Risk prediction of malware victimization based on user behavior

Lévesque, Fanny Lalonde; Fernandez, José M.; Somayaji, Anil

doi:10.1109/malware.2014.6999412

Cited by 21 publications

(5 citation statements)

References 6 publications

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“…Profit-driven cybercrime, which is the focus of this paper/research, has been studied by both social scientists and computer scientists. It has been characterised by empirical contributions that have sought to illuminate the nature and organisation of cybercrime both online and offline [15][16][17][18][19][20]. But, as noted above, the geography of cybercrime has only been addressed by a handful of scholars, and they have identified a number of challenges connected to existing data.…”

Section: Introductionmentioning

confidence: 99%

“…Often using technical data, cybersecurity firms, law enforcement agencies and international organisations regularly publish reports that identify the major sources of cyber attacks (see for example [21][22][23][24]). Some of these sources have been aggregated by scholars (see [20,[25][26][27][28][29]). But the kind of technical data contained in these reports cannot accurately measure offender location.…”

Section: Introductionmentioning

confidence: 99%

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Mapping the global geography of cybercrime with the World Cybercrime Index

Bruce,

Lusthaus,

Kashyap

et al. 2024

PLoS ONE

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Cybercrime is a major challenge facing the world, with estimated costs ranging from the hundreds of millions to the trillions. Despite the threat it poses, cybercrime is somewhat an invisible phenomenon. In carrying out their virtual attacks, offenders often mask their physical locations by hiding behind online nicknames and technical protections. This means technical data are not well suited to establishing the true location of offenders and scholarly knowledge of cybercrime geography is limited. This paper proposes a solution: an expert survey. From March to October 2021 we invited leading experts in cybercrime intelligence/investigations from across the world to participate in an anonymized online survey on the geographical location of cybercrime offenders. The survey asked participants to consider five major categories of cybercrime, nominate the countries that they consider to be the most significant sources of each of these types of cybercrimes, and then rank each nominated country according to the impact, professionalism, and technical skill of its offenders. The outcome of the survey is the World Cybercrime Index, a global metric of cybercriminality organised around five types of cybercrime. The results indicate that a relatively small number of countries house the greatest cybercriminal threats. These findings partially remove the veil of anonymity around cybercriminal offenders, may aid law enforcement and policymakers in fighting this threat, and contribute to the study of cybercrime as a local phenomenon.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mapping the global geography of cybercrime with the World Cybercrime Index

Bruce,

Lusthaus,

Kashyap

et al. 2024

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…Overall, it is estimated that the majority of users fall victim to some form of cybercrime [21][22][23], with malware and fraudulent activities being the most common [18,23,24]. In terms of predictors, self-protective behavior (related to users' threat and risk perception, their perceptions and attitudes towards security technologies) [25,26], online activities [27][28][29], psychological traits [30][31][32], and socio-demographic characteristics [33,34] were established to have a significant influence on cybercrime victimization.…”

Section: Introductionmentioning

confidence: 99%

Country Life in the Digital Era: Comparison of Technology Use and Cybercrime Victimization between Residents of Rural and Urban Environments in Slovenia

2022

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Cybercrime is one of the most significant security challenges of the 21st century. However, official statistics do not provide insights into its prevalence and nature. Representative cross-sectional field studies may help fill this gap, focusing on differences between urban and rural technology users. We (a) investigated the association between the purpose of computers and other electronic device usage and perceived vulnerability, (b) compared the differences in the purpose of computers or other electronic device use and perceived vulnerability, and (c) compared the perceived cyber victimization between residents of rural and urban areas. We conducted a field study that resulted in a representative sample of the Republic of Slovenia in Europe. We found several significant differences in the purpose of technology use and perceived cyber victimization. Furthermore, the results indicate that the purpose of technology use is somehow associated with perceived vulnerability in cyberspace; however, such associations are different in cyberspace than in the material world.

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“…First, some researchers examined the differences between users regarding their browsing habits and the corresponding needs for personalized protection [1,[4][5][6][7][8][9][10][11]. Second, several systems addressed the benefit of having a proactive or predictive approach rather than a reactive one; taking action only once the attack occurred could lower the effectiveness of blocking the malware [3,4,8,[12][13][14][15]. Third, some projects considered the need to maintain a low level of privacy invasion while supplying means of protection to the users [8].…”

Section: Introductionmentioning

confidence: 99%

“…For a security system to be proactive, it needs to predict the level of risk or forecast an upcoming malware attack. The subject of predicting the risk of infection has been addressed in several studies [3,4,8,[12][13][14][15]. Bilge et al [13] achieved excellent results in predicting infections by analyzing the binaries installed on users' computers and identifying ones that are more likely to be attacked.…”

Section: Introductionmentioning

confidence: 99%

Co-similar malware infection patterns as a predictor of future risk

2021

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The internet is flooded with malicious content that can come in various forms and lead to information theft and monetary losses. From the ISP to the browser itself, many security systems act to defend the user from such content. However, most systems have at least one of three major limitations: 1) they are not personalized and do not account for the differences between users, 2) their defense mechanism is reactive and unable to predict upcoming attacks, and 3) they extensively track and use the user’s activity, thereby invading her privacy in the process. We developed a methodological framework to predict future exposure to malicious content. Our framework accounts for three factors–the user’s previous exposure history, her co-similarity to other users based on their previous exposures in a conceptual network, and how the network evolves. Utilizing over 20,000 users’ browsing data, our approach succeeds in achieving accurate results on the infection-prone portion of the population, surpassing common methods, and doing so with as little as 1/1000 of the personal information it requires.

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Risk prediction of malware victimization based on user behavior

Cited by 21 publications

References 6 publications

Mapping the global geography of cybercrime with the World Cybercrime Index

Mapping the global geography of cybercrime with the World Cybercrime Index

Country Life in the Digital Era: Comparison of Technology Use and Cybercrime Victimization between Residents of Rural and Urban Environments in Slovenia

Co-similar malware infection patterns as a predictor of future risk

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