Herding Vulnerable Cats: A Statistical Approach to Disentangle Joint Responsibility for Web Security in Shared Hosting

Hosting providers play a key role in fighting web compromise, but their ability to prevent abuse is constrained by the security practices of their own customers. {\em Shared} hosting, offers a unique perspective since customers operate under restricted privileges and providers retain more control over configurations. We present the first empirical analysis of the distribution of web security features and software patching practices in shared hosting providers, the influence of providers on these security practices, and their impact on web compromise rates. We construct provider-level features on the global market for shared hosting -- containing 1,259 providers -- by gathering indicators from 442,684 domains. Exploratory factor analysis of 15 indicators identifies four main latent factors that capture security efforts: content security, webmaster security, web infrastructure security and web application security. We confirm, via a fixed-effect regression model, that providers exert significant influence over the latter two factors, which are both related to the software stack in their hosting environment. Finally, by means of GLM regression analysis of these factors on phishing and malware abuse, we show that the four security and software patching factors explain between 10\% and 19\% of the variance in abuse at providers, after controlling for size. For web-application security for instance, we found that when a provider moves from the bottom 10\% to the best-performing 10\%, it would experience 4 times fewer phishing incidents. We show that providers have influence over patch levels--even higher in the stack, where CMSes can run as client-side software--and that this influence is tied to a substantial reduction in abuse levels

Scripting the crime commission process in the illicit online prescription drug trade

This paper considers the processes in the illicit online prescription drug trade, namely search-redirection attacks and the operation of unlicensed pharmacies using crime script analysis. Empirical data have been used to describe the salient elements of the online criminal infrastructures and associated monetization paths enabling criminal profitability. This analysis reveals the existence of structural chokepoints: components of online criminal operations being limited in number, and critical for the operations’ profitability. Consequently, interventions targeting such components can reduce the opportunities and incentives to engage in online crime through an increase in criminal operational costs, and in the risk of apprehension.This work was supported by the Department of Homeland Security (DHS) Science and Technology Directorate, Cyber Security Division (DHSS&T/CSD) Broad Agency Announcement 11.02; the Government of Australia; and SPAWAR Systems Center Pacific [contract number N66001-13-C-0131]. The opinions, findings, and conclusions or recommendations expressed are those of the authors and do not reflect those of the aforementioned agencies.This is the final version of the article. It first appeared from Oxford University Press via http://dx.doi.org/10.1093/cybsec/tyv00

Adversarial behaviours knowledge area

The technological advancements witnessed by our society in recent decades have brought improvements in our quality of life, but they have also created a number of opportunities for attackers to cause harm. Before the Internet revolution, most crime and malicious activity generally required a victim and a perpetrator to come into physical contact, and this limited the reach that malicious parties had. Technology has removed the need for physical contact to perform many types of crime, and now attackers can reach victims anywhere in the world, as long as they are connected to the Internet. This has revolutionised the characteristics of crime and warfare, allowing operations that would not have been possible before. In this document, we provide an overview of the malicious operations that are happening on the Internet today. We first provide a taxonomy of malicious activities based on the attacker’s motivations and capabilities, and then move on to the technological and human elements that adversaries require to run a successful operation. We then discuss a number of frameworks that have been proposed to model malicious operations. Since adversarial behaviours are not a purely technical topic, we draw from research in a number of fields (computer science, criminology, war studies). While doing this, we discuss how these frameworks can be used by researchers and practitioners to develop effective mitigations against malicious online operations.Published versio

Experimental Case Studies for Investigating E-Banking Phishing Techniques and Attack Strategies

Phishing is a form of electronic identity theft in which a combination of social engineering and web site spoofing techniques are used to trick a user into revealing confidential information with economic value. The problem of social engineering attack is that there is no single solution to eliminate it completely, since it deals largely with the human factor. This is why implementing empirical experiments is very crucial in order to study and to analyze all malicious and deceiving phishing website attack techniques and strategies. In this paper, three different kinds of phishing experiment case studies have been conducted to shed some light into social engineering attacks, such as phone phishing and phishing website attacks for designing effective countermeasures and analyzing the efficiency of performing security awareness about phishing threats. Results and reactions to our experiments show the importance of conducting phishing training awareness for all users and doubling our efforts in developing phishing prevention techniques. Results also suggest that traditional standard security phishing factor indicators are not always effective for detecting phishing websites, and alternative intelligent phishing detection approaches are needed

Adaptive Traffic Fingerprinting for Darknet Threat Intelligence

Darknet technology such as Tor has been used by various threat actors for organising illegal activities and data exfiltration. As such, there is a case for organisations to block such traffic, or to try and identify when it is used and for what purposes. However, anonymity in cyberspace has always been a domain of conflicting interests. While it gives enough power to nefarious actors to masquerade their illegal activities, it is also the cornerstone to facilitate freedom of speech and privacy. We present a proof of concept for a novel algorithm that could form the fundamental pillar of a darknet-capable Cyber Threat Intelligence platform. The solution can reduce anonymity of users of Tor, and considers the existing visibility of network traffic before optionally initiating targeted or widespread BGP interception. In combination with server HTTP response manipulation, the algorithm attempts to reduce the candidate data set to eliminate client-side traffic that is most unlikely to be responsible for server-side connections of interest. Our test results show that MITM manipulated server responses lead to expected changes received by the Tor client. Using simulation data generated by shadow, we show that the detection scheme is effective with false positive rate of 0.001, while sensitivity detecting non-targets was 0.016+-0.127. Our algorithm could assist collaborating organisations willing to share their threat intelligence or cooperate during investigations.Comment: 26 page

Standing out among the daily spam: How to catch website owners\u27 attention by means of vulnerability notifications

Running a business without having a website is nearly impossible nowadays. Most business owners use content managements sys- tems to manage their websites. Yet, those can pose security risks and provide vulnerabilities for manipulations. With vulnerability notifications, website owners are notified about security risks. To identify common themes with respect to vulnerability notifications and provide deeper insight into the motivations of website owners to react to those notifications, we conducted 25 semi-structured interviews. In compliance with previous research, we could confirm that distrust in unexpected notifications is high and, in contrast to previous research, we suggest that verification possibilities are the most important factors to establish trust in notifications. We also endorse the findings that raising awareness for the severity and the complexity of the problems is crucial to increase remediation rates

Master of sheets: A tale of compromised cloud documents

As of 2014, a fifth of EU citizens relied on cloud accounts to store their documents according to a Eurostat report. Although useful, there are downsides to the use of cloud documents. They often accumulate sensitive information over time, including financial information. This makes them attractive targets to cybercriminals. To understand what happens to compromised cloud documents that contain financial information, we set up 100 fake payroll sheets comprising 1000 fake records of fictional individuals. We populated the sheets with traditional bank payment information, cryptocurrency details, and payment URLs. To lure cybercriminals and other visitors into visiting the sheets, we leaked links pointing to the sheets via paste sites. We collected data from the sheets for a month, during which we observed 235 accesses across 98 sheets. Two sheets were not opened. We also recorded 38 modifications in 7 sheets. We present detailed measurements and analysis of accesses, modifications, edits, and devices that visited payment URLs in the sheets. Contrary to our expectations, bank payment URLs received many more clicks than cryptocurrency payment URLs despite the popularity of cryptocurrencies and emerging blockchain technologies. On the other hand, sheets that contained cryptocurrency details recorded more modifications than sheets that contained traditional banking information. In summary, we present a comprehensive picture of what happens to compromised cloud spreadsheets.Accepted manuscrip

A Macroscopic Study of Network Security Threats at the Organizational Level.

Defenders of today's network are confronted with a large number of malicious activities such as spam, malware, and denial-of-service attacks. Although many studies have been performed on how to mitigate security threats, the interaction between attackers and defenders is like a game of Whac-a-Mole, in which the security community is chasing after attackers rather than helping defenders to build systematic defensive solutions. As a complement to these studies that focus on attackers or end hosts, this thesis studies security threats from the perspective of the organization, the central authority that manages and defends a group of end hosts. This perspective provides a balanced position to understand security problems and to deploy and evaluate defensive solutions. This thesis explores how a macroscopic view of network security from an organization's perspective can be formed to help measure, understand, and mitigate security threats. To realize this goal, we bring together a broad collection of reputation blacklists. We first measure the properties of the malicious sources identified by these blacklists and their impact on an organization. We then aggregate the malicious sources to Internet organizations and characterize the maliciousness of organizations and their evolution over a period of two and half years. Next, we aim to understand the cause of different maliciousness levels in different organizations. By examining the relationship between eight security mismanagement symptoms and the maliciousness of organizations, we find a strong positive correlation between mismanagement and maliciousness. Lastly, motivated by the observation that there are organizations that have a significant fraction of their IP addresses involved in malicious activities, we evaluate the tradeoff of one type of mitigation solution at the organization level --- network takedowns.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116714/1/jingzj_1.pd