28 research outputs found
Denial-of-Service Vulnerability of Hash-based Transaction Sharding: Attacks and Countermeasures
Since 2016, sharding has become an auspicious solution to tackle the
scalability issue in legacy blockchain systems. Despite its potential to
strongly boost the blockchain throughput, sharding comes with its own security
issues. To ease the process of deciding which shard to place transactions,
existing sharding protocols use a hash-based transaction sharding in which the
hash value of a transaction determines its output shard. Unfortunately, we show
that this mechanism opens up a loophole that could be exploited to conduct a
single-shard flooding attack, a type of Denial-of-Service (DoS) attack, to
overwhelm a single shard that ends up reducing the performance of the system as
a whole.
To counter the single-shard flooding attack, we propose a countermeasure that
essentially eliminates the loophole by rejecting the use of hash-based
transaction sharding. The countermeasure leverages the Trusted Execution
Environment (TEE) to let blockchain's validators securely execute a transaction
sharding algorithm with a negligible overhead. We provide a formal
specification for the countermeasure and analyze its security properties in the
Universal Composability (UC) framework. Finally, a proof-of-concept is
developed to demonstrate the feasibility and practicality of our solution
NeuCEPT: Locally Discover Neural Networks' Mechanism via Critical Neurons Identification with Precision Guarantee
Despite recent studies on understanding deep neural networks (DNNs), there
exists numerous questions on how DNNs generate their predictions. Especially,
given similar predictions on different input samples, are the underlying
mechanisms generating those predictions the same? In this work, we propose
NeuCEPT, a method to locally discover critical neurons that play a major role
in the model's predictions and identify model's mechanisms in generating those
predictions. We first formulate a critical neurons identification problem as
maximizing a sequence of mutual-information objectives and provide a
theoretical framework to efficiently solve for critical neurons while keeping
the precision under control. NeuCEPT next heuristically learns different
model's mechanisms in an unsupervised manner. Our experimental results show
that neurons identified by NeuCEPT not only have strong influence on the
model's predictions but also hold meaningful information about model's
mechanisms.Comment: 6 main page
XRand: Differentially Private Defense against Explanation-Guided Attacks
Recent development in the field of explainable artificial intelligence (XAI)
has helped improve trust in Machine-Learning-as-a-Service (MLaaS) systems, in
which an explanation is provided together with the model prediction in response
to each query. However, XAI also opens a door for adversaries to gain insights
into the black-box models in MLaaS, thereby making the models more vulnerable
to several attacks. For example, feature-based explanations (e.g., SHAP) could
expose the top important features that a black-box model focuses on. Such
disclosure has been exploited to craft effective backdoor triggers against
malware classifiers. To address this trade-off, we introduce a new concept of
achieving local differential privacy (LDP) in the explanations, and from that
we establish a defense, called XRand, against such attacks. We show that our
mechanism restricts the information that the adversary can learn about the top
important features, while maintaining the faithfulness of the explanations.Comment: To be published at AAAI 202
Active Membership Inference Attack under Local Differential Privacy in Federated Learning
Federated learning (FL) was originally regarded as a framework for
collaborative learning among clients with data privacy protection through a
coordinating server. In this paper, we propose a new active membership
inference (AMI) attack carried out by a dishonest server in FL. In AMI attacks,
the server crafts and embeds malicious parameters into global models to
effectively infer whether a target data sample is included in a client's
private training data or not. By exploiting the correlation among data features
through a non-linear decision boundary, AMI attacks with a certified guarantee
of success can achieve severely high success rates under rigorous local
differential privacy (LDP) protection; thereby exposing clients' training data
to significant privacy risk. Theoretical and experimental results on several
benchmark datasets show that adding sufficient privacy-preserving noise to
prevent our attack would significantly damage FL's model utility.Comment: Published at AISTATS 202
Tin Dioxide Nanocrystals as an Effective Sensitizer for Erbium Ions in Er-Doped SnO 2
Undoped SnO2 and erbium-doped SnO2 powders were successfully prepared by precipitation method. The effect of the heat treatment and doping contents on the structure of tin oxide and optical properties was also studied. The XRD data and Raman spectra indicate that the SnO2 crystals have formed after being heat-treated at 400°C and the average size of grains is about 8 nm for doping content of 1 mol%. An increase of doping concentration has controlled the growth of nanocrystals. The principle of the visible and infrared emissions of SnO2 and SnO2:Er is also discussed. All photoluminescence study shows that the Er3+ ions can be located in SnO2 nanocrystals and that there is energy transfer from defect levels of SnO2 nanoparticles to neighboring Er3+ ions of crystals
Non-coding RNAs versus protein biomarkers to diagnose and differentiate acute stroke:Systematic review and meta-analysis
BACKGROUND: Stroke diagnosis is dependent on lengthy clinical and neuroimaging assessments, while rapid treatment initiation improves clinical outcome. Currently, more sensitive biomarker assays of both non-coding RNA- and protein biomarkers have improved their detectability, which could accelerate stroke diagnosis. This systematic review and meta-analysis compares non-coding RNA- with protein biomarkers for their potential to diagnose and differentiate acute stroke (subtypes) in (pre-)hospital settings.METHODS: We performed a systematic review and meta-analysis of studies evaluating diagnostic performance of non-coding RNA- and protein biomarkers to differentiate acute ischemic and hemorrhagic stroke, stroke mimics, and (healthy) controls. Quality appraisal of individual studies was assessed using the QUADAS-2 tool while the meta-analysis was performed with the sROC approach and by assessing pooled sensitivity and specificity, diagnostic odds ratios, positive- and negative likelihood ratios, and the Youden Index.SUMMARY OF REVIEW: 112 studies were included in the systematic review and 42 studies in the meta-analysis containing 11627 patients with ischemic strokes, 2110 patients with hemorrhagic strokes, 1393 patients with a stroke mimic, and 5548 healthy controls. Proteins (IL-6 and S100 calcium-binding protein B (S100B)) and microRNAs (miR-30a) have similar performance in ischemic stroke diagnosis. To differentiate between ischemic- or hemorrhagic strokes, glial fibrillary acidic protein (GFAP) levels and autoantibodies to the NR2 peptide (NR2aAb, a cleavage product of NMDA neuroreceptors) were best performing whereas no investigated protein or non-coding RNA biomarkers differentiated stroke from stroke mimics with high diagnostic potential.CONCLUSIONS: Despite sampling time differences, circulating microRNAs (< 24 h) and proteins (< 4,5 h) perform equally well in ischemic stroke diagnosis. GFAP differentiates stroke subtypes, while a biomarker panel of GFAP and UCH-L1 improved the sensitivity and specificity of UCH-L1 alone to differentiate stroke.</p
Sex Differences in Prehospital Identification of Large Vessel Occlusion in Patients with Suspected Stroke
BACKGROUND: Differences in clinical presentation of acute ischemic stroke between men and women may affect prehospital identification of anterior circulation large vessel occlusion (aLVO). We assessed sex differences in diagnostic performance of 8 prehospital scales to detect aLVO. METHODS: We analyzed pooled individual patient data from 2 prospective cohort studies (LPSS [Leiden Prehospital Stroke Study] and PRESTO [Prehospital Triage of Patients With Suspected Stroke Study]) conducted in the Netherlands between 2018 and 2019, including consecutive patients ≥18 years suspected of acute stroke who presented within 6 hours after symptom onset. Ambulance paramedics assessed clinical items from 8 prehospital aLVO detection scales: Los Angeles Motor Scale, Rapid Arterial Occlusion Evaluation, Cincinnati Stroke Triage Assessment Tool, Cincinnati Prehospital Stroke Scale, Prehospital Acute Stroke Severity, gaze-face-arm-speech-time, Conveniently Grasped Field Assessment Stroke Triage, and Face-Arm-Speech-Time Plus Severe Arm or Leg Motor Deficit. We assessed the diagnostic performance of these scales for identifying aLVO at prespecified cut points for men and women.RESULTS: Of 2358 patients with suspected stroke (median age, 73 years; 47% women), 231 (10%) had aLVO (100/1114 [9%] women and 131/1244 [11%] men). The area under the curve of the scales ranged from 0.70 (95% CI, 0.65-0.75) to 0.77 (95% CI, 0.73-0.82) in women versus 0.69 (95% CI, 0.64-0.73) to 0.75 (95% CI, 0.71-0.79) in men. Positive predictive values ranged from 0.23 (95% CI, 0.20-0.27) to 0.29 (95% CI, 0.26-0.31) in women versus 0.29 (95% CI, 0.24-0.33) to 0.37 (95% CI, 0.32-0.43) in men. Negative predictive values were similar (0.95 [95% CI, 0.94-0.96] to 0.98 [95% CI, 0.97-0.98] in women versus 0.94 [95% CI, 0.93-0.95] to 0.96 [95% CI, 0.94-0.97] in men). Sensitivity of the scales was slightly higher in women than in men (0.53 [95% CI, 0.43-0.63] to 0.76 [95% CI, 0.68-0.84] versus 0.49 [95% CI, 0.40-0.57] to 0.63 [95% CI, 0.55-0.73]), whereas specificity was lower (0.79 [95% CI, 0.76-0.81] to 0.87 [95% CI, 0.84-0.89] versus 0.82 [95% CI, 0.79-0.84] to 0.90 [95% CI, 0.88-0.91]). Rapid arterial occlusion evaluation showed the highest positive predictive values in both sexes (0.29 in women and 0.37 in men), reflecting the different event rates. CONCLUSIONS: aLVO scales show similar diagnostic performance in both sexes. The rapid arterial occlusion evaluation scale may help optimize prehospital transport decision-making in men as well as in women with suspected stroke.</p
Sex Differences in Prehospital Identification of Large Vessel Occlusion in Patients with Suspected Stroke
BACKGROUND: Differences in clinical presentation of acute ischemic stroke between men and women may affect prehospital identification of anterior circulation large vessel occlusion (aLVO). We assessed sex differences in diagnostic performance of 8 prehospital scales to detect aLVO. METHODS: We analyzed pooled individual patient data from 2 prospective cohort studies (LPSS [Leiden Prehospital Stroke Study] and PRESTO [Prehospital Triage of Patients With Suspected Stroke Study]) conducted in the Netherlands between 2018 and 2019, including consecutive patients ≥18 years suspected of acute stroke who presented within 6 hours after symptom onset. Ambulance paramedics assessed clinical items from 8 prehospital aLVO detection scales: Los Angeles Motor Scale, Rapid Arterial Occlusion Evaluation, Cincinnati Stroke Triage Assessment Tool, Cincinnati Prehospital Stroke Scale, Prehospital Acute Stroke Severity, gaze-face-arm-speech-time, Conveniently Grasped Field Assessment Stroke Triage, and Face-Arm-Speech-Time Plus Severe Arm or Leg Motor Deficit. We assessed the diagnostic performance of these scales for identifying aLVO at prespecified cut points for men and women.RESULTS: Of 2358 patients with suspected stroke (median age, 73 years; 47% women), 231 (10%) had aLVO (100/1114 [9%] women and 131/1244 [11%] men). The area under the curve of the scales ranged from 0.70 (95% CI, 0.65-0.75) to 0.77 (95% CI, 0.73-0.82) in women versus 0.69 (95% CI, 0.64-0.73) to 0.75 (95% CI, 0.71-0.79) in men. Positive predictive values ranged from 0.23 (95% CI, 0.20-0.27) to 0.29 (95% CI, 0.26-0.31) in women versus 0.29 (95% CI, 0.24-0.33) to 0.37 (95% CI, 0.32-0.43) in men. Negative predictive values were similar (0.95 [95% CI, 0.94-0.96] to 0.98 [95% CI, 0.97-0.98] in women versus 0.94 [95% CI, 0.93-0.95] to 0.96 [95% CI, 0.94-0.97] in men). Sensitivity of the scales was slightly higher in women than in men (0.53 [95% CI, 0.43-0.63] to 0.76 [95% CI, 0.68-0.84] versus 0.49 [95% CI, 0.40-0.57] to 0.63 [95% CI, 0.55-0.73]), whereas specificity was lower (0.79 [95% CI, 0.76-0.81] to 0.87 [95% CI, 0.84-0.89] versus 0.82 [95% CI, 0.79-0.84] to 0.90 [95% CI, 0.88-0.91]). Rapid arterial occlusion evaluation showed the highest positive predictive values in both sexes (0.29 in women and 0.37 in men), reflecting the different event rates. CONCLUSIONS: aLVO scales show similar diagnostic performance in both sexes. The rapid arterial occlusion evaluation scale may help optimize prehospital transport decision-making in men as well as in women with suspected stroke.</p