As miscreants routinely hijack thousands of vulnerable web servers weekly for cheap hosting and traffic acquisition, security services have turned to notifications both to alert webmasters of ongoing incidents as well as to expedite recovery. In this work we present the first large-scale measurement study on the effectiveness of combinations of browser, search, and direct webmaster notifications at reducing the duration a site remains compromised. Our study captures the life cycle of 760,935 hijacking incidents from July, 2014--June, 2015, as identified by Google Safe Browsing and Search Quality. We observe that direct communication with webmasters increases the likelihood of cleanup by over 50% and reduces infection lengths by at least 62%. Absent this open channel for communication, we find browser interstitials---while intended to alert visitors to potentially harmful content---correlate with faster remediation. As part of our study, we also explore whether webmasters exhibit the necessary technical expertise to address hijacking incidents. Based on appeal logs where webmasters alert Google that their site is no longer compromised, we find 80% of operators successfully clean up symptoms on their first appeal. However, a sizeable fraction of site owners do not address the root cause of compromise, with over 12% of sites falling victim to a new attack within 30 days. We distill these findings into a set of recommendations for improving web security and best practices for webmasters.

We investigate the emergence of the exploit-as-a-service model for driveby browser compromise. In this regime, attackers pay for an exploit kit or service to do the "dirty work" of exploiting a victim's browser, decoupling the complexities of browser and plugin vulnerabilities from the challenges of generating traffic to a website under the attacker's control. Upon a successful exploit, these kits load and execute a binary provided by the attacker, effectively transferring control of a victim's machine to the attacker.

Although Voice over IP (VoIP) is rapidly being adopted, its security implications are not yet fully understood. Since VoIP calls may traverse untrusted networks, packets should be encrypted to ensure confidentiality. However, we show that it is possible toidentify the phrases spoken within encrypted VoIP callswhen the audio is encoded using variable bit rate codecs. To do so, we train a hidden Markov model using only knowledge of the phonetic pronunciations of words, such as those provided by a dictionary, and search packet sequences for instances of specified phrases. Our approach does not require examples of the speaker’s voice, or even example recordings of the words that make up the target phrase. We evaluate our techniques on a standard speech recognition corpus containing over 2,000 phonetically rich phrases spoken by 630 distinct speakers from across the continental United States. Our results indicate that we can identify phrases within encrypted calls with an average accuracy of 50%, and with accuracy greater than 90% for some phrases. Clearly, such an attack calls into question the efficacy of current VoIP encryption standards. In addition, we examine the impact of various features of the underlying audio on our performance and discuss methods for mitigation.

Although biometrics have garnered significant interest as a source of entropy for cryptographic key generation, recent studies indicate that many biometric modalities may not actually offer enough uncertainty for this purpose. In this paper, we exploit a novel source of entropy that can be used with any biometric modality but that has yet to be utilized for key generation, namely associating uncertainty with the way in which the biometric input is measured. Our construction poses only a modest requirement on a user: the ability to remember a low-entropy password. We identify the technical challenges of this approach, and develop novel techniques to overcome these difficulties. Our analysis of this approach indicates that it may offer the potential to generate stronger keys: In our experiments, 40% of the users are able to generate keys that are at least 230 times stronger than passwords alone.

Despite the rapid adoption of Voice over IP (VoIP), its security implications are not yet fully understood. Since VoIP calls may traverse untrusted networks, packets should be encrypted to ensure confidentiality. However, we show that when the audio is encoded using variable bit rate codecs, the lengths of encrypted VoIP packets can be used to identify the phrases spoken within a call. Our results indicate that a passive observer can identify phrases from a standard speech corpus within encrypted calls with an average accuracy of 50%, and with accuracy greater than 90% for some phrases. Clearly, such an attack calls into question the efficacy of current VoIP encryption standards. In addition, we examine the impact of various features of the underlying audio on our performance and discuss methods for mitigation.

Biometric security is a topic of rapidly growing importance in the areas of user authentication and cryptographic key generation. In this paper, we describe our steps toward developing evaluation methodologies for behavioral biometrics that take into account threat models that have been largely ignored. We argue that the pervasive assumption that forgers are minimally motivated (or, even worse, naive) is too optimistic and even dangerous. Taking handwriting as a case in point, we show through a series of experiments that some users are significantly better forgers than others, that such forgers can be trained in a relatively straightforward fashion to pose an even greater threat, that certain users are easy targets for forgers, and that most humans are a relatively poor judge of handwriting authenticity, and hence, their unaided instincts cannot be trusted. Additionally, to overcome current labor-intensive hurdles in performing more accurate assessments of system security, we present a generative attack model based on concatenative synthesis that can provide a rapid indication of the security afforded by the system. We show that our generative attacks match or exceed the effectiveness of forgeries rendered by the skilled humans we have encountered.