The ability to enforce robust and dynamic access controls on cloud-hosted data while simultaneously ensuring confidentiality with respect to the cloud itself is a clear goal for many users and organizations. To this end, there has been much cryptographic research proposing the use of (hierarchical) identity-based encryption, attribute-based encryption, predicate encryption, functional encryption, and related technologies to perform robust and private access control on untrusted cloud providers. However, the vast majority of this work studies static models in which the access control policies being enforced do not change over time. This is contrary to the needs of most practical applications, which leverage dynamic data and/or policies. In this paper, we show that the cryptographic enforcement of dynamic access controls on untrusted platforms incurs computational costs that are likely prohibitive in practice. Specifically, we develop lightweight constructions for enforcing role-based access controls (i.e., RBAC0) over cloud-hosted files using identity-based and traditional public-key cryptography. This is done under a threat model as close as possible to the one assumed in the cryptographic literature. We prove the correctness of these constructions, and leverage real-world RBAC datasets and recent techniques developed by the access control community to experimentally analyze, via simulation, their associated computational costs. This analysis shows that supporting revocation, file updates, and other state change functionality is likely to incur prohibitive overheads in even minimally-dynamic, realistic scenarios. We identify a number of bottlenecks in such systems, and fruitful areas for future work that will lead to more natural and efficient constructions for the cryptographic enforcement of dynamic access controls. Our findings naturally extend to the use of more expressive cryptographic primitives (e.g., HIBE or ABE) and richer access control models (e.g., RBAC1 or ABAC).

ABSTRACT Web spammers have taken note of the popularity of public forums such as blogs, wikis, webboards, and guestbooks. They are now exploiting them with the purpose of driving traffic to their malicious or fraudulent websites, such as those used for phishing, distributing malware, or selling counterfeit pharmaceuticals. A popular technique they use is to spam these forums with URLs to their spam websites. We consider the problem of classifying URLs posted to forums as spam or legitimate by considering the link structure of the graph rooted at the posted URL. We investigate various graph metrics and associated metadata to analyze link structures. To lessen noisy structural characteristics of the link graphs for spam classification, we also examine two techniques: differing depths and aggregating sub‐graphs of the link graphs. Our results show that a support vector machine classifier based on combinations of graph metrics and metadata of link graphs can achieve a pragmatically high performance in forum spam detection. Copyright © 2014 John Wiley & Sons, Ltd.

The notion of emergent properties is becoming common place in the physical and social sciences, with applications in physics, chemistry, biology, medicine, economics, and sociology. Unfortunately, little attention has been given to the discussion of emergence in the realm of computer security, from either the attack or defense perspectives, despite there being examples of such attacks and defenses. We review the concept of emergence, discuss it in the context of computer security, argue that understanding such concepts is essential for securing our current and future systems, give examples of current attacks and defenses that make use of such concepts, and discuss the tools currently available to understand this field. We conclude by arguing that more focus needs to be given to the emergent perspective in information security, especially as we move forward to the Internet of Things and a world full of cyber-physical systems, as we believe many future attacks will make use of such ideas and defenses will require such insights.

A secure ad-hoc survey scheme enables a survey authority to independently (without any interaction) select an ad-hoc group of registered users based only on their identities (e.g., their email addresses), and create a survey where only selected users can anonymously submit exactly one response. We present a formalization of secure ad-hoc surveys and a provably-secure implementation in the random oracle model, called ANONIZE. Our performance analysis shows that ANONIZE enables securely implementing million-person anonymous surveys using a single modern workstation. As far as we know, ANONIZE constitutes the first implementation of a large-scale secure computation protocol (of non-trivial functionalities) that scales to millions of users.

Recent work demonstrates the feasibility and practical use of secure two-party computation [5, 9, 15, 23]. In this work, we present the first Graphical Processing Unit (GPU)-optimized implementation of an optimized Yao's garbled-circuit protocol for two-party secure computation in the honest-but-curious and 1-bit-leaked malicious models. We implement nearly all of the modern protocol advancements, such as Free-XOR, Pipelining, and OT extension. Our implementation is the first allowing entire circuits to be generated concurrently, and makes use of a modification of the XOR technique so that circuit generation is optimized for implementation on SIMD architectures of GPUs. In our best cases we generate about 75 million gates per second and we exceed the state of the art performance metrics on modern CPU systems by a factor of about 200, and GPU systems by about a factor of 2.3. While many recent works on garbled circuits exploit the embarrassingly parallel nature of many tasks that are part of a secure computation protocol, we show that there are still various forms and levels of parallelization that may yet improve the performance of these protocols. In particular, we highlight that implementations on the SIMD architecture of modern GPUs require significantly different approaches than the general purpose MIMD architecture of multi-core CPUs, which again differ from the needs of parallelizing on compute clusters. Additionally, modifications to the security models for many common protocols have large effects on reasonable parallel architectures for implementation.

We construct a Non-Malleable Chosen Ciphertext Attack (NM-CCA1) encryption scheme from any encryption scheme that is also plaintext aware and weakly simulatable. We believe this is the first construction of a NM-CCA1 scheme that follows strictly from encryption schemes with seemingly weaker or inco mparable security definitions to NM-CCA1. Previously, the statistical Plaintext Awareness #1 (PA1) notion was only known to imply CCA1. Our result is therefore novel because unlike the case of Chosen Plaintext Attack (CPA) and Chosen Chiphertext Attack (CCA2), it is unknown whether a CCA1 scheme can be transformed into an NM-CCA1 scheme. Additionally, we show both the Damgård Elgamal Scheme (DEG) [in: CRYPTO, J. Feigenbaum, ed., Lecture Notes in Computer Science, Vol. 576, Springer, 1991, pp. 445–456] and the Cramer–Shoup Lite Scheme (CS-Lite) [SIAM J. Comput. 33(1) (2003), 167–226] are weakly simulatable under the DDH assumption. Since both are known to be statistical Plaintext Aware 1 (PA1) under the Diffie–Hellman Knowledge (DHK) assumption, they instantiate our scheme securely. Furthermore, in response to a question posed by Matsuda and Matsuura [in: Public Key Cryptography, D. Catalano, N. Fazio, R. Gennaro and A. Nicolosi, eds, Lecture Notes in Computer Science, Vol. 6571, Springer, 2011, pp. 246–264], we define cNM-CCA1-security in which an NM-CCA1-adversary is permitted to ask a c≥1 number of parallel queries after receiving the challenge ciphertext. We extend our construction to yield a cNM-CCA1 scheme for any constant c. All of our constructions are black-box.

Forums on the Web are increasingly spammed by miscreants in order to attract visitors to their (often malicious) websites. In this paper, we study the prevalence of forum spamming and find that Internet users are at a high risk of encountering forums with spam links posted on them. To mitigate the problem, we examine the characteristics of 286 days of forum spam posted at a research blog and develop light-weight features based on spammers' IP, commenting activity and the anatomy of their posts. We find that an SVM classifier trained on these features can achieve a 99.81% precision and 92.82% recall in identifying forum spam.

Digital wireless radios broadcast identification numbers that uniquely identify them. As has been previously observed, given the ubiquity with which people carry smartphones with their embedded WiFi radios powered on, comes the ability to track individuals' movements. The ability to use wireless radios for positioning has been previously observed and developed in to useful products. In these systems a user willingly geolocates themselves by providing identifiers to infrastructure hardware. In this paper we consider the converse question: what rates of monitoring by smartphones devices in a given metropolitan area are necessary to achieve different levels of involuntary geolocation. While previous work has looked at countermeasure that attempt to maintain privacy, no work has attempted to quantify the problem and risks. Using appropriate simulations we give the first quantitative support for the number and conditions of tracking devices necessary to track the locations of non-participant individuals in urban environments. We provide evidence that a small, but not insignificant, number of mobile devices can be used to track a majority of users during a significant fraction of their travel with current devices. We conclude that in the immediate future, malnets would require relatively high infection rates to pose a significant threat, but that voluntary networks, with perceived benefit can probably achieve the usage rates necessary to track individual movements of non-subscribed users to a high-degree of accuracy. Our results also suggest ubiquitous deployment of 802.11n in smartphones would make geolocation feasible by malnets

MOTIVATION: Enzyme catalysis is involved in numerous biological processes and the disruption of enzymatic activity has been implicated in human disease. Despite this, various aspects of catalytic reactions are not completely understood, such as the mechanics of reaction chemistry and the geometry of catalytic residues within active sites. As a result, the computational prediction of catalytic residues has the potential to identify novel catalytic pockets, aid in the design of more efficient enzymes and also predict the molecular basis of disease. RESULTS: We propose a new kernel-based algorithm for the prediction of catalytic residues based on protein sequence, structure and evolutionary information. The method relies upon explicit modeling of similarity between residue-centered neighborhoods in protein structures. We present evidence that this algorithm evaluates favorably against established approaches, and also provides insights into the relative importance of the geometry, physicochemical properties and evolutionary conservation of catalytic residue activity. The new algorithm was used to identify known mutations associated with inherited disease whose molecular mechanism might be predicted to operate specifically though the loss or gain of catalytic residues. It should, therefore, provide a viable approach to identifying the molecular basis of disease in which the loss or gain of function is not caused solely by the disruption of protein stability. Our analysis suggests that both mechanisms are actively involved in human inherited disease. AVAILABILITY AND IMPLEMENTATION: Source code for the structural kernel is available at www.informatics.indiana.edu/predrag/.

Enzyme catalysis is involved in numerous biological processes and the disruption of enzymatic activity has been implicated in human disease. Despite the functional importance, various aspects of catalytic reactions are not completely understood, such as the mechanics of reaction chemistry and the geometry of catalytic residues within active sites. As a result, the computational prediction of catalytic residues has the potential to identify novel catalytic pockets, aid in the design of more efficient enzymes and also predict the molecular basis of disease. We proposed a new kernel-based algorithm for the prediction of catalytic residues and functional sites in general in protein structures [ 1 ]. The method relies upon explicit modelling of similarity between residue-centred neighbourhoods in protein structures. Specifically, we start with a construction of oriented structural neighbourhoods followed by separating the neighbourhood volume into small cells. The similarities between two structural neighbourhoods are accumulation of their similarity in each cell. The kernel function is a product of three kernels, each addressing a separate aspect of protein function: (i) the geometric kernel addresses the shape similarity, (ii) the chemical kernel addresses the similarity in physicochemical properties, and (iii) the evolutionary kernel addresses the evolutionary similarity of conservation patterns for the residues in two structural neighbourhoods. Our approach was favourably evaluated against two of the leading alternative approaches, FEATURE [ 2 ] and GBT [ 3 ], as shown in Table 1 . The new algorithm was used to identify known mutations associated with inherited disease whose molecular mechanism might be predicted to operate specifically though the loss or gain of catalytic residues. It should therefore provide a viable approach in identifying the molecular basis of disease in which the loss or gain of function is not caused solely by the disruption of protein stability. Our analysis suggests that both loss and gain of catalytic residues are actively involved in human inherited disease. Our kernel method for functional sites prediction based on protein structures evaluates favourably against established methods on the same data set using the same evaluation procedure. The results from applying our catalytic residue predictor to disease mutations indicated that both loss and gain of catalytic residues are actively involved in human inherited disease.

Under CPA and CCA1 attacks, a secure bit encryption scheme can be applied bit-by-bit to construct a secure many-bit encryption scheme. The same construction fails, however, under a CCA2 attack. In fact, since the notion of CCA2 security was introduced by Rackoff and Simon [21], it has been an open question to determine whether single bit CCA2 secure encryption implies the existence of many-bit CCA2 security. We positively resolve this long-standing question and establish that bit encryption is complete for CPA, CCA1, and CCA2 notions. Our construction is black-box, and thus requires novel techniques to avoid known impossibility results concerning trapdoor predicates [10]. To the best of our knowledge, our work is also the first example of a non-shielding reduction (introduced in [9]) in the standard (i.e., not random-oracle) model.

Abstract — Internet Protocol Security (IPSec) is a widely deployed mechanism for implementing Virtual Private Networks (VPNs). In previous work, we examined the overheads incurred by an IPSec server in a single client setting. In this paper, we extend that work by examining the scaling of a VPN server in a multiple client environment and by evaluating the effectiveness of connection credential caching. Motivated by the potential benefits of caching, we also propose a cryptographically secure cache resumption protocol for IPSec connections to reduce the connection establishment overheads. I.