Cybercrime 2.0: When the Cloud Turns Dark

Provos, Niels; Rajab, Moheeb Abu; Mavrommatis, Panayiotis

doi:10.1145/1515964.1517412

Cited by 30 publications

(25 citation statements)

References 2 publications

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“…Emphasis that digital shadow economy activities are profit-driven reveals the general purpose of the phenomenon -financial gain (Holz Moore et al 2009 and others). Inclusion of sophisticated equipment, the requirement for advanced technical skills as well as a high degree of coordination between the offending parties are also pointed out (Dittrich 2009;Provos et al 2009;Vlachos et al 2011). The basic detriment brought about by digital shadow economy is composed of deprivation of the officially registered entities from potential gains (profit, revenues) and lost revenues in the state budget (Vlachos et al 2011;Holz et al 2012;Dobson et al 2015 and others).…”

Section: Concepts Features and Channels Of Digital Shadow Economy: Tmentioning

confidence: 99%

The Definition of Digital Shadow Economy

Remeikienė

Gasparėnienė

Schneider

2017

Technological and Economic Development of Economy

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Abstract. Considering the lack of the scientific studies on the selected topic, the authors of this article raise the aim to set up the definition of digital shadow economy and identify its distinctive features and channels. Thus far, the studies on illegal digital activities have covered ambiguous interpretations of digital shadow economy that incorporated both criminal and economic aspects of the activities performed. The results of the empirical research have enabled to formulate the definition of digital shadow economy that refers to illegal activities, such as digital service provision and sales of goods/services online, when operating exceptionally in digital space, the entities violate the existent legal norms and regulations with a pursuit of illegal mutual interest and material benefits. The newly formulated definition of digital shadow economy has served as a corner-stone for identification of the distinctive features and channels of this phenomenon. Hence, the results of the research may make a significant and weighty contribution to the development of the theory of economics and may raise the awareness of what the phenomenon of digital shadow economy implies.

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Section: Concepts Features and Channels Of Digital Shadow Economy: Tmentioning

confidence: 99%

The Definition of Digital Shadow Economy

Remeikienė

Gasparėnienė

Schneider

2017

Technological and Economic Development of Economy

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“…In the same category we can include drive-by download attacks. Once an attacker embeds malicious code in a vulnerable website, the drive-by download runs automatically when a user visits the website [Mavromatis and Monrose 2008;Provos et al 2009]. In general, full automation can help hide the origin of a semantic attack and reduce the effort required to replicate it, but also limits control over the process.…”

Section: Ma: Mode Of Automationmentioning

confidence: 99%

“…via phishing email, social media post etc). The machines of the users are infected when they open the link to the website [Mavromatis and Monrose 2008;Provos et al 2009;Egele et al 2008;Cova et al 2010]. The deception takes advantage of the normal-looking cosmetics and behaviour of the affected website.…”

Section: Ap2 Es1mentioning

confidence: 99%

A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks

2015

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Social engineering is used as an umbrella term for a broad spectrum of computer exploitations that employ a variety of attack vectors and strategies to psychologically manipulate a user. Semantic attacks are the specific type of social engineering attacks that bypass technical defences by actively manipulating object characteristics, such as platform or system applications, to deceive rather than directly attack the user. Commonly observed examples include obfuscated URLs, phishing emails, drive-by downloads, spoofed websites and scareware to name a few. This paper presents a taxonomy of semantic attacks, as well as a survey of applicable defences. By contrasting the threat landscape and the associated mitigation techniques in a single comparative matrix, we identify the areas where further research can be particularly beneficial.

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“…This could mean that they may; Make a misinformed conclusion or decision (this could range from something very small to very large) Unable to find genuine content Spend additional time on a website as they filtering and searching through genuine and spam content Attempt to inform staff of the problem (which of course may redundantly occur many times by many users) Simply give up and no longer visit the site / lose interest Become emotionally frustrated, angry etc Being redirected to another site which may be one that replicates the original, is an advertising page or may even be something illegal and/or offensive. Their computer becomes infected with Malware [11]. The six stages are shown in Fig.…”

Section: F Content Consumermentioning

confidence: 99%

Key Parameters in Identifying Cost of Spam 2.0

Ridzuan

Potdar

Talevski

et al. 2010

2010 24th IEEE International Conference on Advanced Information Networking and Applications

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Abstract-This paper aims to provide an analytical view in estimating the cost of Spam 2.0. For this purpose, the authors define the web spam lifecycle and its associated impact. We also enlisted 5 stakeholders and focused on defining 5 cost calculations using a large collection of references. The cost of web spam then can be calculated with the definition of 13 parameters. Detail explanations of the web spam cost impacts are given with regards to the main four stakeholders: spammer, application provider, content provider and content consumer. Ongoing research in developing honey spam is also presented in this paper.

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Cybercrime 2.0: When the Cloud Turns Dark

Abstract: joined Google in 2003 and is currently a principal software engineer in the Infrastructure Security Group. His areas of interest include computer and network security, as well as large-scale distributed systems. He serves on the Usenix board of directors. MOHEEB ABU RAJAB

Cited by 30 publications

References 2 publications

The Definition of Digital Shadow Economy

The Definition of Digital Shadow Economy

A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks

Key Parameters in Identifying Cost of Spam 2.0

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