Phishing happens beyond technology : the effects of human behaviors and demographics on each step of a phishing process

Prior studies have shown that the behaviours and attitudes of Internet users influence the likelihood of being victimised by phishing attacks. Many scammers design a step-by-step approach to phishing in order to gain the potential victim's trust and convince them to take the desired actions. It is important to understand which behaviours and attitudes can influence following the attacker in each step of a phishing scam. This will enable us to identify the root causes of phishing and to develop specific mitigation plans for each step of the phishing process and to increase prevention points. This study investigates to what extent people's risk-taking and decision-making styles influence the likelihood of phishing victimisation in three specific phishing steps. We asked participants to play a risk-taking game and to answer questions related to two psychological scales to measure their behaviours, and then conducted a simulated phishing campaign to assess their phishability throughout the three phishing steps selected. We find that the attitude to risk-taking and gender can predict users' phishability in the different steps selected. There are however other possible direct and indirect behavioural factors that could be investigated in future studies. The results of this study and the model developed can be used to build a comprehensive framework to prevent the success of phishing attempts, starting from their root causes

Moving from a "human-as-problem" to a "human-as-solution" cybersecurity mindset

Cybersecurity has gained prominence, with a number of widely publicised security incidents, hacking attacks and data breaches reaching the news over the last few years. The escalation in the numbers of cyber incidents shows no sign of abating, and it seems appropriate to take a look at the way cybersecurity is conceptualised and to consider whether there is a need for a mindset change.To consider this question, we applied a "problematization" approach to assess current conceptualisations of the cybersecurity problem by government, industry and hackers. Our analysis revealed that individual human actors, in a variety of roles, are generally considered to be "a problem". We also discovered that deployed solutions primarily focus on preventing adverse events by building resistance: i.e. implementing new security layers and policies that control humans and constrain their problematic behaviours. In essence, this treats all humans in the system as if they might well be malicious actors, and the solutions are designed to prevent their ill-advised behaviours. Given the continuing incidences of data breaches and successful hacks, it seems wise to rethink the status quo approach, which we refer to as "Cybersecurity, Currently". In particular, we suggest that there is a need to reconsider the core assumptions and characterisations of the well-intentioned human's role in the cybersecurity socio-technical system. Treating everyone as a problem does not seem to work, given the current cyber security landscape.Benefiting from research in other fields, we propose a new mindset i.e. "Cybersecurity, Differently". This approach rests on recognition of the fact that the problem is actually the high complexity, interconnectedness and emergent qualities of socio-technical systems. The "differently" mindset acknowledges the well-intentioned human's ability to be an important contributor to organisational cybersecurity, as well as their potential to be "part of the solution" rather than "the problem". In essence, this new approach initially treats all humans in the system as if they are well-intentioned. The focus is on enhancing factors that contribute to positive outcomes and resilience. We conclude by proposing a set of key principles and, with the help of a prototypical fictional organisation, consider how this mindset could enhance and improve cybersecurity across the socio-technical system

How Do Tor Users Interact With Onion Services?

Onion services are anonymous network services that are exposed over the Tor network. In contrast to conventional Internet services, onion services are private, generally not indexed by search engines, and use self-certifying domain names that are long and difficult for humans to read. In this paper, we study how people perceive, understand, and use onion services based on data from 17 semi-structured interviews and an online survey of 517 users. We find that users have an incomplete mental model of onion services, use these services for anonymity and have varying trust in onion services in general. Users also have difficulty discovering and tracking onion sites and authenticating them. Finally, users want technical improvements to onion services and better information on how to use them. Our findings suggest various improvements for the security and usability of Tor onion services, including ways to automatically detect phishing of onion services, more clear security indicators, and ways to manage onion domain names that are difficult to remember.Comment: Appeared in USENIX Security Symposium 201

Optimizing Anti-Phishing Solutions Based on User Awareness, Education and the Use of the Latest Web Security Solutions

Phishing has grown significantly in volume over the time, becoming the most usual web threat today. The present economic crisis is an added argument for the great increase in number of attempts to cheat internet users, both businesses and private ones. The present research is aimed at helping the IT environment get a more precise view over the phishing attacks in Romania; in order to achieve this goal we have designed an application able to retrieve and interpret phishing related data from five other trusted web sources and compile them into a meaningful and more targeted report. As a conclusion, besides making available regular reports, we underline the need for a higher degree of awareness related to this issue.Security, Phishing, Ev-SSL, Security Solutions

An Evasion and Counter-Evasion Study in Malicious Websites Detection

Malicious websites are a major cyber attack vector, and effective detection of them is an important cyber defense task. The main defense paradigm in this regard is that the defender uses some kind of machine learning algorithms to train a detection model, which is then used to classify websites in question. Unlike other settings, the following issue is inherent to the problem of malicious websites detection: the attacker essentially has access to the same data that the defender uses to train its detection models. This 'symmetry' can be exploited by the attacker, at least in principle, to evade the defender's detection models. In this paper, we present a framework for characterizing the evasion and counter-evasion interactions between the attacker and the defender, where the attacker attempts to evade the defender's detection models by taking advantage of this symmetry. Within this framework, we show that an adaptive attacker can make malicious websites evade powerful detection models, but proactive training can be an effective counter-evasion defense mechanism. The framework is geared toward the popular detection model of decision tree, but can be adapted to accommodate other classifiers