12292877
Weighted Pushdown Systems and Trust-Management Systems
The authorization problem is to decide whether, according to a security policy, some principal should be allowed access to a resource. In the trust-management system SPKI/SDSI, the security policy is given by a set of certificates, and proofs of authorization take the form of certificate chains. The certificate-chain-discovery problem is to discover a proof of authorization for a given request. Certificate-chain-discovery algorithms for SPKI/SDSI have been investigated by several researchers. We consider a variant of the certificate-chain discovery problem where the certificates are distributed over a number of servers, which then have to cooperate to identify the proof of authorization for a given request. We propose two protocols for this purpose. These protocols are based on distributed model-checking algorithms for weighted pushdown systems (WPDSs). These protocols can also handle cases where certificates are labeled with weights and where multiple certificate chains must be combined to form a proof of authorization. We have implemented these protocols in a prototype and report preliminary results of our evaluation.
11355624
Theory and Techniques for Automatic Generation of Vulnerability-Based Signatures
In this paper, we explore the problem of creating \emph{vulnerability signatures}. A vulnerability signature is based on a program vulnerability, and is not specific to any particular exploit. The advantage of vulnerability signatures is that their quality can be guaranteed. In particular, we create vulnerability signatures which are guaranteed to have zero false positives. We show how to automate signature creation for any vulnerability that can be detected by a runtime monitor. We provide a formal definition of a vulnerability signature, and investigate the computational complexity of creating and matching vulnerability signatures. We systematically explore the design space of vulnerability signatures. We also provide specific techniques for creating vulnerability signatures in a variety of language classes. In order to demonstrate our techniques, we have built a prototype system. Our experiments show that we can, using a single exploit, automatically generate a vulnerability signature as a regular expression, as a small program, or as a system of constraints. We demonstrate techniques for creating signatures of vulnerabilities which can be exploited via multiple program paths. Our results indicate that our approach is a viable option for signature generation, especially when guarantees are desired.
3839837
Creating Vulnerability Signatures Using Weakest Preconditions
Signature-based tools such as network intrusion detection systems are widely used to protect critical systems. Automatic signature generation techniques are needed to enable these tools due to the speed at which new vulnerabilities are discovered. In particular, we need automatic techniques which generate sound signatures - signatures which will not mistakenly block legitimate traffic or raise false alarms. In addition, we need signatures to have few false negatives and will catch many different exploit variants. We investigate new techniques for automatically generating sound vulnerability signatures with fewer false negatives than previous research using program binary analysis. The key problem to reducing false negatives is to consider as many as possible different program paths an exploit may take. Previous work considered each possible program path an exploit may take separately, thus generating signatures that are exponential in the size of the number of branches considered. In the exact same scenario, we show how to reduce the overall signature size and the generation time from exponential to polynomial. We do this without requiring any additional assumptions, or relaxing any properties. This efficiency gain allows us to consider many more program paths, which results in reducing the false negatives of generated signatures. We achieve these results by creating algorithms for generating vulnerability signatures that are based on computing weakest preconditions (WP). The weakest precondition for a program path to a vulnerability is a function which matches all exploits that may exploit the vulnerability along that path. We have implemented our techniques and generated signatures for several binary programs. Our results demonstrate that our WP-based algorithm generates more succinct signatures than previous approaches which were based on forward symbolic execution.
5961776
NetSpy: Automatic Generation of Spyware Signatures for NIDS
We present NetSpy, a tool to automatically generate network-level signatures for spyware. NetSpy determines whether an untrusted program is spyware by correlating user input with network traffic generated by the untrusted program. If classified as spyware, NetSpy also generates a signature characterizing the malicious substrate of the spyware's network behavior. Such a signature can be used by network intrusion detection systems to detect spyware installations in large networks. In our experiments, NetSpy precisely identified each of the 7 spyware programs that we considered and generated network-level signatures for them. Of the 9 supposedly-benign programs that we considered, NetSpy correctly characterized 6 of them as benign. The remaining 3 programs showed network behavior that was highly suggestive of spying activity
1622406
Structure Analysis and SNR-Variance Evolution for Parallel Concatenated Coded IDMA Systems
This paper is concerned with parallel concatenated coded interleave-division multiple-access (IDMA) systems. We briefly present the transmitter/receiver structure of these systems and propose an efficient SNR-variance evolution scheme for bit-error-rate (BER) performance evaluation. The proposed evolution scheme is also useful for system performance optimization. Numerical results show that the BER performance curves obtained by simulation and evolution are quite close when the data length is long enough.
15500084
Understanding the Prediction of Transmembrane Proteins by Support Vector Machine using Association Rule Mining
With the efforts to understand protein structure, many computational approaches have been made recently. Among them, the support vector machine (SVM) methods have been recently applied and showed successful performance compared with other machine learning schemes. However, despite the high performance, the SVM approaches suffer from the problem of understandability since it is a black-box model. To overcome this limitation, this study attempted to combine the SVM with the association rule based classifier which can present the meaningful explanation about the prediction. To perform this task, a new association rule based classifier (PCPAR) was devised based on the existing classifier, CPAR, to handle the sequential data. PCPAR creates the patterns by merging the generated rules and then classifies the sequential data based on the pattern match. The experimental result presents the following: with sequential data, the PCPAR scheme shows better performance with respect to the accuracy and the number of generated patterns than CPAR method whether applied alone or combined with SVM. The combined scheme of SVMPCPAR generates more compact patterns than the combined scheme of SVM with decision tree, SVM DT, with similar performance. These patterns are easily understandable and biologically meaningful
6306890
APPLE: A Novel P2P Based e-Learning Environment
With the rapid development of information technology, dramatic changes have been taken place in the fundamental ways that people acquire and disseminate knowledge. Various e-Learning systems have been designed to help people take full advantage of the benefit brought by the technology. The newly emerged Peer to Peer (P2P) and grid computing will serve as the key driven forces to bring revolutionary impact on the future society. This paper evaluates the potential contribution of the P2P and grid technology into the e-Learning system and introduces a novel P2P based e-Learning environment, called APPLE. With the help of Gnutella-like P2P network, APPLE provides live broadcasting services to share services of education resources. We build a virtual classroom service based on WSRF.NET, which exposes the service as a grid service that could be accessed by all the users among the grid.
15916460
An approach to security and privacy of RFID system for supply chain
Radio frequency identification (RFID) is expected to become pervasive and ubiquitous, as it can be embedded into everyday items as smart labels. A typical scenario of exploiting RFID is supply chain. The RFID based supply chain management yields convenience, efficiency and productivity gains. However, RFID systems create new risks to security and privacy. We briefly present the current solutions to RFID security and privacy. A new approach is then proposed, which exploits randomized read access control and thus prevents hostile tracking and man-in-the-middle attack. In addition, compared with current schemes that achieve the similar security level, the proposed approach dramatically decreases the computation load. Another benefit is that it is suitable for RFID systems with a large number of tags
9363924
RNA pseudoknot prediction using term rewriting
RNA plays a critical role in mediating every step of cellular information transfer from genes to functional proteins. Pseudoknots are widely occurring structural motifs found in all types of RNA and are also functionally important. Therefore predicting their structures is an important problem. In this paper, we present a new RNA pseudoknot prediction method based on term rewriting rather than on dynamic programming, comparative sequence analysis, or context-free grammars. The method we describe is implemented using the Mfold RNA/DNA folding package and the term rewriting language Maude. Our method was tested on 211 pseudoknots in PseudoBase and achieves an average accuracy of 74.085% compared to the experimentally determined structure. In fact, most pseudoknots discovered by our method achieve an accuracy of above 90%. These results indicate that term rewriting has a broad potential in RNA applications from prediction of pseudoknots to higher level RNA structures involving complex RNA tertiary interactions.