Reverse Social Engineering to Counter Social Engineering in Mobile Money Theft: A Tanzanian Context

Kilavo, Hassan; Mselle, Leonard J.; Rais, Ramadhani I.; Mrutu, Salehe I.

doi:10.1080/19361610.2022.2031702

Cited by 3 publications

(2 citation statements)

References 1 publication

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“…The rise of interconnected systems and the Internet of Things (IoT) introduced new threat vectors, allowing attackers to exploit vulnerabilities in interconnected devices and networks . Social engineering became increasingly prevalent, leveraging psychological manipulation to deceive individuals or gain unauthorized access (Kilavo et al, 2023). Advanced Persistent Threats (APTs) marked another shift, involving prolonged and targeted attacks for data exfiltration or system compromise (Quintero-Bonilla & Martín del Rey, 2020).…”

Section: Evolution Of Cyber Threats and Their Impact On Traditional S...mentioning

confidence: 99%

Learn, Unlearn and Relearn: Adaptive Cybersecurity Culture Model

Gundu

2024

iccws

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In the ever-evolving cyberspace landscape, organisations face persistent threats that continuously mutate and adapt. To effectively defend against these dynamic cyber threats, a fundamental shift in cybersecurity culture is imperative. This paper presents a novel Adaptive Cybersecurity Culture Model (ACCM) that encapsulates the principles of "Learn, Unlearn, and Relearn" as a strategic stance to foster resilience and adaptability in the face of evolving cyber threats. The ACCM emphasizes the importance of continuous learning as the cornerstone of cybersecurity culture. It advocates the adoption of a growth mindset within organisations, encouraging employees to stay updated with emerging threats, technologies, and best practices. However, the model goes beyond mere learning; it underscores the significance of unlearning outdated practices and misconceptions that may hinder effective cybersecurity. Furthermore, the ACC model introduces the concept of "Relearn," emphasizing the need to rapidly adapt and evolve strategies and tactics in response to ever-changing cyber threats. It promotes a culture of agility and adaptability, enabling organisations to respond effectively to both known and unforeseen cyber challenges. The model presented in this paper draws from case studies of various industries to illustrate the successful adoption and transformation of cybersecurity culture using the Learn, Unlearn, and Relearn principles. The ACCM represents a paradigm shift in cybersecurity culture, acknowledging that the ability to adapt is as critical as the ability to protect. By fostering a culture of continuous learning, unlearning, and relearning, organisations can proactively enhance their cyber resilience and effectively defend against the ever-evolving cyber threat landscape. This paper provides a roadmap for organisations to embark on this transformative journey toward a more adaptive and resilient cybersecurity culture.

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Section: Evolution Of Cyber Threats and Their Impact On Traditional S...mentioning

confidence: 99%

Learn, Unlearn and Relearn: Adaptive Cybersecurity Culture Model

Gundu

2024

iccws

View full text Add to dashboard Cite

show abstract

“…Eliminating attacker profiles and concentrating on human targets are critical beneficiary targets. The victim's capacity to withstand the manipulation of behavior, either by recognizing and/or responding in an attack-coping way, is what determines the success of SE assaults (Kilavo et al, 2023). Investigating Cialdini's concepts of influencing current social engineering research methodologies provided ideas for probable relationships between the Five-Factor Models personality factors (the "Big 5").…”

Section: Personality Traits Frameworkmentioning

confidence: 99%

A comprehensive survey on social engineering-based attacks on social networks

Naz,

Sarwar,

Kaleem

et al. 2024

Int. j. adv. appl. sci.

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Threats based on social engineering in social networks are becoming a more common problem. Social engineering is a type of attack that relies on trickery and exploiting human psychology to gain access to confidential information or resources. It involves deceptive techniques like phishing, pretexting, and baiting, tricking individuals into revealing sensitive information or performing specific actions. These tactics can lead to unauthorized access to user accounts, identity theft, or the distribution of harmful content. This study offers a detailed review of threats related to social engineering on social networks. It explores various social engineering attacks, the methods used to execute these threats, and measures that can be adopted to minimize the risk of becoming a victim. The research aimed to develop a new, broad classification of social engineering attacks and strategies for responding to them. It also examines the challenges that social engineering poses to algorithms on social media platforms and highlights the need for more research. The study concludes by pointing out the shortcomings of current approaches and suggesting future research directions, stressing the importance of standardized protective measures and increasing awareness among potential victims. This thorough examination improves our understanding of social engineering attacks and encourages the development of innovative solutions and ethical practices, contributing to a more secure digital environment.

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Determinants of Mobile Money Fraud on C2C E-Commerce

Fianu

Arku

Boateng

2023

Exploring the Dark Side of FinTech and Implications of Monetary Policy

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The study sought to investigate the determinants of MoMo fraud perception in C2C e-commerce from a trust perspective. The research model comprises a set of relationships between constructs from empirical studies. The constructs are culture (uncertainty avoidance), perceived reputation of mobile service provider, trust in C2C trader, structural assurance, perceived usefulness, and consumer fraud perception. A quantitative research design was used for the study. The sample consisted of three hundred and eighty-seven (387) respondents. Data were analysed using PLS-SEM (partial least squares structural equation modelling) via SmartPLS 3. Culture (uncertainty avoidance) was found to have a significant negative influence on consumer fraud perception. Perceived reputation of the mobile service provider was found to have an insignificant influence on consumer fraud perception. Trust in C2C trader, structural assurance, and perceived usefulness were found to have a significant positive influence on consumer fraud perception.

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Reverse Social Engineering to Counter Social Engineering in Mobile Money Theft: A Tanzanian Context

Cited by 3 publications

References 1 publication

Learn, Unlearn and Relearn: Adaptive Cybersecurity Culture Model

Learn, Unlearn and Relearn: Adaptive Cybersecurity Culture Model

A comprehensive survey on social engineering-based attacks on social networks

Determinants of Mobile Money Fraud on C2C E-Commerce

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