Binary Program Vulnerability Mining Based on Neural Network

Software security analysts typically only have access to the executable program and cannot directly access the source code of the program.This poses significant challenges to security analysis.While it is crucial to identify vulnerabilities in such non-source code programs,there exists a limited set of generalized tools due to the low versatility of current vulnerability mining methods.However,these tools suffer from some shortcomings.In terms of targeted fuzzing,the path searching for target points is not streamlined enough,and the completely random testing leads to an excessively large search space.Additionally,when it comes to code similarity analysis,there are issues with incomplete code feature extraction,which may result in information loss.In this paper,we propose a cross-platform and cross-architecture approach to exploit vulnerabilities using neural network obfuscation techniques.By leveraging the Angr framework,a deobfuscation technique is introduced,along with the adoption of a VEX-IR-based intermediate language conversion method.This combination allows for the unified handling of binary programs across various architectures,compilers,and compilation options.Subsequently,binary programs are processed to extract multi-level spatial features using a combination of a skip-gram model with self-attention mechanism and a bidirectional Long Short-Term Memory(LSTM)network.Finally,the graph embedding network is utilized to evaluate the similarity of program functionalities.Based on these similarity scores,a target function is determined,and symbolic execution is applied to solve the target function.The solved content serves as the initial seed for targeted fuzzing.The binary program is processed by using the de-obfuscation technique and intermediate language transformation method,and then the similarity of program functions is evaluated by using a graph embedding network,and symbolic execution is performed based on these similarity scores.This approach facilitates cross-architecture analysis of executable programs without their source codes and concurrently reduces the risk of symbolic execution path explosion.

Fracture Reactivation Modeling in a Depleted Reservoir

Injection-induced fracture reactivation during hydraulic fracturing processes in shale gas development as well as coal bed methane(CBM)and other unconventional oil and gas recovery is widely investigated because of potential permeability enhancement impacts.Less attention is paid to induced fracture reactivation during oil and gas production and its impacts on reservoir permeability,despite its relatively common occurrence.During production,a reservoir tends to shrink as effective stresses increase,and the deviatoric effective stresses also increase.These changes in the principal effective stresses may cause Coulomb fracture slip in existing natural fractures,depending on their strength,orientation,and initial stress conditions.In this work,an extended finite element model with contact constraints is used to investigate different fracture slip scenarios induced by general reservoir pressure depletion.The numerical experiments assess the effect of Young’s modulus,the crack orientation,and the frictional coefficient of the crack surface on the distribution of stress and displacement after some reservoir depletion.Results show that the crack orientation significantly affects the state of stress and displacement,particularly in the vicinity of the crack.Slip can only occur in permitted directions,as determined by the magnitudes of the principal stresses and the frictional coefficient.Lastly,a larger frictional coefficient(i.e.,a rougher natural fracture surface)makes the crack less prone to shear slip.

Electrospinning synthesis of novel lithium-rich 0.4Li2MnO3.0.6LiNi1/3CO1/3Mn1/3O2 nanotube and its electrochemical performance as cathode of lithium-ion battery

In this study, a lithium-rich 0.4Li2MnO3.0.6LiNi1/3Co1/3Mn1/3O2 nanotube layered cathode synthesized by novel electrospinning is reported, and the effects of temperature on the electrochemical performance and morphologies are investigated. The crystal structure is characterized by X-ray diffraction patterns, and refined by two sets of diffraction data （R-3m and C2/m）. Refined crystal structure is 0.4Li2MnO3.0.6LiNi1/3COl/3Mn13O2 compos- ite. The inductively coupled plasma optical emission spec- trometer and thermogravimetric and differential scanning calorimetry analysis measurement supply reference to opti- mize the calcination temperature and heat-treatment time. The morphology is characterized by scanning and high- resolution transmission electron microscope techniques, and the micro-nanostructured hollow tubes of Li-rich 0.4Li2MnO3-0.6LiNil/3COl/3Mn1/3O2 composite with outer diameter of 200-400 nm and the wall thickness of 50-80 nm are synthesized successfully. The electrochemical evaluation shows that 0.4Li2MnO3.0.6LiNi1/3Cov3Mn1/3O2 sintered at 800 ℃ for 8 h delivers the highest capacity of the first dis- charge capacity of 267.7 mAh/g between 2.5 V and 4.8 V at 0.1C and remains 183.3 mAh/g after 50 cycles. The electro- spinning method with heat-treatment to get micro-nanos- tructured lithium-rich cathode shows promising application inlithium-ion batteries with stable electrochemical performance and higher C-rate performance for its shorter Li ions transfer channels and stable designed structure.

Local tips, global impact: community-driven measures as avenues of promoting inclusion in the control of neglected tropical diseases: a case study in Kenya

Background:Neglected tropical diseases(NTDs)affect poor populations with little or no’’political voice’to influence control activities.While most NTDs have interventions that work,the biggest challenge remains in delivering targeted interventions to affected populations residing in areas experiencing weak health systems.Despite the upward development trends in most countries of sub-Saharan Africa(SSA),the healthcare worker to population ratio remains exceptionally low,with some areas not served at all;thus,there is a need to involve other personnel for school and community-based healthcare approaches.Nonetheless,the current community-based programs suffer from inconsistent community participation due to a lack of coordinated response,and an expanded intervention agenda that lacks context-specific solutions applicable to rural,urban,and marginalized areas.Methods:This research investigated the capacity of local communities to address the burden of NTDs.Informed by the social theory of human capability,the research collected primary qualitative data by conducting key informant interviews and focus group discussions of people infected or affected by NTDs.The interview data were collected and transcribed verbatim for thematic analysis using Nvivo version 12.Results:Our findings reveal,first,a need for intersectoral collaboration between governments and affected populations for inclusive and sustainable NTD solutions.Second,a’’bottom-up’approach that enhances capacity building,sensitization,and behaviour change for improved uptake of NTD interventions.Third,the enforcement of Public Health Legislative Acts that mandates the reporting and treatment of NTDs such as leprosy.Fourth,the establishment of support groups and counseling services to assist persons suffering from debilitating and permanent effects of NTDs.Conclusions:Our research demonstrates the importance of human agency in encouraging new forms of participation leading to the co-production of inclusive and sustainable solutions against NTDs.

Assessment and validation of liquid breakup models for high-pressure dense diesel sprays

Liquid breakup in fuel spray and atomization significantly affects the consequent mixture formation, combustion behavior, and emission formation processes in a direct injection diesel engine. In this paper, different models for liquid breakup processes in high-pressure dense diesel sprays and its impact on multi-dimensional diesel engine simulation have been evaluated against experi- mental observations, along with the influence of the liquid breakup models and the sensitivity of model parameters on diesel sprays and diesel engine simulations. It is found that the modified Kelvin-Helmholtz （KH）-Rayleigh-Taylor （RT） breakup model gives the most reasonable predicted results in both engine simulation and high-pressure diesel spray simulation. For the standard KH-RT model, the model constant Cbl for the breakup length has a significant effect on the predictability of the model, and a fixed value of the constant Cbl cannot provide a satisfactory result for different operation conditions. The Taylor-analogy- breakup （TAB） based models and the RT model do not provide reasonable predictions for the characteristics of high-pressure sprays and simulated engine performance and emissions.

Identification of a dynamic model for shape memory alloy actuator using Hammerstein-Wiener gray box and mutable smart bee algorithm

Purpose–The purpose of the current investigation is to design a robust and reliable computational framework to effectively identify the nonlinear behavior of shape memory alloy(SMA)actuators,as one of the most applicable types of actuators in engineering and industry.The motivation of proposing such an intelligent paradigm emanates in the pursuit of fulfilling the necessity of devising a simple yet effective identification system capable of modeling the hysteric dynamical respond of SMA actuators.Design/methodology/approach–To address the requirements of designing a pragmatic identification system,the authors integrate a set of fast yet reliable intelligent methodologies and provide a predictive tool capable of realizing the nonlinear hysteric behavior of SMA actuators in a computationally efficient fashion.First,the authors utilize the governing equations to design a gray box Hammerstein-Wiener identifier model.At the next step,they adopt a computationally efficient metaheuristic algorithm to elicit the optimum operating parameters of the gray box identifier.Findings–Applying the proposed hybrid identifier framework allows the authors to find out its advantages in modeling the behavior of SMA actuator.Through different experiments,the authors conclude that the proposed identifier can be used for identification of highly nonlinear dynamic behavior of SMA actuators.Furthermore,by extending the conclusions and expounding the obtained results,one can easily infer that such a hybrid method may be conveniently applied to model other engineering phenomena that possess dynamic nonlinear reactions.Based on the exerted experiments and implementing the method,the authors come to the conclusion that integrating the power of metaheuristic exploration/exploitation with gray box identifier results a predictive paradigm that much more computationally efficient as compared with black box identifiers such as neural networks.Additionally,the derived gray box method has a higher degree of preference over the black box identifiers,as it allows a manipulated expert to extract the knowledge of the system at hand.Originality/value–The originality of the research paper is twofold.From the practical(engineering)point of view,the authors built a prototype biased-spring SMA actuator and carried out several experiments to ascertain and validate the parameters of the model.From the computational point of view,the authors seek for designing a novel identifier that overcomes the main flaws associated with the performance of black-box identifiers that are the lack of a mean for extracting the governing knowledge of the system at hand,and high computational expense pertinent to the structure of black-box identifiers.

Discussion of“A selective review of statistical methods using calibration information from similar studies”and some remarks on data integration

Qin,Liu and Li(henceforth QLL)review methods for combining information using empirical likelihood and related approaches;many of these ideas originated in the earlier work of Jing Qin.I thank the authors for their review,and for the opportunity to contribute to its discussion.I have little to say about technical aspects,which are well established but will comment briefly on broader aspects of data integration,and implications for methods like those in the article.

Responses to discussions on‘Optimal reinsurance designs based on risk measures:a review’

We would like to thank four discussants(Professor Chengguo Weng,Professor Tim J.Boonen,Professor Shengchao Zhuang,and Professor Ambrose Lo)for their interesting discussions and comments on our review paper about optimal reinsurance designs based on riskmeasures.Their discussions and comments providemore other interesting research topics for the study of optimal reinsurance designs.Our specified response to each discussant is given as follows.