Smart Contract Based DDoS Attack Traceability Audit Mechanism in Intelligent IoT

In this paper,we focus on providing data provenance auditing schemes for distributed denial of service(DDoS)defense in intelligent internet of things(IoT).To achieve effective DDoS defense,we introduce a two-layer collaborative blockchain framework to support data auditing.Specifically,using data scattered among intelligent IoT devices,switch gateways self-assemble a layer of blockchain in the local autonomous system(AS),and the main chain with controller participation can be aggregated by its associated layer of blocks once a cycle,to obtain a global security model.To optimize the processing delay of the security model,we propose a process of data pre-validation with the goal of ensuring data consistency while satisfying overhead requirements.Since the flood of identity spoofing packets,it is difficult to solve the identity consistency of data with traditional detection methods,and accountability cannot be pursued afterwards.Thus,we proposed a Packet Traceback Telemetry(PTT)scheme,based on in-band telemetry,to solve the problem.Specifically,the PTT scheme is executed on the distributed switch side,the controller to schedule and select routing policies.Moreover,a tracing probabilistic optimization is embedded into the PTT scheme to accelerate path reconstruction and save device resources.Simulation results show that the PTT scheme can reconstruct address spoofing packet forward path,reduce the resource consumption compared with existing tracing scheme.Data tracing audit method has fine-grained detection and feasible performance.

ICN Based Vehicle-to-Cloud Delivery for Multimedia Streaming in Urban Vehicular Networks

Mobile multimedia streaming is an open topic in vehicular environment.Due to the high intermittent links,it has become a critical challenge to deliver high quality video streaming in vehicular networks.In this paper,we reform the Information Centric Networking(ICN) concept for multimedia delivery in urban vehicular networks.By leveraging the ICN perspective,we highlight that vehicular peers can obtain multimedia chunks via the vehicle-to-cloud(V2C) approach to improve the delivery quality.Based on this,we propose a lightweight multipath selection strategy to guide the network system to adaptively adjust the forwarding means.Extensive simulations show that the proposed solution can optimize the utilization of network paths,lighten network loads as well as avoid wasting resources.

Distributed Asynchronous Learning for Multipath Data Transmission Based on P-DDQN

Adaptive packet scheduling can efficiently enhance the performance of multipath Data Transmission.However,realizing precise packet scheduling is challenging due to the nature of high dynamics and unpredictability of network link states.To this end,this paper proposes a distributed asynchronous deep reinforcement learning framework to intensify the dynamics and prediction of adaptive packet scheduling.Our framework contains two parts:local asynchronous packet scheduling and distributed cooperative control center.In local asynchronous packet scheduling,an asynchronous prioritized replay double deep Q-learning packets scheduling algorithm is proposed for dynamic adaptive packet scheduling learning,which makes a combination of prioritized replay double deep Q-learning network(P-DDQN)to make the fitting analysis.In distributed cooperative control center,a distributed scheduling learning and neural fitting acceleration algorithm to adaptively update neural network parameters of P-DDQN for more precise packet scheduling.Experimental results show that our solution has a better performance than Random weight algorithm and Round-Robin algorithm in throughput and loss ratio.Further,our solution has 1.32 times and 1.54 times better than Random weight algorithm and Round-Robin algorithm on the stability of multipath data transmission,respectively.

Comparison of Clinical Characteristics and Outcomes of MAFLD and NAFLD in Chinese Health Examination Populations

Background and Aims:The recently proposed concept of metabolic dysfunction-associated fatty liver disease(MAFLD)has remained controversial.We aimed to describe the features and associated outcomes to examine the diagnostic ability of MAFLD for identifying high-risk individuals.Methods:In this retrospective cohort study,we enrolled 72,392 Chinese participants between 2014 and 2015.Participants were classified as MAFLD,nonalcoholic fatty liver disease(NAFLD),non-MAFLD-NAFLD,and a normal control group.The primary outcomes were liver-related and cardiovascular disease(CVD)events.Person-years of follow-up were calculated from enrolment to the diagnosis of the event,or the last date of data(June,2020).Results:Of the 72,392 participants,31.54%(22,835)and 28.33%(20,507)qualified the criteria for NAFLD or MAFLD,respectively.Compared with NAFLD,MAFLD patients were more likely to be male,overweight,and have higher biochemical indices including liver enzyme levels.Lean MAFLD diagnosed with≥2 or≥3 metabolic abnormalities presented similar clinical manifestations.During the median follow-up of 5.22 years,919 incident cases of severe liver disease and 2,073 CVD cases were recorded.Compared with the normal control group,the NAFLD and MAFLD groups had a higher cumulative risk of liver failure and cardiac-cerebral vascular diseases.There were no significant differences in risk between the non-MAFLD-NAFLD and normal group.Diabetes-MAFLD group had the highest incidence of liver-related and cardiac-cerebral vascular diseases,lean MAFLD came second,and obese-MAFLD had the lowest incidence.Conclusions:This real-world study provided evidence for rationally assessing the benefit and practicability of the change in terminology from NAFLD to MAFLD.MAFLD may be better than NAFLD in identifying fatty liver with worse clinical features and risk profile.

Optimization of high-pressure processing-assisted extraction of pectic polysaccharides from three berries

Background and objectives:High-pressure processing(HPP)is a promising assistive method to extract pectic polysaccharides with high rhamnogalacturonan I(RG-I)domain and berries are sources of such pectic polysaccharides.This study extracts pectic polysaccharides from goji berry,raspberry,and cranberry,examines how HPP influences the pectic polysaccharide structure of three berries,and provides a basis for the extraction and modification of pectic polysaccharides with specific structure and bioactivity.Materials and methods:An orthogonal test was performed to optimize the HPP-assisted alkali method to extract the high yield and high RG-I content pectic polysaccharides from three berries.Structural information of pectic polysaccharides extracted by the HPP method and conventional methods were compared from the perspectives of monosaccharide composition,molecular weight,Fourier transform infrared spectroscopy,andnuclearmagneticresonancespectroscopy.Results:For raspberry,the optimal conditions consisted of a pressure of 50o MPa,a pH of 13,and a pressure-holding time of 12 min,while the optimal conditions for goji berry and cranberry were both 40o MPa,pH 13,and 15 min.Under the optimal conditions,the yields for goji berry,raspberry,and cranberry were 10.49%,16.63%,and 17.52%,respectively,and RG-l contents were 81.85%,83.30%,and 63.22%,respectively.HPP showed an effect to degrade homogalacturonan backbones and side chains and increase the RG-I content to some extent.Conclusion:HPP-assisted alkali method was revealed to be an efficient method to extract high RG-I content pectic polysaccharides,especially for cranberry,and was a potential method to modify pectic polysaccharide structure in a certain way.

A rapid method for extraction,purification and structure analysis of chondroitin sulfate from six marine tissues

This study was designed to establish a strategy for the extraction,purification,and structure analysis of chondroitin sulfate(cs)in milligram amounts.Crude acidic polysaccharides were extracted from six kinds of marine animals by enzymatic hydrolysis and hexadecylpyridinium chloride precipitation and purified by Q Sepharose Fast Flow strong anion exchange column.The purification of each crude polysaccharide was completed within 1 h.The structure of the polysaccharides,i.e.their chemical characterization,functional group,molecular weight and monosaccharide composition,were analyzed by colorimetry,nuclear magnetic resonace and high-performance liquid chromatogrpahy,respectively.All polysaccharides were identified as Cs.The oligosaccharide profile produced by enzyme hydrolysis of polysaccharides was determined by strong anion-exchange high-performance liquid chromatorgraphy.This method can be widely applied to the extraction and characterization of chondroitin sulfate from unknown raw materials,screening high-quality sources of functional polysaccharides,and laying a good foundation for thefollowing studyof the structure-function relationshipof polysaccharides.