As technologies to defend against phishing and malware often impose an additional financial and usability cost on users (such as security keys), a question remains as to who should adopt these heightened protections. We measure over 1.2 billion email-based phishing and malware attacks against Gmail users to understand what factors place a person at heightened risk of attack. We find that attack campaigns are typically short-lived and at first glance indiscriminately target users on a global scale. However, by modeling the distribution of targeted users, we find that a person's demographics, location, email usage patterns, and security posture all significantly influence the likelihood of attack. Our findings represent a first step towards empirically identifying the most at-risk users.

Cybercriminals have found in online social networks a propitious medium to spread spam and malicious content. Existing techniques for detecting spam include predicting the trustworthiness of accounts and analyzing the content of these messages. However, advanced attackers can still successfully evade these defenses.

In this paper, we present the first longitudinal measurement study of the underground ecosystem fueling credential theft and assess the risk it poses to millions of users. Over the course of March, 2016--March, 2017, we identify 788,000 potential victims of off-the-shelf keyloggers; 12.4 million potential victims of phishing kits; and 1.9 billion usernames and passwords exposed via data breaches and traded on blackmarket forums. Using this dataset, we explore to what degree the stolen passwords---which originate from thousands of online services---enable an attacker to obtain a victim's valid email credentials---and thus complete control of their online identity due to transitive trust. Drawing upon Google as a case study, we find 7--25% of exposed passwords match a victim's Google account. For these accounts, we show how hardening authentication mechanisms to include additional risk signals such as a user's historical geolocations and device profiles helps to mitigate the risk of hijacking. Beyond these risk metrics, we delve into the global reach of the miscreants involved in credential theft and the blackhat tools they rely on. We observe a remarkable lack of external pressure on bad actors, with phishing kit playbooks and keylogger capabilities remaining largely unchanged since the mid-2000s.

Administrators need effective tools to quickly and automatically obtain a succinct, yet informative, overview of the status of their networks to make critical administrative decisions in a timely and effective manner. While the existing tools might help in pointing out machines that are heavily used or services that are failing, more subtle relationships, such as indirect dependencies between services, are not made apparent. In this paper, we propose novel techniques to automatically provide insights into the state of a network and the importance of the network components. We developed a tool, called Paris, which receives traffic information from various off-the-shelf network monitoring devices. Paris computes an importance metric for the network's components based on which the administrators can prioritize their defensive and prohibitive actions. We evaluated Paris by running it on a mid-size, real-world network. The results show that Paris is able to automatically provide situation awareness in a timely, effective manner.

Detecting dependencies among network services has been well-studied in previous research. These attempts at service dependency detection fall into two classes: active and passive approaches. While passive approaches suffer from high false positives, active approaches suffer from applicability problems. In this paper, we design a new application-independent active approach for detecting dependencies among services. We present a traffic watermarking approach with arbitrarily low false positives and easy applicability. We provide statistical tests for detecting watermarked flows, and we compute the false positive and false negative rates of these tests both analytically and experimentally. Furthermore, we implemented the proposed watermarking system (Rippler) in a small university lab network. We ran our system for four months and detected 38 dependencies among 54 services. Finally, we compared the efficiency of our approach against three previous systems by testing them on this real-world network data.

Computer networks are constantly being targeted by different attacks. Since not all attacks are created equal, it is of paramount importance for network administrators to be aware of the status of the network infrastructure, the relevance of each attack with respect to the goals of the organization under attack, and also the most likely next steps of the attackers. In particular, the last capability, attack prediction, is of the most importance and value to the network administrators, as it enables them to provision the required actions to stop the attack and/or minimize its damage to the network's assets. Unfortunately, the existing approaches to attack prediction either provide limited useful information or are too complex to scale to the real-world scenarios.

Live security exercises are a powerful educational tool to motivate students to excel and foster research and development of novel security solutions. Our insight is to design a live security exercise to provide interesting datasets in a specific area of security research. In this paper we validated this insight, and we present the design of a novel kind of live security competition centered on the concept of Cyber Situational Awareness. The competition was carried out in December 2010, and involved 72 teams (900 students) spread across 16 countries, making it the largest educational live security exercise ever performed. We present both the innovative design of this competition and the novel dataset we collected. In addition, we define Cyber Situational Awareness metrics to characterize the toxicity and effectiveness of the attacks performed by the participants with respect to the missions carried out by the targets of the attack.