Biblio

An authenticated data structure (ADS) is a data structure whose operations can be carried out by an untrusted prover, the results of which a verifier can efficiently check as authentic. This is done by having the prover produce a compact proof that the verifier can check along with each operation's result. ADSs thus support outsourcing data maintenance and processing tasks to untrusted servers without loss of integrity. Past work on ADSs has focused on particular data structures (or limited classes of data structures), one at a time, often with support only for particular operations.

This paper presents a generic method, using a simple extension to a ML-like functional programming language we call λ• (lambda-auth), with which one can program authenticated operations over any data structure defined by standard type constructors, including recursive types, sums, and products. The programmer writes the data structure largely as usual and it is compiled to code to be run by the prover and verifier. Using a formalization of λ• we prove that all well-typed λ• programs result in code that is secure under the standard cryptographic assumption of collision-resistant hash functions. We have implemented λ• as an extension to the OCaml compiler, and have used it to produce authenticated versions of many interesting data structures including binary search trees, red-black+ trees, skip lists, and more. Performance experiments show that our approach is efficient, giving up little compared to the hand-optimized data structures developed previously.

Cloud storage has rapidly acquired popularity among users, constituting a seamless solution for the backup, synchronization, and sharing of large amounts of data. This technology, however, puts user data in the direct control of cloud service providers, which raises increasing security and privacy concerns related to the integrity of outsourced data, the accidental or intentional leakage of sensitive information, the profiling of user activities and so on. We present GORAM, a cryptographic system that protects the secrecy and integrity of the data outsourced to an untrusted server and guarantees the anonymity and unlinkability of consecutive accesses to such data. GORAM allows the database owner to share outsourced data with other clients, selectively granting them read and write permissions. GORAM is the first system to achieve such a wide range of security and privacy properties for outsourced storage. Technically, GORAM builds on a combination of ORAM to conceal data accesses, attribute-based encryption to rule the access to outsourced data, and zero-knowledge proofs to prove read and write permissions in a privacy-preserving manner. We implemented GORAM and conducted an experimental evaluation to demonstrate its feasibility.

In his book Outliers, Malcom Gladwell describes the 10,000-Hour Rule, a key to success in any field, as simply a matter of practicing a specific task that can be accomplished with 20 hours of work a week for 10 years [10]. Ongoing changes in technology and national security needs require aspiring excellent cybersecurity professionals to set a goal of 10,000 hours of relevant, hands-on skill development. The education system today is ill prepared to meet the challenge of producing an adequate number of cybersecurity professionals, but programs that use competitions and learning environments that teach depth are filling this void.

This work reports an efficient and compact FPGA processor for the SHA-256 algorithm. The novel processor architecture is based on a custom datapath that exploits the reusing of modules, having as main component a 4-input Arithmetic-Logic Unit not previously reported. This ALU is designed as a result of studying the type of operations in the SHA algorithm, their execution sequence and the associated dataflow. The processor hardware architecture was modeled in VHDL and implemented in FPGAs. The results obtained from the implementation in a Virtex5 device demonstrate that the proposed design uses fewer resources achieving higher performance and efficiency, outperforming previous approaches in the literature focused on compact designs, saving around 60% FPGA slices with an increased throughput (Mbps) and efficiency (Mbps/Slice). The proposed SHA processor is well suited for applications like Wi-Fi, TMP (Trusted Mobile Platform), and MTM (Mobile Trusted Module), where the data transfer speed is around 50 Mbps.

To find security vulnerabilities, many research approaches and commercial tools use a static analysis and check constraints. Previous work compared using a benchmark several approaches where the static analysis and constraints are combined, and the evaluation focused on corner cases in the Java language. We extend the comparative evaluation of these approaches to include one approach that separates the constraints from the static analysis. We also extend the benchmark to cover more classes of security vulnerabilities. Approaches that combine the static analysis and constraints work well for vulnerabilities that are sensitive to the order in which statements are executed. The additional effort required to write separate constraints is rewarded by better recall in dealing with dataflow communication and better precision for callback methods that are common in applications built on frameworks such as Android. 

Static types may be used both by the language implementation and directly by the user as documentation. Though much existing work focuses primarily on the implications of static types on the semantics of programs, relatively little work considers the impact on usability that static types pro- vide. Though the omission of static type information may decrease program length and thereby improve readability, it may also decrease readability because users must then frequently derive type information manually while reading programs. As type inference becomes more popular in languages that are in widespread use, it is important to consider whether the adoption of type inference may impact productivity of developers.

Session management in distributed Internet services is traditionally based on username and password, explicit logouts and mechanisms of user session expiration using classic timeouts. Emerging biometric solutions allow substituting username and password with biometric data during session establishment, but in such an approach still a single verification is deemed sufficient, and the identity of a user is considered immutable during the entire session. Additionally, the length of the session timeout may impact on the usability of the service and consequent client satisfaction. This paper explores promising alternatives offered by applying biometrics in the management of sessions. A secure protocol is defined for perpetual authentication through continuous user verification. The protocol determines adaptive timeouts based on the quality, frequency and type of biometric data transparently acquired from the user. The functional behavior of the protocol is illustrated through Matlab simulations, while model-based quantitative analysis is carried out to assess the ability of the protocol to contrast security attacks exercised by different kinds of attackers. Finally, the current prototype for PCs and Android smartphones is discussed.
 

Trust and reputation techniques have offered favorable solutions to the web service selection problem. In distributed systems, service consumers identify pools of service providers that offer similar functionalities. Therefore, the selection task is mostly influenced by the non-functional requirements of the consumers captured by a varied number of QoS metrics. In this paper, we present a QoS-aware trust model that leverages the correlation information among various QoS metrics. We compute the trustworthiness of web services based on probability theory by exploiting two statistical distributions, namely, Dirichlet and generalized Dirichlet, which represent the distributions of the outcomes of multi-dimensional correlated QoS metrics. We employ the Dirichlet and generalized Dirichlet when the QoS metrics are positively or negatively correlated, respectively. Experimental results endorse the advantageous capability of our model in capturing the correlation among QoS metrics and estimating the trustworthiness and reputation of service providers.

This paper documents and discusses the design of a low-cost Flapping-Wing Micro Air Vehicle (FW-MAV) designed to be easy to fabricate using readily available materials and equipment. Basic theory of operation as well as the rationale underlying various design decisions will be provided. Using this paper, it should be possible for readers to construct their own devices quickly and at little expense.

Detecting and preventing attacks before they compromise a system can be done using acceptance testing, redundancy based mechanisms, and using external consistency checking such external monitoring and watchdog processes. Diversity-based adjudication, is a step towards an oracle that uses knowable behavior of a healthy system. That approach, under best circumstances, is able to detect even zero-day attacks. In this approach we use functionally equivalent but in some way diverse components and we compare their output vectors and reactions for a given input vector. This paper discusses practical relevance of this approach in the context

Cloud federation is a future evolution of Cloud computing, where Cloud Service Providers (CSP) collaborate dynamically to share their virtual infrastructure for load balancing and meeting the Quality of Service during the demand spikes. Today, one of the major obstacles in adoption of federation is the lack of trust between Cloud providers participating in federation. In order to ensure the security of critical and sensitive data of customers, it is important to evaluate and establish the trust between Cloud providers, before redirecting the customer's requests from one provider to other provider. We are proposing a trust evaluation model and underlying protocol that will facilitate the cloud providers to evaluate the trustworthiness of each other and hence participate in federation to share their infrastructure in a trusted and reliable way.

Proliferation of Android devices and apps has created a demand for applicable automated software testing techniques. Prior research has primarily focused on either unit or GUI testing of Android apps, but not their end-to-end system testing in a systematic manner. We present EvoDroid, an evolutionary approach for system testing of Android apps. EvoDroid overcomes a key shortcoming of using evolutionary techniques for system testing, i.e., the inability to pass on genetic makeup of good individuals in the search. To that end, EvoDroid combines two novel techniques: (1) an Android-specific program analysis technique that identifies the segments of the code amenable to be searched independently, and (2) an evolutionary algorithm that given information of such segments performs a step-wise search for test cases reaching deep into the code. Our experiments have corroborated EvoDroid’s ability to achieve significantly higher code coverage than existing Android testing tools.

The success of machine learning, particularly in supervised settings, has led to numerous attempts to apply it in adversarial settings such as spam and malware detection. The core challenge in this class of applications is that adversaries are not static data generators, but make a deliberate effort to evade the classifiers deployed to detect them. We investigate both the problem of modeling the objectives of such adversaries, as well as the algorithmic problem of accounting for rational, objective-driven adversaries. In particular, we demonstrate severe shortcomings of feature reduction in adversarial settings using several natural adversarial objective functions, an observation that is particularly pronounced when the adversary is able to substitute across similar features (for example, replace words with synonyms or replace letters in words). We offer a simple heuristic method for making learning more robust to feature cross-substitution attacks. We then present a more general approach based on mixed-integer linear programming with constraint generation, which implicitly trades off overfitting and feature selection in an adversarial setting using a sparse regularizer along with an evasion model. Our approach is the first method for combining an adversarial classification algorithm with a very general class of models of adversarial classifier evasion. We show that our algorithmic approach significantly outperforms state-of-the-art alternatives.

In previous work, the viability of split-cycle constant-period frequency modulation for controlling two degrees of freedom of flapping wing micro air vehicle has been demonstrated. Though the proposed wing control system was made compact and self-sufficient to be deployed on the vehicle, it was not built for on-the-fly configurability of all the split-cycle control's parameters. Further the system had limited external communication capabilities that rendered it inappropriate for its integration into a higher level research framework to analyze and validate motion controllers in flapping vehicles. In this paper, an improved control system has been proposed that could addresses the on-the-fly configurability issue and provide an improved external communication capabilities, hence the wing control system could be seamlessly integrated in a research framework for analyzing and validating motion controllers for flapping wing vehicles.

Sandboxes impose a security policy, isolating applications and their components from the rest of a system. While many sandboxing techniques exist, state of the art sandboxes generally perform their functions within the system that is being defended. As a result, when the sandbox fails or is bypassed, the security of the surrounding system can no longer be assured. We experiment with the idea of in-nimbo sandboxing, encapsulating untrusted computations away from the system we are trying to protect. The idea is to delegate computations that may be vulnerable or malicious to virtual machine instances in a cloud computing environment. This may not reduce the possibility of an in-situ sandbox compromise, but it could significantly reduce the consequences should that possibility be realized. To achieve this advantage, there are additional requirements, including: (1) A regulated channel between the local and cloud environments that supports interaction with the encapsulated application, (2) Performance design that acceptably minimizes latencies in excess of the in-situ baseline. To test the feasibility of the idea, we built an in-nimbo sandbox for Adobe Reader, an application that historically has been subject to significant attacks. We undertook a prototype deployment with PDF users in a large aerospace firm. In addition to thwarting several examples of existing PDF-based malware, we found that the added increment of latency, perhaps surprisingly, does not overly impair the user experience with respect to performance or usability.