Node forgery or impersonation, in which legitimate cryptographic credentials are captured by an adversary, constitutes one major security threat facing wireless networks. The fact that mobile devices are prone to be compromised and reverse engineered significantly increases the risk of such attacks in which adversaries can obtain secret keys on trusted nodes and impersonate the legitimate node. One promising approach toward thwarting these attacks is through the extraction of unique fingerprints that can provide a reliable and robust means for device identification. These fingerprints can be extracted from transmitted signal by analyzing information across the protocol stack. In this paper, the first unified and comprehensive tutorial in the area of wireless device fingerprinting for security applications is presented.In particular, we aim to provide a detailed treatment on developing novel wireless security solutions using device fingerprinting techniques. The objectives are three-fold: (i) to introduce a comprehensive taxonomy of wireless features that can be used in fingerprinting, (ii) to provide a systematic review on fingerprint algorithms including both white-list based and unsupervised learning approaches, and (iii) to identify key open research problems in the area of device fingerprinting and feature extraction, as applied to wireless security.
More than one million prostate biopsies are performed in the United States every year. A failure to find cancer is not definitive in a significant percentage of patients due to the presence of equivocal structures or continuing clinical suspicion. We have identified gene expression changes in stroma that can detect tumor nearby. We compared gene expression profiles of 13 biopsies containing stroma near tumor and 15 biopsies from volunteers without prostate cancer. About 3,800 significant expression changes were found and thereafter filtered using independent expression profiles to eliminate possible age-related genes and genes expressed at detectable levels in tumor cells. A stroma-specific classifier for nearby tumor was constructed on the basis of 114 candidate genes and tested on 364 independent samples including 243 tumor-bearing samples and 121 nontumor samples (normal biopsies, normal autopsies, remote stroma, as well as stroma within a few millimeters of tumor). The classifier predicted the tumor status of patients using tumor-free samples with an average accuracy of 97% (sensitivity ¼ 98% and specificity ¼ 88%) whereas classifiers trained with sets of 100 randomly generated genes had no diagnostic value. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for categorizing the presence of tumor in patients when a prostate sample is derived from near the tumor but does not contain any recognizable tumor. Cancer Res; 71(7); 2476-87. Ó2011 AACR.
The use of cellular data networks is increasingly popular as network coverage becomes more ubiquitous and many diverse usercontributed mobile applications become available. The growing cellular traffic demand means that cellular network carriers are facing greater challenges to provide users with good network performance and energy efficiency, while protecting networks from potential attacks. To better utilize their limited network resources while securing the network and protecting client devices the carriers have already deployed various network policies that influence traffic behavior. Today, these policies are mostly opaque, though they directly impact application designs and may even introduce network vulnerabilities.We present NetPiculet, the first tool that unveils carriers' NAT and firewall policies by conducting intelligent measurement. By running NetPiculet on the major U.S. cellular providers as well as deploying it as a smartphone application in the wild covering more than 100 cellular ISPs, we identified the key NAT and firewall policies which have direct implications on performance, energy, and security. For example, NAT boxes and firewalls set timeouts for idle TCP connections, which sometimes cause significant energy waste on mobile devices. Although most carriers today deploy sophisticated firewalls, they are still vulnerable to various attacks such as battery draining and denial of service. These findings can inform developers in optimizing the interaction between mobile applications and cellular networks and also guide carriers in improving their network configurations.
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