Automated Website Fingerprinting through Deep Learning

Several studies have shown that the network traffic that is generated by a visit to a website over Tor reveals information specific to the website through the timing and sizes of network packets. By capturing traffic traces between users and their Tor entry guard, a network eavesdropper can leverage this meta-data to reveal which website Tor users are visiting. The success of such attacks heavily depends on the particular set of traffic features that are used to construct the fingerprint. Typically, these features are manually engineered and, as such, any change introduced to the Tor network can render these carefully constructed features ineffective. In this paper, we show that an adversary can automate the feature engineering process, and thus automatically deanonymize Tor traffic by applying our novel method based on deep learning. We collect a dataset comprised of more than three million network traces, which is the largest dataset of web traffic ever used for website fingerprinting, and find that the performance achieved by our deep learning approaches is comparable to known methods which include various research efforts spanning over multiple years. The obtained success rate exceeds 96% for a closed world of 100 websites and 94% for our biggest closed world of 900 classes. In our open world evaluation, the most performant deep learning model is 2% more accurate than the state-of-the-art attack. Furthermore, we show that the implicit features automatically learned by our approach are far more resilient to dynamic changes of web content over time. We conclude that the ability to automatically construct the most relevant traffic features and perform accurate traffic recognition makes our deep learning based approach an efficient, flexible and robust technique for website fingerprinting.Comment: To appear in the 25th Symposium on Network and Distributed System Security (NDSS 2018

Selective inhibition of the p53–MDM2 interaction by nutlin drugs: a new therapeutic perspective for neuroblastoma

Neuroblastoma is one of the most common and most deadly childhood tumors. There is an unmet need to develop new therapeutic modalities for this malignancy that preferentially should be guided by our increasing knowledge of the biology of neuroblastoma. Proliferation and survival of neuroblastoma cells is critically dependent on suppression of the activity of the tumor suppressor protein p53, which is often mediated by increased activity of the MDM2 oncoprotein. Accordingly, small-molecule inhibitors of the interaction between MDM2 and p53 may provide a useful therapeutic option for the treatment of neuroblastoma by restoring the potent antitumor activity of wild-type p53. One of the most promising classes of selective inhibitors of the p53–MDM2 interaction are the nutlins, which have been extensively studied over the last years in several tumor types, including neuroblastoma. We discuss here preclinical data that support the notion that nutlin drugs may offer therapeutic benefit for children with neuroblastoma, on condition that wild-type p53 is present

Herding Vulnerable Cats: A Statistical Approach to Disentangle Joint Responsibility for Web Security in Shared Hosting

Hosting providers play a key role in fighting web compromise, but their ability to prevent abuse is constrained by the security practices of their own customers. {\em Shared} hosting, offers a unique perspective since customers operate under restricted privileges and providers retain more control over configurations. We present the first empirical analysis of the distribution of web security features and software patching practices in shared hosting providers, the influence of providers on these security practices, and their impact on web compromise rates. We construct provider-level features on the global market for shared hosting -- containing 1,259 providers -- by gathering indicators from 442,684 domains. Exploratory factor analysis of 15 indicators identifies four main latent factors that capture security efforts: content security, webmaster security, web infrastructure security and web application security. We confirm, via a fixed-effect regression model, that providers exert significant influence over the latter two factors, which are both related to the software stack in their hosting environment. Finally, by means of GLM regression analysis of these factors on phishing and malware abuse, we show that the four security and software patching factors explain between 10\% and 19\% of the variance in abuse at providers, after controlling for size. For web-application security for instance, we found that when a provider moves from the bottom 10\% to the best-performing 10\%, it would experience 4 times fewer phishing incidents. We show that providers have influence over patch levels--even higher in the stack, where CMSes can run as client-side software--and that this influence is tied to a substantial reduction in abuse levels

Proton Radiography With Timepix Based Time Projection Chambers

The development of a proton radiography system to improve the imaging of patients in proton beam therapy is described. The system comprises gridpix based time projection chambers, which are based on the Timepix chip designed by the Medipix collaboration, for tracking the protons. This type of detector was chosen to have minimal impact on the actual determination of the proton tracks by the tracking detectors. To determine the residual energy of the protons, a BaF2 crystal with a photomultiplier tube is used. We present data taken in a feasibility experiment with phantoms that represent tissue equivalent materials found in the human body. The obtained experimental results show a good agreement with the performed simulations

Dual targeting of MDM2 and BCL2 as a therapeutic strategy in neuroblastoma

Wild-type p53 tumor suppressor activity in neuroblastoma tumors is hampered by increased MDM2 activity, making selective MDM2 antagonists an attractive therapeutic strategy for this childhood malignancy. Since monotherapy in cancer is generally not providing long-lasting clinical responses, we here aimed to identify small molecule drugs that synergize with idasanutlin (RG7388). To this purpose we evaluated 15 targeted drugs in combination with idasanutlin in three p53 wild type neuroblastoma cell lines and identified the BCL2 inhibitor venetoclax (ABT-199) as a promising interaction partner. The venetoclax/idasanutlin combination was consistently found to be highly synergistic in a diverse panel of neuroblastoma cell lines, including cells with high MCL1 expression levels. A more pronounced induction of apoptosis was found to underlie the synergistic interaction, as evidenced by caspase-3/7 and cleaved PARP measurements. Mice carrying orthotopic xenografts of neuroblastoma cells treated with both idasanutlin and venetoclax had drastically lower tumor weights than mice treated with either treatment alone. In conclusion, these data strongly support the further evaluation of dual BCL2/MDM2 targeting as a therapeutic strategy in neuroblastoma

Depletion of tRNA-halves enables effective small RNA sequencing of low-input murine serum samples

The ongoing ascent of sequencing technologies has enabled researchers to gain unprecedented insights into the RNA content of biological samples. MiRNAs, a class of small non-coding RNAs, play a pivotal role in regulating gene expression. The discovery that miRNAs are stably present in circulation has spiked interest in their potential use as minimally-invasive biomarkers. However, sequencing of blood-derived samples ( serum, plasma) is challenging due to the often low RNA concentration, poor RNA quality and the presence of highly abundant RNAs that dominate sequencing libraries. In murine serum for example, the high abundance of tRNA-derived small RNAs called 5' tRNA halves hampers the detection of other small RNAs, like miRNAs. We therefore evaluated two complementary approaches for targeted depletion of 5' tRNA halves in murine serum samples. Using a protocol based on biotinylated DNA probes and streptavidin coated magnetic beads we were able to selectively deplete 95% of the targeted 5' tRNA half molecules. This allowed an unbiased enrichment of the miRNA fraction resulting in a 6-fold increase of mapped miRNA reads and 60% more unique miRNAs detected. Moreover, when comparing miRNA levels in tumor-carrying versus tumor-free mice, we observed a three-fold increase in differentially expressed miRNAs

Genome wide expression profiling of p53 regulated miRNAs in neuroblastoma

Restoration of the antitumor activity of p53 could offer a promising approach for the treatment of neuroblastoma. MicroRNAs (miRNAs) are important mediators of p53 activity, but their role in the p53 response has not yet been comprehensively addressed in neuroblastoma. Therefore, we set out to characterize alterations in miRNA expression that are induced by p53 activation in neuroblastoma cells. Genome-wide miRNA expression analysis showed that miR-34a-5p, miR-182-5p, miR-203a, miR-222-3p, and miR-432-5p are upregulated following nutlin-3 treatment in a p53 dependent manner. The function of miR-182-5p, miR-203a, miR-222-3p, and miR-432-5p was analyzed by ectopic overexpression of miRNA mimics. We observed that these p53-regulated miRNAs inhibit the proliferation of neuroblastoma cells to varying degrees, with the most profound growth inhibition recorded for miR-182-5p. Overexpression of miR-182-5p promoted apoptosis in some neuroblastoma cell lines and induced neuronal differentiation of NGP cells. Using Chromatin Immunoprecipitation-qPCR (ChIP-qPCR), we did not observe direct binding of p53 to MIR182, MIR203, MIR222, and MIR432 in neuroblastoma cells. Taken together, our findings yield new insights in the network of p53-regulated miRNAs in neuroblastoma

Radiation Hardness of dSiPM Sensors in a Proton Therapy Radiation Environment

In vivo verification of dose delivery in proton therapy by means of positron emission tomography (PET) or prompt gamma imaging is mostly based on fast scintillation detectors. The digital silicon photomultiplier (dSiPM) allows excellent scintillation detector timing properties and is thus being considered for such verification methods. We present here the results of the first investigation of radiation damage to dSiPM sensors in a proton therapy radiation environment. Radiation hardness experiments were performed at the AGOR cyclotron facility at the KVI-Center for Advanced Radiation Technology, University of Groningen. A 150-MeV proton beam was fully stopped in a water target. In the first experiment, bare dSiPM sensors were placed at 25 cm from the Bragg peak, perpendicular to the beam direction, a geometry typical for an in situ implementation of a PET or prompt gamma imaging device. In the second experiment, dSiPM-based PET detectors containing lutetium yttrium orthosilicate scintillator crystal arrays were placed at 2 and 4 m from the Bragg peak, perpendicular to the beam direction; resembling an in-room PET implementation. Furthermore, the experimental setup was simulated with a Geant4-based Monte Carlo code in order to determine the angular and energy distributions of the neutrons and to determine the 1-MeV equivalent neutron fluences delivered to the dSiPM sensors. A noticeable increase in dark count rate (DCR) after an irradiation with about 108 1-MeV equivalent neutrons/cm2 agrees with observations by others for analog SiPMs, indicating that the radiation damage occurs in the single photon avalanche diodes and not in the electronics integrated on the sensor chip. It was found that in the in situ location, the DCR becomes too large for successful operation after the equivalent of a few weeks of use in a proton therapy treatment room (about 5× 103 protons). For PET detectors in an in-room setup, detector performance was unchanged even after an irradiation equivalent to three years of use in a treatment room (3× 1015 protons)