Technical methods of national security supervision:Grain storage security as an example

Grain security guarantees national security.China has many widely distributed grain depots to supervise grain storage security.However,this has led to a lack of regulatory capacity and manpower.Amid the development of reserve-level information technology,big data supervision of grain storage security should be improved.This study proposes big data research architecture and an analysis model for grain storage security;as an example,it illustrates the supervision of the grain loss problem in storage security.The statistical analysis model and the prediction and clustering-based model for grain loss supervision were used to mine abnormal data.A combination of feature extraction and feature selection reduction methods were chosen for dimensionality.A comparative analysis showed that the nonlinear prediction model performed better on the grain loss data set,with R2 of 87.21%,87.83%,91.97%,and 89.40%for Gradient Boosting Regressor(GBR),Random Forest,Decision Tree,XGBoost regression on test sets,respectively.Nineteen abnormal data were filtered out by GBR combined with residuals as an example.The deep learning model had the best performance on the mean absolute error,with an R2 of 85.14%on the test set and only one abnormal data identified.This is contrary to the original intention of finding as many anomalies as possible for supervisory purposes.Five classes were generated using principal component analysis dimensionality reduction combined with Density-Based Spatial Clustering of Applications with Noise(DBSCAN)clustering,with 11 anomalous data points screened by adding the amount of normalized grain loss.Based on the existing grain information system,this paper provides a supervision model for grain storage that can help mine abnormal data.Unlike the current post-event supervision model,this study proposes a pre-event supervision model.This study provides a framework of ideas for subsequent scholarly research;the addition of big data technology will help improve efficient supervisory capacity in the field of grain supervision.

A Lightweight Approach(BL-DAC)to Secure Storage Sharing in Cloud-IoT Environments

The growing advent of the Internet of Things(IoT)users is driving the adoption of cloud computing technologies.The integration of IoT in the cloud enables storage and computational capabilities for IoT users.However,security has been one of the main concerns of cloud-integrated IoT.Existing work attempts to address the security concerns of cloud-integrated IoT through authentication,access control,and blockchain-based methods.However,existing frameworks are somewhat limited by scalability,privacy,and centralized structures.To mitigate the existing problems,we propose a blockchain-based distributed access control method for secure storage in the IoT cloud(BL-DAC).Initially,the BL-DAC performs decentralized authentication using the Quantum Neural Network Cryptography(QNNC)algorithm.IoT users and edge nodes are authenticated in the blockchain deployed by distributed Trusted Authorities(TAs)using multiple credentials.The user data is classified into sensitive and non-sensitive categories using the Enhanced Seagull Optimization(ESO)algorithm.Also,the authentication to access this data is performed by a decentralized access control method using smart contract policy.Sensitive user data is encrypted using the QNNC algorithm and stored in the private cloud.In contrast,non-sensitive data is stored in the public cloud,and IPFS is used to store data in a decentralized manner with high reliability.In addition,data security is improved by using a hierarchical blockchain which improves scalability by managing the multiple blockchains hierarchically and is lightweight using Proof of Authentication Consensus(PoAH).The BL-DAC is simulated and validated using the Network Simulator-3.26 simulation tool and validated.This work shows better results than the compared ones in terms of validation metrics such as throughput(26%),encryption time(19%),decryption time(16%),response time(15%),block validation time(31%),attack detection rate(16%),access control precision(13%),and scalability(28%).

A Secure Microgrid Data Storage Strategy with Directed Acyclic Graph Consensus Mechanism

The wide application of intelligent terminals in microgrids has fueled the surge of data amount in recent years.In real-world scenarios,microgrids must store large amounts of data efficiently while also being able to withstand malicious cyberattacks.To meet the high hardware resource requirements,address the vulnerability to network attacks and poor reliability in the tradi-tional centralized data storage schemes,this paper proposes a secure storage management method for microgrid data that considers node trust and directed acyclic graph(DAG)consensus mechanism.Firstly,the microgrid data storage model is designed based on the edge computing technology.The blockchain,deployed on the edge computing server and combined with cloud storage,ensures reliable data storage in the microgrid.Secondly,a blockchain consen-sus algorithm based on directed acyclic graph data structure is then proposed to effectively improve the data storage timeliness and avoid disadvantages in traditional blockchain topology such as long chain construction time and low consensus efficiency.Finally,considering the tolerance differences among the candidate chain-building nodes to network attacks,a hash value update mechanism of blockchain header with node trust identification to ensure data storage security is proposed.Experimental results from the microgrid data storage platform show that the proposed method can achieve a private key update time of less than 5 milliseconds.When the number of blockchain nodes is less than 25,the blockchain construction takes no more than 80 mins,and the data throughput is close to 300 kbps.Compared with the traditional chain-topology-based consensus methods that do not consider node trust,the proposed method has higher efficiency in data storage and better resistance to network attacks.

Multi-authority proxy re-encryption based on CPABE for cloud storage systems

The dissociation between data management and data ownership makes it difficult to protect data security and privacy in cloud storage systems.Traditional encryption technologies are not suitable for data protection in cloud storage systems.A novel multi-authority proxy re-encryption mechanism based on ciphertext-policy attribute-based encryption（MPRE-CPABE） is proposed for cloud storage systems.MPRE-CPABE requires data owner to split each file into two blocks,one big block and one small block.The small block is used to encrypt the big one as the private key,and then the encrypted big block will be uploaded to the cloud storage system.Even if the uploaded big block of file is stolen,illegal users cannot get the complete information of the file easily.Ciphertext-policy attribute-based encryption（CPABE）is always criticized for its heavy overload and insecure issues when distributing keys or revoking user＇s access right.MPRE-CPABE applies CPABE to the multi-authority cloud storage system,and solves the above issues.The weighted access structure（WAS） is proposed to support a variety of fine-grained threshold access control policy in multi-authority environments,and reduce the computational cost of key distribution.Meanwhile,MPRE-CPABE uses proxy re-encryption to reduce the computational cost of access revocation.Experiments are implemented on platforms of Ubuntu and CloudSim.Experimental results show that MPRE-CPABE can greatly reduce the computational cost of the generation of key components and the revocation of user＇s access right.MPRE-CPABE is also proved secure under the security model of decisional bilinear Diffie-Hellman（DBDH）.

HermitFS: A Secure Storage System in theOpen Environment

We present a secure storage system named HermitFS against many types ofattacks. HermitFS uses strong cryptography algorithms and a secure protocol to secure the data fromthe time it is written to the time an authorized user accesses it. Our experimental results andsecure analysis show that HermitFS can protect information from unauthorized access in any openenvironment with little penalty of data o-verhead and acceptable performance.

Research on medical data storage and sharing model based on blockchain

With the process of medical informatization,medical diagnosis results are recorded and shared in the form of electronic data in the computer.However,the security of medical data storage cannot be effectively protected and the unsafe sharing of medical data among different institutions is still a hidden danger that cannot be underestimated.To solve the above problems,a secure storage and sharing model of private data based on blockchain technology and homomorphic encryption is constructed.Based on the idea of blockchain decentralization,the model maintains a reliable medical alliance chain system to ensure the safe transmission of data between different institutions;A privacy data encryption and computing protocol based on homomorphic encryption is constructed to ensure the safe transmission of medical data;Using its complete anonymity to ensure the Blockchain of medical data and patient identity privacy;A strict transaction control management mechanism of medical data based on Intelligent contract automatic execution of preset instructions is proposed.After security verification,compared with the traditional medical big data storage and sharing mode,the model has better security and sharing.

Lightweight and Compromise Resilient Storage Outsourcing with Distributed Secure Accessibility in Mobile Cloud Computing

Mobile Cloud Computing usually consists of front-end users who possess mobile devices and back-end cloud servers. This paradigm empowers users to pervasively access a large volume of storage resources with portable devices in a distributed and cooperative manner. During the period between uploading and downloading files （data）, the privacy and integrity of files need to be guaranteed. To this end, a family of schemes are proposed for different situations. All schemes are lightweight in terms of computational overhead, resilient to storage compromise on mobile devices, and do not assume that trusted cloud servers are present. Corresponding algorithms are proposed in detail for guiding off-the-shelf implementation. The evaluation of security and performance is also extensively analyzed, justifying the applicability of the proposed schemes.

A novel DNA-inspired encryption strategy for concealing cloud storage

Over the last few years,the need of a cloud environment with the ability to detect illegal behaviours along with a secured data storage capability has increased largely.This study presents such a secured cloud storage framework comprising of a deoxyribonucleic acid(DNA)based encryption key which has been generated to make the framework unbreakable,thus ensuring a better and secured distributed cloud storage environment.Furthermore,this work proposes a novel DNA-based encryption technique inspired by the biological characteristics of DNA and the protein synthesis mechanism.The introduced DNA based model also has an additional advantage of being able to decide on selecting suitable storage servers from an existing pool of storage servers on which the data must be stored.A fuzzy-based technique for order of preference by similarity to ideal solution(TOFSIS)multi-criteria decisionmaking(MCDM)model has been employed to achieve the above-mentioned goal.This can decide the set of suitable storage servers and also results in a reduction in execution time by keeping up the level of security to an improved grade.This study also investigates and analyzes the strength of the proposed S-Box and encryption technique against some standard criteria and benchmarks,such as avalanche effect,correlation coefficient,information entropy,linear probability,and differential probability etc.After the avalanche effect analysis,the average change in cipher-text has been found to be 51.85%.Moreover,thorough security,sensitivity and functionality analysis show that the proposed scheme guarantees high security with robustness.

Searchable Encryption System for Big Data Storage

Big data cloud platforms provide users with on-demand configurable computing,storage resources to users,thus involving a large amount of user data.However,most of the data is processed and stored in plaintext,resulting in data leakage.At the same time,simple encrypted storage ensures the confidentiality of the cloud data,but has the following problems:if the encrypted data is downloaded to the client and then decrypted,the search efficiency will be low.If the encrypted data is decrypted and searched on the server side,the security will be reduced.Data availability is finally reduced,and indiscriminate protection measures make the risk of data leakage uncontrollable.To solve the problems,based on searchable encryption and key derivation,a cipher search system is designed in this paper considering both data security and availability,and the use of a search encryption algorithm that supports dynamic update is listed.Moreover,the system structure has the advantage of adapting different searchable encryption algorithm.In particular,a user-centered key derivation mechanism is designed to realize file-level fine-grained encryption.Finally,extensive experiment and analysis show that the scheme greatly improves the data security of big data platform.