Efficient Penetration Testing Path Planning Based on Reinforcement Learning with Episodic Memory

Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test paths.In view of the difficulty for attackers to obtain complete network information in realistic network scenarios,Reinforcement Learning(RL)is a promising solution to discover the optimal penetration path under incomplete information about the target network.Existing RL-based methods are challenged by the sizeable discrete action space,which leads to difficulties in the convergence.Moreover,most methods still rely on experts’knowledge.To address these issues,this paper proposes a penetration path planning method based on reinforcement learning with episodic memory.First,the penetration testing problem is formally described in terms of reinforcement learning.To speed up the training process without specific prior knowledge,the proposed algorithm introduces episodic memory to store experienced advantageous strategies for the first time.Furthermore,the method offers an exploration strategy based on episodic memory to guide the agents in learning.The design makes full use of historical experience to achieve the purpose of reducing blind exploration and improving planning efficiency.Ultimately,comparison experiments are carried out with the existing RL-based methods.The results reveal that the proposed method has better convergence performance.The running time is reduced by more than 20%.

Enhancing Mobile Security through Comprehensive Penetration Testing

In today’s era, where mobile devices have become an integral part of our daily lives, ensuring the security of mobile applications has become increasingly crucial. Mobile penetration testing, a specialized subfield within the realm of cybersecurity, plays a vital role in safeguarding mobile ecosystems against the ever-evolving landscape of threats. The ubiquity of mobile devices has made them a prime target for cybercriminals, and the data and functionality accessed through mobile applications make them valuable assets to protect. Mobile penetration testing is designed to identify vulnerabilities, weaknesses, and potential exploits within mobile applications and the devices themselves. Unlike traditional penetration testing, which often focuses on network and server security, mobile penetration testing zeroes in on the unique challenges posed by mobile platforms. Mobile penetration testing, a specialized field within cybersecurity, is an essential tool in the Cybersecurity specialists’ toolkit to protect mobile ecosystems from emerging threats. This article introduces mobile penetration testing, emphasizing its significance, including comprehensive learning labs for Android and iOS platforms, and highlighting how it distinctly differs from traditional penetration testing methodologies.

Penetration Tests of Multi-Bucket Foundation in Sand for Offshore Wind Turbines

Suction foundations are generally installed with negative pressures to overcome the resistance of soils and complete the penetration,but excessive negative pressures are also avoided to cause seepage damages.In this paper,the model test method was used to analyze the movement characteristics of multi-bucket foundations in the process of sinking in sand,and the common calculation methods of sinking resistances are verified.The critical negative pressure corresponding to the seepage failure of foundation was determined under the action of increasing negative pressure step by step and the characteristics of soil failure were studied.The calculation formula of critical suction in sand was verified in application,and according to the test results,the value of seepage coefficient was modified,which provides an example for the study of suction foundation in sand soils.

Study on strength properties and soil behaviour type classification of Huanghe River Delta silts based on variable rate piezocone penetration test

Fine-grained silt is widely distributed in the Huanghe River Delta(HRD)in China,and the sedimentary structure is complex,meaning that the clay content in the silt is variable.The piezocone penetration test(CPTu)is the most widely approved in situ test method.It can be used to invert soil properties and interpret soil behavior.To analyse the strength properties of surface sediments in the HRD,this paper evaluated the friction angle and its inversion formula through the CPTu penetration test and monotonic simple shear test and other soil unit experiments.The evaluation showed that the empirical formula proposed by Kulhawy and Mayne had better prediction and inversion effect.The HRD silts with clay contents of 9.2%,21.4%and 30.3%were selected as samples for the CPTu variable rate penetration test.The results show as follows.(1)The effects of the clay content on the tip resistance and the pore pressure of silt under different penetration rates were summarized.The tip resistance Q_t is strongly dependent on the clay content of the silt,the B_(q)value of the silt tends to 0 and is not significantly affected by the change of the CPTu penetration rate.(2)Five soil behavior type classification charts and three soil behavior type indexes based on CPTu data were evaluated.The results show that the soil behavior type classification chart based on soil behavior type index ISBT,the Robertson 2010 behavior type classification chart are more suitable for the silty soil in the HRD.

Obtaining 2D Soil Resistance Profiles from the Integration of Electrical Resistivity Data and Standard Penetration Test (SPT) and Light Dynamic Penetrometer (DPL) Resistance Tests—Applications in Mass Movements Studies

In Brazil and various regions globally, the initiation of landslides is frequently associated with rainfall;yet the spatial arrangement of geological structures and stratification considerably influences landslide occurrences. The multifaceted nature of these influences makes the surveillance of mass movements a highly intricate task, requiring an understanding of numerous interdependent variables. Recent years have seen an emergence in scholarly research aimed at integrating geophysical and geotechnical methodologies. The conjoint examination of geophysical and geotechnical data offers an enhanced perspective into subsurface structures. Within this work, a methodology is proposed for the synchronous analysis of electrical resistivity geophysical data and geotechnical data, specifically those extracted from the Light Dynamic Penetrometer (DPL) and Standard Penetration Test (SPT). This study involved a linear fitting process to correlate resistivity with N10/SPT N-values from DPL/SPT soundings, culminating in a 2D profile of N10/SPT N-values predicated on electrical profiles. The findings of this research furnish invaluable insights into slope stability by allowing for a two-dimensional representation of penetration resistance properties. Through the synthesis of geophysical and geotechnical data, this project aims to augment the comprehension of subsurface conditions, with potential implications for refining landslide risk evaluations. This endeavor offers insight into the formulation of more effective and precise slope management protocols and disaster prevention strategies.

Regressive approach for predicting bearing capacity of bored piles from cone penetration test data

In this study, th e least sq u are su p p o rt v ecto r m achine （LSSVM） alg o rith m w as applied to predicting th ebearing capacity o f b ored piles e m b ed d ed in sand an d m ixed soils. Pile g eo m etry an d cone p e n e tra tio nte s t （CPT） resu lts w ere used as in p u t variables for pred ictio n o f pile bearin g capacity. The d ata u se d w erecollected from th e existing litera tu re an d consisted o f 50 case records. The application o f LSSVM w ascarried o u t by dividing th e d ata into th re e se ts： a train in g se t for learning th e pro b lem an d obtain in g arelationship b e tw e e n in p u t variables an d pile bearin g capacity, and testin g an d validation sets forevaluation o f th e predictive an d g en eralization ability o f th e o b tain ed relationship. The predictions o f pilebearing capacity by LSSVM w ere evaluated by com paring w ith ex p erim en tal d ata an d w ith th o se bytrad itio n al CPT-based m eth o d s and th e gene ex pression pro g ram m in g （GEP） m odel. It w as found th a t th eLSSVM perform s w ell w ith coefficient o f d eterm in atio n , m ean, an d sta n d ard dev iatio n equivalent to 0.99,1.03, an d 0.08, respectively, for th e testin g set, an d 1, 1.04, an d 0.11, respectively, for th e v alidation set. Thelow values o f th e calculated m ean squared e rro r an d m ean ab so lu te e rro r indicated th a t th e LSSVM w asaccurate in p redicting th e pile bearing capacity. The results o f com parison also show ed th a t th e p roposedalg o rith m p red icted th e pile bearin g capacity m ore accurately th a n th e trad itio n al m eth o d s including th eGEP m odel.

Fall cone tests considering water content, cone penetration index, and plasticity angle of fine-grained soils

This paper analyzed the consistency of some parameters of soils in the literature and experimental results from fall cone test and its application to soil plasticity classification.Over 500 data from both literatures and experiments using fall cone and Casagrande methods were compiled to assess the relationships among specified water content,cone penetration index ebT,and plasticity angle eaT of finegrained soils.The results indicate that no unique correlation exists among b,liquid limit of the fall cone test(LLc)and a.The water content at 1 mm cone penetration eC0T correlates well with b,plasticity ratio eRpT(i.e.the ratio of plastic limit to liquid limit),and a.Finally,the potential of using the btan a diagram to classify soil plasticity was also discussed.

Adaptive sampling strategy for characterizing spatial distribution of soil liquefaction potential using cone penetration test

Characterizing spatial distribution of soil liquefaction potential is critical for assessing liquefactionrelated hazards(e.g.building damages caused by liquefaction-induced differential settlement).However,in engineering practice,soil liquefaction potential is usually measured at limited locations in a specific site using in situ tests,e.g.cone penetration tests(CPTs),due to the restrictions of time,cost and access to subsurface space.In these cases,liquefaction potential of soil at untested locations requires to be interpreted from limited measured data points using proper interpolation method,leading to remarkable statistical uncertainty in liquefaction assessment.This underlines an important question of how to optimize the locations of CPT soundings and determine the minimum number of CPTs for achieving a target reliability level of liquefaction assessment.To tackle this issue,this study proposes a smart sampling strategy for determining the minimum number of CPTs and their optimal locations in a selfadaptive and data-driven manner.The proposed sampling strategy leverages on information entropy and Bayesian compressive sampling(BCS).Both simulated and real CPT data are used to demonstrate the proposed method.Illustrative examples indicate that the proposed method can adaptively and sequentially select the required number and optimal locations of CPTs.

Round robin using the depth of penetration test method on an armour grade alumina

The depth of penetration(DOP)method is a well-known ballistic test method for characterisation and ranking of ceramic armour materials.The ceramic tile is bonded to a backing material of semi-infinite thickness,and the penetration depth of the projectile gives a measure of the performance of the ceramic.There is,however,an inherent variability in the results from this test method.In this work,the accuracy and the variability of the DOP method has been investigated in a round robin exercise.Six ballistic test centres took part in the exercise.A test protocol was developed,in which the threat type(projectile and impact conditions)and a procedure on how to prepare the targets were specified.The targets consisted of alumina tiles of two different thicknesses that were bonded to polycarbonate backing cubes.Two different 7.62 mm armour piercing projectiles were employed;one with a hard steel core and one with a tungsten carbide core.The projectiles and the other materials all came from single material batches in order to avoid batch-to-batch variations in material properties.These materials were distributed between the ballistic test centres.The test results of the different ballistic test facilities were collected and compared.There was not a lot of variation between the average DOP values obtained at each laboratory,but the variation in penetration depth between shots was high.The consequence of this variation may be less confidence in the test results,and a statistical method was used to evaluate the required number of tests that are sufficient to obtain an average result with high confidence.In most cases,the required number of tests is much higher than what is practically feasible.This work was conducted as part of the European Defence Agency-project CERAMBALL.

Structured Query Language Injection Penetration Test Case Generation Based on Formal Description

Aiming to improve the Structured Query Language( SQL) injection penetration test accuracy through the formalismguided test case generation,an attack purpose based attack tree model of SQL injection is proposed,and then under the guidance of this model, the formal descriptions for the SQL injection vulnerability feature and SQL injection attack inputs are established. Moreover,according to new coverage criteria,these models are instantiated and the executable test cases are generated.Experiments show that compared with the random enumerated test case used in other works,the test case generated by our method can detect the SQL injection vulnerability more effectively. Therefore,the false negative is reduced and the test accuracy is improved.

Liquefaction-Induced Ground Deformations Evaluation Based on Cone Penetration Tests (CPT)

The aim of this paper is to evaluate the liquefaction-induced ground deformations of sand-like soils based on Cone Penetration Tests (CPT) at Semani site, Fieri prefecture in Albania. These tests are performed during the process of investigation of this area, in which a Liquid Natural Gas Terminal-Power Plant was supposed to be built. This paper presents the assessment of the liquefaction and of the liquefaction-induced ground deformations such as lateral spreading displacement and post-liquefaction reconsolidation settlement. The liquefaction-induced lateral spreading and post-liquefaction reconsolidation settlement are estimated based on CPT data according to the method in MNO-12 “soil liquefaction during earthquake”, presented by Idriss and Boulanger (2008). This evaluation is very important and should be taken into consideration for the design of engineering structures that will be constructed in this area. All the calculation’s results are shown in graphs. At the end, there are highlighted some conclusions regarding the liquefaction-induced ground deformations in this site.

Seasonal influence on cone penetration test: An unsaturated soil site example

Interpretation of electric cone penetration test(CPT) based pore water pressure measurement(CPTu) is well established for soils with behavior that follows classical soil mechanics. The literature on the interpretation of these tests performed on unsaturated tropical soils is limited, and little is known about the influence of soil suction on in situ test data. In this context, the CPT data are presented and discussed to illustrate the seasonal variability in an unsaturated tropical soil site. The test data show that soil suction significantly influenced CPT data up to a depth of 4 m at the study site. It shows the importance of considering seasonal variability in unsaturated soil sites caused by soil suction, which was related to water content through a soil-water retention curve(SWRC). It is also important to consider this aspect in the interpretation of CPT data from these soils.

A case study on the soil classification of the Yellow River Delta based on piezocone penetration test

Piezocone penetration test(CPTu),the preferred in-situ tool for submarine investigation,is significant for soil classification and soil depth profile prediction,which can be used to predict soil types and states.However,the accuracy of these methods needs to be validated for local conditions.To distinguish and evaluate the properties of the shallow surface sediments in Chengdao area of the Yellow River Delta,seabed CPTu tests were carried out at ten stations in this area.Nine soil classification methods based on CPTu data are applied for soil classification.The results of classification are compared with the in-situ sampling to determine whether the method can provide sufficient resolution.The methods presented by Robertson(based on soil behavior type index Ic),Olsen and Mitchell are the more consistent and compatible ones compared with other methods.Considering that silt soils have potential to liquefy under storm tide or other adverse conditions,this paper is able to screen soil classification methods suitable for the Chengdao area and help identify the areas where liquefaction or submarine landslide may occur through CPTu investigation.

Application of artificial neural networks for predicting the impact of rolling dynamic compaction using dynamic cone penetrometer test results

Rolling dynamic compaction(RDC),which involves the towing of a noncircular module,is now widespread and accepted among many other soil compaction methods.However,to date,there is no accurate method for reliable prediction of the densification of soil and the extent of ground improvement by means of RDC.This study presents the application of artificial neural networks(ANNs) for a priori prediction of the effectiveness of RDC.The models are trained with in situ dynamic cone penetration(DCP) test data obtained from previous civil projects associated with the 4-sided impact roller.The predictions from the ANN models are in good agreement with the measured field data,as indicated by the model correlation coefficient of approximately 0.8.It is concluded that the ANN models developed in this study can be successfully employed to provide more accurate prediction of the performance of the RDC on a range of soil types.

An Automated Penetration Semantic Knowledge Mining Algorithm Based on Bayesian Inference

Mining penetration testing semantic knowledge hidden in vast amounts of raw penetration testing data is of vital importance for automated penetration testing.Associative rule mining,a data mining technique,has been studied and explored for a long time.However,few studies have focused on knowledge discovery in the penetration testing area.The experimental result reveals that the long-tail distribution of penetration testing data nullifies the effectiveness of associative rule mining algorithms that are based on frequent pattern.To address this problem,a Bayesian inference based penetration semantic knowledge mining algorithm is proposed.First,a directed bipartite graph model,a kind of Bayesian network,is constructed to formalize penetration testing data.Then,we adopt the maximum likelihood estimate method to optimize the model parameters and decompose a large Bayesian network into smaller networks based on conditional independence of variables for improved solution efficiency.Finally,irrelevant variable elimination is adopted to extract penetration semantic knowledge from the conditional probability distribution of the model.The experimental results show that the proposed method can discover penetration semantic knowledge from raw penetration testing data effectively and efficiently.

Development and Application of an in Situ Penetrator for Rapid Strength Testing of Submarine Sediment

In marine engineering, the strength of a submarine sediment is an indispensable parameter for assessment of construction. In this study, a free-fall cone penetrator named IPen was developed to realize a rapid and efficient measurement of sediment strength. The equipment is characterized by modular design and self-contained data acquisition. It is equipped with an acceleration sensor, a water pressure sensor, and a piezocone penetration test(CPTu) probe. It is designed to be released from near seabed surface with a releaser and then fall freely to provide a higher penetration velocity. Its maximum working depth is approximately 2500 m and maximum penetration depth is approximately 3 m. To derive the correlation between penetration resistance and sediment strength, a calibrator was devised to determine the penetration-rate factor. In addition, the factor applicable to in situ test points was determined in laboratory experiments. In June 2016, the IPen was tested in situ in the South Yellow Sea, China, during a shared voyage funded by the National Science Foundation. Meanwhile, undisturbed column samples were collected for laboratory tests. Based on the in situ test results, it was demonstrated that the IPen could accurately record the working states of various sensors during the freely falling course. IPen test results reliably reflected the sediment strength at all the testing points when compared with laboratory calibration tests, in situ vane tests and penetration tests, laboratory penetration tests, and unconsolidated and undrained triaxial compression tests.

Experimental investigation on anti-penetration performance of polyurea-coated ASTM1045 steel plate subjected to projectile impact

In this study,the anti-penetration performance of polyurea/ASTM1405-steel composite plate subjected to high velocity projectile was analyzed.Two kinds of modified polyurea material(AMMT-053 and AMMT-055)were selected and a ballistic impact testing system including speed measuring target system and high-speed camera was designed.This experiment was conducted with a rifle and 5.8 mm projectile to explore the effects by the polyurea coating thickness,the polyurea coating position and the glass-fiber cloth on the anti-penetration performance of polyurea/ASTM1405-steel composite plate.The result showed that the effects of polyurea coating position were different between two types of polyurea,and that the effects of glass-fiber position were disparate between two types of polyurea as well.For AMMT-053 polyurea material,it was better to be on front face than on rear face;whereas for AMMT-055 polyurea,it was better to be on rear surface although the difference was very subtle.Additionally,formulas had been given to describe the relationship between the effectiveness of polyurea and the thickness of polyurea coating.In general,AMMT-055 had better anti-penetration performance than AMMT-053.Furthermore,five typical damage modes including self-healing,crack,local bulge,spallation and local fragmentation were defined and the failure mechanism was analyzed with the results of SHPB test.Additionally,the bonding strength played an important role in the anti-penetration performance of polyurea/steel composite plate.

Effects of Silica Fume and Steel Fiber on Chloride Ion Penetration and Corrosion Behavior of Cement-based Composites

This project was aimed to evaluate the chloride permeability and corrosion behavior of cement-based composites which comprised fibers and silica fume in the mixes~ Resistivity, polarization resistance, ponding and rapid chloride penetration results of specimens were obtained through tests. Test results indicate that resistivity, open circuit potentials and direct current polarization of specimens with w/b ratio of 0.35 are higher than those of specimens with w/b ratio of 0.55. For length-diameter ratio of 65, resistivity and direct current polarization of specimens with fiber length of 35 mm were similar to those of 60 mm. In addition the open circuit potentials of specimens with fiber length of 60 mm were slightly higher that those of 35 mm. The resistivity decreased with increasing steel fiber content, and the open circuit potential and direct current polarization increased with increasing steel fiber content. The specimens containing silica fume were found to provide higher resistivity, open circuit potentials and direct current polarization than the control specimens. The incorporation of steel fiber and silica fume in composites achieved more significantly decreases in resistivity and increases in direct current polarization than steel fiber composites or silica fume composites. The penetration depth and six-hour total charge passed of specimens for w/b ratio of 0.35 were lower than those for w/b ratio of 0.55. For length-diameter ratio of 65, the penetration depth of specimens for fiber length of 35 mm was similar to that of 60 mm. The penetration depth decreased with increased steel fiber content in the composites. By regression analysis, a good correlation between open circuit potential and direct current polarization, and chloride penetration depth and direct current polarization.

Strain Measurement for Hollow Projectiles During Its Penetration of Concrete Targets

Gives a new technique to measure the dynamic deformation behavior and strain development of a hollow steel projectile during its penetration of concrete targets. Direct strain measurement was performed by applying strain gages attached to the inner walls of the hollow projectile, linked with on-board testing and storage recorder. This on-board test-record system is easy to operate, cost-effective and can provide reasonable, accurate and detailed information. Obverse ballistic experiments were carried out on ogival-nose hollow projectiles normally impacting concrete targets at velocities from 150 m/s to 300 m/s. The deformation process of projectiles was measured, recorded and played back. Profiles of voltage-time relationship were successively obtained and transfered to strain-time relationship with the aid of calibration tables. It was found that projectiles go through a series of compression and tension deformations intermittently. Relationships between strain development and projectile deformation process were discussed.