encourage the use of encrypted communication tools, to reduce the risk of theft and intermediary attacks.

Vigilance with Personal Information: Encourage discreet sharing of personal information online and offline. Individuals should avoid excessive sharing on social media.

Strong security measures: Organizations need to establish and enforce strong security measures, defining how sensitive information is handled, shared and stored.

Conclusion:

Social engineering attacks exploit the very fabric of human trust and communication. It is important to understand the various mechanisms involved and implement proactive preventive measures. By fostering a culture of cybersecurity awareness and decency, individuals and organizations can create strong defences against these fraudulent techniques, and ensure a secure digital environment for everyone.

References:

  1. Ivaturi, Koteswara and Janczewski, Lech, “A Taxonomy for Social Engineering attacks” (2011). CONF-IRM 2011 Proceedings. 15. http://aisel.aisnet.org/confirm2011/15
  2. I. Ghafir, V. Prenosil, A. Alhejailan and M. Hammoudeh, “Social Engineering Attack Strategies and Defence Approaches,” 2016 IEEE 4th International Conference on Future Internet of Things and Cloud (FiCloud), Vienna, Austria, 2016, pp. 145-149, doi: 10.1109/FiCloud.2016.28.
  3. M. R. Arabia-Obedoza, G. Rodriguez, A. Johnston, F. Salahdine and N. Kaabouch, “Social Engineering Attacks A Reconnaissance Synthesis Analysis,” 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York, NY, USA, 2020, pp. 0843-0848, doi: 10.1109/UEMCON51285.2020.9298100.
  4. Salahdine F, Kaabouch N. Social Engineering Attacks: A Survey. Future Internet. 2019; 11(4):89. https://doi.org/10.3390/fi11040089
  5. S. Gupta, A. Singhal and A. Kapoor, “A literature survey on social engineering attacks: Phishing attack,” 2016 International Conference on Computing, Communication and Automation (ICCCA), Greater Noida, India, 2016, pp. 537-540, doi: 10.1109/CCAA.2016.7813778.
  6. Chui, K. T., Kochhar, T. S., Chhabra, A., Singh, S. K., Singh, D., Peraković, D., … & Arya, V. (2022). Traffic accident prevention in low visibility conditions using vanets cloud environment. International Journal of Cloud Applications and Computing (IJCAC), 12(1), 1-21.
  7. Gupta, P., Yadav, K., Gupta, B. B., Alazab, M., & Gadekallu, T. R. (2023). A Novel Data Poisoning Attack in Federated Learning based on Inverted Loss Function. Computers & Security, 130, 103270.
  8. Jain, A. K., Gupta, B. B., Kaur, K., Bhutani, P., Alhalabi, W., & Almomani, A. (2022). A content and URL analysis‐based efficient approach to detect smishing SMS in intelligent systems. International Journal of Intelligent Systems, 37(12), 11117-11141.

Cite As

REDDY K.T (2023) Examining the Craft of Social Engineering Attacks and Countermeasures, Insights2Techinfo, pp.1

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