Social Engineering: I-E based Model of Human Weakness for Attack and Defense Investigations

Social engineering is the attack aimed to manipulate dupe to divulge sensitive information or take actions to help the adversary bypass the secure perimeter in front of the information-related resources so that the attacking goals can be completed. Though there are a number of security tools, such as firewalls and intrusion detection systems which are used to protect machines from being attacked, widely accepted mechanism to prevent dupe from fraud is lacking. However, the human element is often the weakest link of an information security chain, especially, in a human-centered environment. In this paper, we reveal that the human psychological weaknesses result in the main vulnerabilities that can be exploited by social engineering attacks. Also, we capture two essential levels, internal characteristics of human nature and external circumstance influences, to explore the root cause of the human weaknesses. We unveil that the internal characteristics of human nature can be converted into weaknesses by external circumstance influences. So, we propose the I-E based model of human weakness for social engineering investigation. Based on this model, we analyzed the vulnerabilities exploited by different techniques of social engineering, and also, we conclude several defense approaches to fix the human weaknesses. This work can help the security researchers to gain insights into social engineering from a different perspective, and in particular, enhance the current and future research on social engineering defense mechanisms

CNA Tactics and Techniques: A Structure Proposal

[EN] Destructive and control operations are today a major threat for cyber physical systems. These operations, known as Computer Network Attack (CNA), and usually linked to state-sponsored actors, are much less analyzed than Computer Network Exploitation activities (CNE), those related to intelligence gathering. While in CNE operations the main tactics and techniques are defined and well structured, in CNA there is a lack of such consensuated approaches. This situation hinders the modeling of threat actors, which prevents an accurate definition of control to identify and to neutralize malicious activities. In this paper, we propose the first global approach for CNA operations that can be used to map real-world activities. The proposal significantly reduces the amount of effort need to identify, analyze, and neutralize advanced threat actors targeting cyber physical systems. It follows a logical structure that can be easy to expand and adapt.Villalón-Huerta, A.; Ripoll-Ripoll, I.; Marco-Gisbert, H. (2021). CNA Tactics and Techniques: A Structure Proposal. Journal of Sensor and Actuator Networks. 10(1):1-23. https://doi.org/10.3390/jsan10010014S12310

Development of Criteria for Mobile Device Cybersecurity Threat Classification and Communication Standards (CTC&CS)

The increasing use of mobile devices and the unfettered access to cyberspace has introduced new threats to users. Mobile device users are continually being targeted for cybersecurity threats via vectors such as public information sharing on social media, user surveillance (geolocation, camera, etc.), phishing, malware, spyware, trojans, and keyloggers. Users are often uninformed about the cybersecurity threats posed by mobile devices. Users are held responsible for the security of their device that includes taking precautions against cybersecurity threats. In recent years, financial institutions are passing the costs associated with fraud to the users because of the lack of security. The purpose of this study was to design, develop, and empirically test new criteria for a Cybersecurity Threats Classification and Communication Standard (CTC&CS) for mobile devices. The conceptual foundation is based on the philosophy behind the United States Occupational Safety and Health Administration (OSHA)’s Hazard Communication Standard (HCS) of Labels and Pictograms that is mainly focused on chemical substances. This study extended the HCS framework as a model to support new criteria for cybersecurity classification and communication standards. This study involved three phases. The first phase conducted two rounds of the Delphi technique and collected quantitative data from 26 Subject Matter Experts (SMEs) in round one and 22 SMEs in round two through an anonymous online survey. Results of Phase 1 emerged with six threats categories and 62 cybersecurity threats. Phase 2 operationalized the elicited and validated criteria into pictograms, labels, and safety data sheets. Using the results of phase one as a foundation, two to three pictograms, labels, and safety data sheets (SDSs) from each of the categories identified in phase one were developed, and quantitative data were collected in two rounds of the Delphi technique from 24 and 19 SMEs respectively through an online survey and analyzed. Phase 3, the main data collection phase, empirically evaluated the developed and validated pictograms, labels, and safety data sheets for their perceived effectiveness as well as performed an analysis of covariance (ANCOVA) with 208 non-IT professional mobile device users. The results of this study showed that pictograms were highly effective; this means the participants were satisfied with the characteristics of the pictograms such as color, shapes, visual complexity, and found these characteristics valuable. On the other hand, labels and Safety Data Sheets (SDS) did not show to be effective, meaning the participants were not satisfied or lacked to identify importance with the characteristics of labels and SDS. Furthermore, the ANCOVA results showed significant differences in perceived effectiveness with SDSs with education and a marginal significance level with labels when controlled for the number of years of mobile device use. Based on the results, future research implications can observe discrepancies of pictogram effectiveness between different educational levels and reading levels. Also, research should focus on identifying the most effective designs for pictograms within the cybersecurity context. Finally, longitudinal studies should be performed to understand the aspects that affect the effectiveness of pictograms

A computer network attack taxonomy and ontology

Computer network attacks differ in the motivation of the entity behind the attack, the execution and the end result. The diversity of attacks has the consequence that no standard classification ex-ists. The benefit of automated classification of attacks, means that an attack could be mitigated accordingly. The authors extend a previous, initial taxonomy of computer network attacks which forms the basis of a proposed network attack ontology in this pa-per. The objective of this ontology is to automate the classifica-tion of a network attack during its early stages. Most published taxonomies present an attack from either the attacker's or defend-er's point of view. The authors' taxonomy presents both these points of view. The framework for an ontology was developed using a core class, the "Attack Scenario", which can be used to characterize and classify computer network attacks