A New Role for Human Resource Managers: Social Engineering Defense

[Excerpt] The general risk of social engineering attacks to organizations has increased with the rise of digital computing and communications, while for an attacker the risk has decreased. In order to counter the increased risk, organizations should recognize that human resources (HR) professionals have just as much responsibility and capability in preventing this risk as information technology (IT) professionals. Part I of this paper begins by defining social engineering in context and with a brief history pre-digital age attacks. It concludes by showing the intersection of HR and IT through examples of operational attack vectors. In part II, the discussion moves to a series of measures that can be taken to help prevent social engineering attacks

An Examination of User Detection of Business Email Compromise Amongst Corporate Professionals

With the evolution in technology and increase in utilization of the public Internet, Internet-based mobile applications, and social media, security risks for organizations have greatly increased. While corporations leverage social media as an effective tool for customer advertisements, the abundance of information available via public channels along with the growth in Internet connections to corporate networks including mobile applications, have made cyberattacks attractive for cybercriminals. Cybercrime against organizations is a daily threat and targeting companies of all sizes. Cyberattacks are continually evolving and becoming more complex that make it difficult to protect against with traditional security methods. Cybercriminals utilize email attacks as their most common method to compromise corporations for financial gain. Email attacks on corporations have evolved into very sophisticated scams that specifically target businesses that conduct wire transfers or financial transactions as part of their standard mode of operations. This new evolution of email driven attacks is called Business Email Compromise (BEC) attacks and utilize advanced social engineering, phishing techniques, and email hacking to manipulate employees into conducting fraudulent wire transfers that are intended for actual suppliers and business partners. One of the most common types of BEC attacks is the Chief Executive Officer (CEO) fraud, which are highly customized and targeted attacks aimed to impersonate corporate users that have authority to approve financial transactions and wire transfers in order to influence an employee to unknowingly conduct a fraudulent financial wire transfer. Thus, the main goal of this research study was to assess if there are any significant differences of corporate users’ detection skills of BEC attacks in a simulated test environment based on their personality attributes, using the Myers-Briggs Type Indicator® (MBTI®)’ 16 personalities® framework. BEC attacks have attributed to over $26 billion in corporate financial losses across the globe and are continually increasing. The human aspect in the cybersecurity has been a known challenge and is especially significant in direct interaction with BEC attacks. Furthermore, this research study analyzed corporate users’ attention span levels and demographics to assess if there are any significant differences on corporate users’ BEC attack detection skills. Moreover, this research study analyzed if there are any significant differences for BEC detection skills before and after a BEC awareness training. This research study was conducted by first developing an experiment to measure BEC detection and ensure validity via cybersecurity subject matter experts using the Delphi process. The experiment also collected qualitative and quantitative data for the participants’ performance measures using an application developed for the study. This research was conducted on a group of 45 corporate users in an experimental setting utilizing online surveys and a BEC detection mobile test application. This research validated and developed a BEC detection measure as well as the BEC awareness training module that were utilized in the research experiment. The results of the experiments were analyzed using analysis of variance (ANOVA) and analysis of covariance (ANCOVA) to address the research questions. It was found that there were that no statistically significant mean differences for Business Email Compromise Detection (BECD) skills between personality attributes of corporate professional participants, However, results indicated that there was a significant mean difference for BECD skills and span attention with a p\u3c.0001. Furthermore, there was a significant mean difference for BECD skills and span attention when controlled for gender with a p\u3c0.05. Furthermore, the results indicated that the BEC detection awareness training significantly improved the participant BEC detection skill with a p\u3c.0001. Moreover, following the training, it was found that female BEC detection test scores improved by 45% where the men BECD score improved by 31%. Recommendations for research and industry stakeholders are provided, including to corporations on methods to mitigate BEC attacks

Undertsanding the intention to click on a phishing e-mail

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsA phishing e-mail takes advantage of human vulnerability, which is common, and is consequently not completely preventable. Phishing e-mails are the leading cause of organizational security breaches. To study this phenomenon, we combine the theory of planned behaviour model with preventive countermeasures to understand the intention to click on a phishing e-mail. Based on 144 individuals, we show that behaviour intention and preventive countermeasures influence the intention to click on a phishing e-mail. Based on our findings, we provide theoretical and practical implications

Refining the PoinTER “human firewall” pentesting framework

PurposePenetration tests have become a valuable tool in the cyber security defence strategy, in terms of detecting vulnerabilities. Although penetration testing has traditionally focused on technical aspects, the field has started to realise the importance of the human in the organisation, and the need to ensure that humans are resistant to cyber-attacks. To achieve this, some organisations “pentest” their employees, testing their resilience and ability to detect and repel human-targeted attacks. In a previous paper we reported on PoinTER (Prepare TEst Remediate), a human pentesting framework, tailored to the needs of SMEs. In this paper, we propose improvements to refine our framework. The improvements are based on a derived set of ethical principles that have been subjected to ethical scrutiny.MethodologyWe conducted a systematic literature review of academic research, a review of actual hacker techniques, industry recommendations and official body advice related to social engineering techniques. To meet our requirements to have an ethical human pentesting framework, we compiled a list of ethical principles from the research literature which we used to filter out techniques deemed unethical.FindingsDrawing on social engineering techniques from academic research, reported by the hacker community, industry recommendations and official body advice and subjecting each technique to ethical inspection, using a comprehensive list of ethical principles, we propose the refined GDPR compliant and privacy respecting PoinTER Framework. The list of ethical principles, we suggest, could also inform ethical technical pentests.OriginalityPrevious work has considered penetration testing humans, but few have produced a comprehensive framework such as PoinTER. PoinTER has been rigorously derived from multiple sources and ethically scrutinised through inspection, using a comprehensive list of ethical principles derived from the research literature

An eye for deception: A case study in utilizing the human-as-a-security-sensor paradigm to detect zero-day semantic social engineering attacks

In a number of information security scenarios, human beings can be better than technical security measures at detecting threats. This is particularly the case when a threat is based on deception of the user rather than exploitation of a specific technical flaw, as is the case of spear-phishing, application spoofing, multimedia masquerading and other semantic social engineering attacks. Here, we put the concept of the humanas-a-security-sensor to the test with a first case study on a small number of participants subjected to different attacks in a controlled laboratory environment and provided with a mechanism to report these attacks if they spot them. A key challenge is to estimate the reliability of each report, which we address with a machine learning approach. For comparison, we evaluate the ability of known technical security countermeasures in detecting the same threats. This initial proof of concept study shows that the concept is viable

Crowdsourcing Cybersecurity: Cyber Attack Detection using Social Media

Social media is often viewed as a sensor into various societal events such as disease outbreaks, protests, and elections. We describe the use of social media as a crowdsourced sensor to gain insight into ongoing cyber-attacks. Our approach detects a broad range of cyber-attacks (e.g., distributed denial of service (DDOS) attacks, data breaches, and account hijacking) in an unsupervised manner using just a limited fixed set of seed event triggers. A new query expansion strategy based on convolutional kernels and dependency parses helps model reporting structure and aids in identifying key event characteristics. Through a large-scale analysis over Twitter, we demonstrate that our approach consistently identifies and encodes events, outperforming existing methods.Comment: 13 single column pages, 5 figures, submitted to KDD 201

The Relationship Between Social Persuasion Strategies, Phishing Features and Email Exposure Time on Phishing Susceptibility

This item is only available electronically.A ‘phishing email’ aims to persuade an unsuspecting individual to reveal personal credentials and sensitive information. Currently, the global costs to businesses and individuals associated with phishing related attacks are reported in the hundreds of millions of dollars. While technological interventions capture a proportion of these phishing emails, ultimately, the human user is the last line of defence in determining the legitimacy of the email. ‘Phishers’ aim to exploit human weaknesses through the use of various persuasion strategies that create a sense of urgency and time pressure to respond to emails. Typically, individuals must also rely on subtle phishing features in an email to determine if the email is genuine or an attempted phish. Furthermore, phishers take advantage of the assumption that users determine the legitimacy of emails in a short amount of time. The present study aims to examine the impact of these email characteristics of persuasion strategies, the number of phishing features, and exposure time on phishing detection and susceptibility. Using an online survey platform, participants (N= 136) completed an email sorting task where they were required to review and sort 60 incoming emails from the inbox of ‘Professor Alex Jones’. Several significant results were obtained supporting the hypotheses. It demonstrated that individuals are better able to detect a phishing email when it utilises common persuasion strategies (authority and scarcity), and contain a greater number of phishing features. It also revealed that with increased email exposure time, individuals had a better phishing detection rate. However, the effect of identifying phishing emails with common persuasion strategies was not greater during shorter exposure time, providing a non-significant result. A greater understanding of these email factors associated with phishing susceptibility could lead to more tailored awareness campaigns and/or training programs to increase phishing detection and reduce susceptibility.Thesis (B.PsychSc(Hons)) -- University of Adelaide, School of Psychology, 202

SUBJECT MATTER EXPERTS’ FEEDBACK ON EXPERIMENTAL PROCEDURES TO MEASURE USER’S JUDGMENT ERRORS IN SOCIAL ENGINEERING ATTACKS

Distracted users can fail to correctly distinguish the differences between legitimate and malicious emails or search engine results. Mobile phone users can have a more challenging time identifying malicious content due to the smaller screen size and the limited security features in mobile phone applications. Thus, the main goal of this research study was to design, develop, and validate a set of field experiments to assess user’s judgment when exposed to two types of simulated social engineering attacks: phishing and Potentially Malicious Search Engine Results (PMSER), based on the interaction of the environment (distracting vs. non-distracting) and type of device used (mobile vs. computer). In this paper, we provide the results from the Delphi methodology research we conducted using an expert panel consisting of 28 cybersecurity Subject Matter Experts (SMEs) who participated, out of 60 cybersecurity experts invited. Half of the SMEs were with over 10 years of experience in cybersecurity, the rest around five years. SMEs were asked to validate two sets of experimental tasks (phishing & PMSER) as specified in RQ1. The SMEs were then asked to identify physical and Audio/Visual (A/V) environmental factors for distracting and non-distracting environments. About 50% of the SMEs found that an airport was the most distracting environment for mobile phone and computer users. About 35.7% of the SMEs also found that a home environment was the least distracting environment for users, with an office setting coming into a close second place. About 67.9% of the SMEs chose “all” for the most distracting A/V distraction level, which included continuous background noise, visual distractions, and distracting/loud music. About 46.4% of the SMEs chose “all” for the least distracting A/V level, including a quiet environment, relaxing background music, and no visual distractions. The SMEs were then asked to evaluate a randomization table. This was important for RQ2 to set up the eight experimental protocols to maintain the validity of the proposed experiment. About 89.3% indicated a strong consensus that we should keep the randomization as it is. The SMEs were also asked whether we should keep, revise, or replace the number of questions for each mini-IQ test to three questions each. About 75% of the SMEs responded that we should keep the number of mini-IQ questions to three. Finally, the SMEs were asked to evaluate the proposed procedures for the pilot testing and experimental research phases conducted in the future. About 96.4% of the SMEs selected to keep the first pilot testing procedure. For second and third pilot testing procedures, the SMEs responded with an 89.3% strong consensus to keep the procedures. For the first experimental procedure, a strong consensus of 92.9% of the SMEs recommended keeping the procedure. Finally, for the third experimental procedure, there was an 85.7% majority to keep the procedure. The expert panel was used to validate the proposed experimental procedures and recommended adjustments. The conclusions, study limitations, and recommendations for future research are discussed