Can whole steps of grain production be outsourced? Empirical analysis based on the three provinces of Jiangsu,Jilin,and Sichuan in China

Certain outsourcing services for agricultural management in China,such as pest control in grain production,have experienced prolonged sluggishness,contrasting with the relatively high level of outsourcing services observed in harvesting,land preparation,and sowing.This study examines the feasibility of implementing whole-step outsourcing in grain production by conducting a case study of rice and maize production in Jiangsu,Jilin,and Sichuan provinces in China.The provision of outsourcing services hinges on two essential conditions:technological advancements fostering specialized production and economies of scale,coupled with a market size sufficient to realize the aforementioned potential economies of scale.The results showed that outsourcing pest control or harvesting services had varying economies of scale.The outsourcing services in pest control were less common than in harvesting services,and their marginal growth space of the economies of scale with technological change was also smaller.Determined by the operational characteristics of pest control itself,the market scale of its professional services is small.Therefore,achieving the whole-step outsourcing of grain production necessitates not only technological innovation but also effective policy interventions to overcome the constraints of market scale.Such interventions include(1)optimizing crop layouts between planning regions and reducing land fragmentation and(2)supplying timely and effective inter-regional agricultural information for service providers aided by information technology.

Outsourced Privacy-Preserving kNN Classifier Model Based on Multi-Key Homomorphic Encryption

Outsourcing the k-Nearest Neighbor(kNN)classifier to the cloud is useful,yet it will lead to serious privacy leakage due to sensitive outsourced data and models.In this paper,we design,implement and evaluate a new system employing an outsourced privacy-preserving kNN Classifier Model based on Multi-Key Homomorphic Encryption(kNNCM-MKHE).We firstly propose a security protocol based on Multi-key Brakerski-Gentry-Vaikuntanathan(BGV)for collaborative evaluation of the kNN classifier provided by multiple model owners.Analyze the operations of kNN and extract basic operations,such as addition,multiplication,and comparison.It supports the computation of encrypted data with different public keys.At the same time,we further design a new scheme that outsources evaluation works to a third-party evaluator who should not have access to the models and data.In the evaluation process,each model owner encrypts the model and uploads the encrypted models to the evaluator.After receiving encrypted the kNN classifier and the user’s inputs,the evaluator calculated the aggregated results.The evaluator will perform a secure computing protocol to aggregate the number of each class label.Then,it sends the class labels with their associated counts to the user.Each model owner and user encrypt the result together.No information will be disclosed to the evaluator.The experimental results show that our new system can securely allow multiple model owners to delegate the evaluation of kNN classifier.

A secure outsourced Turing- equivalent computation scheme against semi-honest workers using fully homomorphic encryption

A scheme that can realize homomorphic Turing- equivalent privacy-preserving computations is proposed, where the encoding of the Turing machine is independent of its inputs and running time. Several extended private information retrieval protocols based on fully homomorphic encryption are designed, so that the reading and writing of the tape of the Turing machine, as well as the evaluation of the transition function of the Turing machine, can be performed by the permitted Boolean circuits of fully homomorphic encryption schemes. This scheme overwhelms the Turing-machine-to- circuit conversion approach, which also implements the Turing-equivalent computation. The encoding of a Turing- machine-to-circuit conversion approach is dependent on both the input data and the worst-case runtime. The proposed scheme efficiently provides the confidentiality of both program and data of the delegator in the delegator-worker model of outsourced computation against semi-honest workers.

TPTVer： A Trusted Third Party Based Trusted Verifier for Multi-Layered Outsourced Big Data System in Cloud Environment

Cloud computing is very useful for big data owner who doesn't want to manage IT infrastructure and big data technique details. However, it is hard for big data owner to trust multi-layer outsourced big data system in cloud environment and to verify which outsourced service leads to the problem. Similarly, the cloud service provider cannot simply trust the data computation applications. At last,the verification data itself may also leak the sensitive information from the cloud service provider and data owner. We propose a new three-level definition of the verification, threat model, corresponding trusted policies based on different roles for outsourced big data system in cloud. We also provide two policy enforcement methods for building trusted data computation environment by measuring both the Map Reduce application and its behaviors based on trusted computing and aspect-oriented programming. To prevent sensitive information leakage from verification process,we provide a privacy-preserved verification method. Finally, we implement the TPTVer, a Trusted third Party based Trusted Verifier as a proof of concept system. Our evaluation and analysis show that TPTVer can provide trusted verification for multi-layered outsourced big data system in the cloud with low overhead.

Software outsourcing risk management: establishing outsourcee evaluation item systems

Outsourcing software development has many advantages as well as inevitable risks. Of these risks, outsourcee se-lection is one of the most important. A wrong outsourcee selection may have severe adverse influence on the expected outcome of the project. We analyzed the risks involved in outsourcee selection and also provided methods to identify these risks. Using the principles of Analytical Hierarchy Process (AHP) and Cluster Analysis based on Group Decision Making, we established an index evaluation system to evaluate and select outsourcees. Real world applications of this system demonstrated its effectiveness in evaluating and selecting qualified outsourcees.

A Scheme for Verifying the Integrity of Outsourced Data

Unauthorized tampering with outsourced data can result in significant losses for both data owner and users.Data integrity therefore becomes an important factor in outsourced data systems.In this paper,we address this problem and propose a scheme for verifying the integrity of outsourced data.We first propose a new authenticated data structure for authenticating membership queries in sets based on accumulators,and then show how to apply it to the problem of verifying the integrity of outsourced data.We also prove that our scheme is secure under the q-strong DiffieHellman assumption.More importantly,our scheme has the constant cost communication,meanwhile keeping other complexity measures constant.Compared to previous schemes based on accumulators,our scheme reduces update cost and so improves previous schemes based on accumulators.In addition,the experimental comparison shows that our scheme outperforms the previous schemes.

(r,QI)-Transform：Reversible Data Anonymity Based on Numeric Type of Data in Outsourced Database

An outsource database is a database service provided by cloud computing companies.Using the outsource database can reduce the hardware and software＇s cost and also get more efficient and reliable data processing capacity.However,the outsource database still has some challenges.If the service provider does not have sufficient confidence,there is the possibility of data leakage.The data may has user＇s privacy,so data leakage may cause data privacy leak.Based on this factor,to protect the privacy of data in the outsource database becomes very important.In the past,scholars have proposed k-anonymity to protect data privacy in the database.It lets data become anonymous to avoid data privacy leak.But k-anonymity has some problems,it is irreversible,and easier to be attacked by homogeneity attack and background knowledge attack.Later on,scholars have proposed some studies to solve homogeneity attack and background knowledge attack.But their studies still cannot recover back to the original data.In this paper,we propose a data anonymity method.It can be reversible and also prevent those two attacks.Our study is based on the proposed r-transform.It can be used on the numeric type of attributes in the outsource database.In the experiment,we discussed the time required to anonymize and recover data.Furthermore,we investigated the defense against homogeneous attack and background knowledge attack.At the end,we summarized the proposed method and future researches.

FACOR：Flexible Access Control with Outsourceable Revocation in Mobile Clouds

Access control is a key mechanism to secure outsourced data in mobile clouds. Some existing solutions are proposed to enforce flexible access control on outsourced data or reduce the computations performed by mobile devices. However, less attention has been paid to the efficiency of revocation when there are mobile devices needed to be revoked. In this paper, we put forward a new solution, referred to as flexible access control with outsourceable revocation(FACOR) for mobile clouds. The FACOR applies the attribute-based encryption to enable flexible access control on outsourced data, and allows mobile users to outsource the time-consuming encryption and decryption computations to proxies, with only requiring attributes authorization to be fully trusted. As an advantageous feature, FACOR provides an outsourceable revocation for mobile users to reduce the complicated attribute-based revocation operations. The security analysis shows that our FACOR scheme achieves data security against collusion attacks and unauthorized accesses from revoked users. Both theoretical and experimental results confirm that our proposed scheme greatly reliefs the mobile devices from heavy encryption and decryption computations, as well as the complicated revocation of access rights in mobile clouds.

DBT-PDP:Provable data possession with outsourced data batch transfer based on blockchain

In the scenario of large-scale data ownership transactions,existing data integrity auditing schemes are faced with security risks from malicious third-party auditors and are inefficient in both calculation and communication,which greatly affects their practicability.This paper proposes a data integrity audit scheme based on blockchain where data ownership can be traded in batches.A data tag structure which supports data ownership batch transaction is adopted in our scheme.The update process of data tag does not involve the unique information of each data,so that any user can complete ownership transactions of multiple data in a single transaction through a single transaction auxiliary information.At the same time,smart contract is introduced into our scheme to perform data integrity audit belongs to third-party auditors,therefore our scheme can free from potential security risks of malicious third-party auditors.Safety analysis shows that our scheme is proved to be safe under the stochastic prediction model and k-CEIDH hypothesis.Compared with similar schemes,the experiment shows that communication overhead and computing time of data ownership transaction in our scheme is lower.Meanwhile,the communication overhead and computing time of our scheme is similar to that of similar schemes in data integrity audit.

SEOT: Secure dynamic searchable encryption with outsourced ownership transfer

When one enterprise acquires another,the electronic data of the acquired enterprise will be transferred to the acquiring enterprise.In particular,if the data system of acquired enterprise contains a searchable encryption mechanism,the corresponding searchability will also be transferred.In this paper,we introduce the concept of Searchable Encryption with Ownership Transfer(SEOT),and propose a secure SEOT scheme.Based on the new structure of polling pool,our proposed searchable encryption scheme not only achieves efficient transfer of outsourced data,but also implements secure transfer of data searchability.Moreover,we optimize the storage cost for user to a desirable value.We prove our scheme can achieve the secure characteristics,then carry out the performance evaluation and experiments.The results demonstrate that our scheme is superior in efficiency and practicability.

Lightning-fast and privacy-preserving outsourced computation in the cloud

In this paper,we propose a framework for lightning-fast privacy-preserving outsourced computation framework in the cloud,which we refer to as LightCom.Using LightCom,a user can securely achieve the outsource data storage and fast,secure data processing in a single cloud server different from the existing multi-server outsourced computation model.Specifically,we first present a general secure computation framework for LightCom under the cloud server equipped with multiple Trusted Processing Units(TPUs),which face the side-channel attack.Under the LightCom,we design two specified fast processing toolkits,which allow the user to achieve the commonly-used secure integer computation and secure floating-point computation against the side-channel information leakage of TPUs,respectively.Furthermore,our LightCom can also guarantee access pattern protection during the data processing and achieve private user information retrieve after the computation.We prove that the proposed LightCom can successfully achieve the goal of single cloud outsourced data processing to avoid the extra computation server and trusted computation server,and demonstrate the utility and the efficiency of LightCom using simulations.

Strategic Contracting for Software Upgrade Outsourcing in Industry 4.0

The advent of Industry 4.0 has compelled businesses to adopt digital approaches that combine software toenhance production efficiency. In this rapidly evolving market, software development is an ongoing process thatmust be tailored to meet the dynamic needs of enterprises. However, internal research and development can beprohibitively expensive, driving many enterprises to outsource software development and upgrades to externalservice providers. This paper presents a software upgrade outsourcing model for enterprises and service providersthat accounts for the impact of market fluctuations on software adaptability. To mitigate the risk of adverseselection due to asymmetric information about the service provider’s cost and asymmetric information aboutthe enterprise’s revenues, we propose pay-per-time and revenue-sharing contracts in two distinct informationasymmetry scenarios. These two contracts specify the time and transfer payments for software upgrades. Througha comparative analysis of the optimal solutions under the two contracts and centralized decision-making withfull-information, we examine the characteristics of the solutions under two information asymmetry scenarios andanalyze the incentive effects of the two contracts on the various stakeholders. Overall, our study offers valuableinsights for firms seeking to optimize their outsourcing strategies and maximize their returns on investment insoftware upgrades.

Trusted Certified Auditor Using Cryptography for Secure Data Outsourcing and Privacy Preservation in Fog-Enabled VANETs

With the recent technological developments,massive vehicular ad hoc networks(VANETs)have been established,enabling numerous vehicles and their respective Road Side Unit(RSU)components to communicate with oneanother.The best way to enhance traffic flow for vehicles and traffic management departments is to share thedata they receive.There needs to be more protection for the VANET systems.An effective and safe methodof outsourcing is suggested,which reduces computation costs by achieving data security using a homomorphicmapping based on the conjugate operation of matrices.This research proposes a VANET-based data outsourcingsystem to fix the issues.To keep data outsourcing secure,the suggested model takes cryptography models intoaccount.Fog will keep the generated keys for the purpose of vehicle authentication.For controlling and overseeingthe outsourced data while preserving privacy,the suggested approach considers the Trusted Certified Auditor(TCA).Using the secret key,TCA can identify the genuine identity of VANETs when harmful messages aredetected.The proposed model develops a TCA-based unique static vehicle labeling system using cryptography(TCA-USVLC)for secure data outsourcing and privacy preservation in VANETs.The proposed model calculatesthe trust of vehicles in 16 ms for an average of 180 vehicles and achieves 98.6%accuracy for data encryption toprovide security.The proposedmodel achieved 98.5%accuracy in data outsourcing and 98.6%accuracy in privacypreservation in fog-enabled VANETs.Elliptical curve cryptography models can be applied in the future for betterencryption and decryption rates with lightweight cryptography operations.

Access control scheme with tracing for outsourced databases

To manage dynamic access control and deter pi- rate attacks on outsourced databases, a dynamic access control scheme with tracing is proposed. In our scheme, we introduce the traitor tracing idea into outsource databases, and employ a polynomial function and filter function as the basic means of constructing encryption and decryption procedures to reduce computation, communication, and storage overheads. Compared to previous access control schemes for outsourced databases, our scheme can not only protect sensitive data from leaking and perform scalable encryption at the server side without shipping the outsourced data back to the data owner when group membership is changed, but also provide trace-and-revoke features. When malicious users clone and sell their decryption keys for profit, our scheme can trace the decryption keys to the malicious users and revoke them. Furthermore, our scheme avoids massive message exchanges for establishing the decryption key between the data owner and the user. Compared to previously proposed publickey traitor tracing schemes, our scheme can simultaneously achieve full collusion resistance, full recoverability, full revocation, and black-box traceability. The proof of security and analysis of performance show that our scheme is secure and efficient.

Research on the Status Quo and Countermeasures of Human Resource Management Outsourcing in China’s Pharmaceutical Enterprises

Objective To explore the current situation of human resource management outsourcing in China’s pharmaceutical enterprises,and to put forward some suggestions for enterprises and the government.Methods The current situation of human resource management outsourcing in China’s pharmaceutical enterprises was analyzed through the method of literature research.Results and Conclusion At present,the status of human resource management outsourcing in China’s pharmaceutical companies is that the level of human resource outsourcing companies is not high,and there are no relevant industry norms and laws.The information asymmetry between pharmaceutical enterprises and outsourcing companies results in adverse selection and moral hazard.Besides,the different culture of pharmaceutical enterprises and outsourcing companies leads to inefficient communication between enterprises and employee.To solve these problems,the government should promote and improve industry norms and laws to regulate the market.In addition,enterprises should clarify the motivation for outsourcing and make good decision on the outsourcing content.Meanwhile,enterprises should strengthen communication with employees to eliminate employees’concerns.

Lightning-fast and privacy-preserving outsourced computation in the cloud

In this paper,we propose a framework for lightning-fast privacy-preserving outsourced computation framework in the cloud,which we refer to as LightCom.Using LightCom,a user can securely achieve the outsource data storage and fast,secure data processing in a single cloud server different from the existing multi-server outsourced computation model.Specifically,we first present a general secure computation framework for LightCom under the cloud server equipped with multiple Trusted Processing Units(TPUs),which face the side-channel attack.Under the LightCom,we design two specified fast processing toolkits,which allow the user to achieve the commonly-used secure integer computation and secure floating-point computation against the side-channel information leakage of TPUs,respectively.Furthermore,our LightCom can also guarantee access pattern protection during the data processing and achieve private user information retrieve after the computation.We prove that the proposed LightCom can successfully achieve the goal of single cloud outsourced data processing to avoid the extra computation server and trusted computation server,and demonstrate the utility and the efficiency of LightCom using simulations.

OUTSOURCE TO AN OEM OR AN ODM？ PROFITABILITY AND SUSTAINABILITY ANALYSIS OF A FASHION SUPPLY CHAIN

Consider a fashion supply chain comprising a supplier, a contract manufacturer and a fashion brand, we examine the fashion brand＇s profit performances when the contract manufacturer is either an OEM （having no design capability） or an ODM （having design capability）. Regarding OEM, the fashion brand designs the products, outsources the manufacturing function, and has the option of outsourcing procurement function. Regarding ODM, the fashion brand buys unlabeled products from the ODM, which is charge of designing and manufacturing. In this case, buy-back contract is widely adopted so as to share the risk of demand uncertainty between the ODM and the fashion brand. We solve the wholesale pricing problems via sequential/simultaneous optimization, and derive the buy-back price via generalize Nash bargaining. We find that, fashion brand prefers contracting with an ODM when its bargaining power in buy-back negotiation is larger than a threshold, although the fashion brand＇s order size under ODM is always larger than that under OEM. Interestingly, we find that the buy-back price is decreasing in the fashion brand＇s bargaining power. We further analyze the supply chain sustainability in both ODM and OEM scenarios, fmding that the supply chain might achieve both environmental sustainability and economic sustainability in OEM scenario when the fashion brand＇s bargaining power in buy-back negotiation is small.

CAPACITY ALLOCATION AND COORDINATION ISSUES FOR THE TIMELY PROCESSING OF OUTSOURCED OPERATIONS

We consider dynamic capacity booking problems faced by multiple manufacturers each outsourcing certain operations to a common third-party firm. Each manufacturer, upon observing the current state of the third-party schedule, books capacity with the objective to jointly minimize holding costs that result from early deliveries, tardiness penalties due to late deliveries, and third-party capacity booking costs. When making a reservation, each manufacturer evaluates two alternative courses of action： （i） reserving capacity not yet utilized by other manufactures who booked earlier; or （ii） forming a coalition with a subset or all of other manufacturers to achieve a schedule minimizing coalition costs, i.e., a centralized schedule for that coalition. The latter practice surely benefits the coalition as a whole; however, some manufacturers may incur higher costs if their operations are either pushed back too much, or delivered too early. For this reason, a cost allocation scheme making each manufacturer no worse than they would be when acting differently （i.e., participating in a smaller coalition or acting on their own behalf,） must accompany centralized scheduling for the coalition. We model this relationship among the manufacturers as a cooperative game with transferable utility, and present optimal and/or heuristic algorithms to attain individually and eoalitionally optimal schedules as well as a linear program formulation to find a core allocation of the manufacturers＇ costs.

Towards privacy-preserving dynamic deep packet inspection over outsourced

The prosperity of network function virtualization(NFV)pushes forward the paradigm of migrating in-house middleboxes to third-party providers,i.e.,software(virtualized)middlebox services.A lot of enterprises have outsourced traffic processing such as deep packet inspection(DPI),traffic classification,and load balancing to middleboxes provided by cloud providers.However,if the traffic is forwarded to the cloud provider without careful processing,it will cause privacy leakage,as the cloud provider has all the rights to access the data.To solve the security issue,recent efforts are made to design secure middleboxes that can directly conduct network functions over encrypted traffic and middlebox rules.However,security concerns from dynamic operations like dynamic DPI and rule updates are still not yet fully addressed.In this paper,we propose a privacy-preserving dynamic DPI scheme with forward privacy for outsourced middleboxes.Our design can enable cloud side middlebox to conduct secure packet inspection over encrypted traffic data.Besides,the middlebox providers cannot analyze the relationship between the newly added rules and the previous data.Several recent papers have proven that it is a strong property that resist adaptive attacks.Furthermore,we design a general method to inspect stateful packets while still ensuring the state privacy protection.We formally define and prove the security of our design.Finally,we implement a system prototype and analyze the performance from experimental aspects.The evaluation results demonstrate our scheme is effective and efficient.

Verifiable Auditing Protocol with Proxy Re-Encryption for Outsourced Databases in Cloud

As a new computing paradigm, outsourcing computing provides inexpensive, on-demand, convenient storage and computing services for cloud clients. For the security of outsourcing databases to the cloud, it is important to allow the user to verify the query results returned by the cloud server. So far, tremendous efforts have been carried out to study secure outsourcing computing. The existing scheme supports that the user can detect the correctness and completeness of the query results even if the cloud server returns an empty set. However, since the data owner performs the database encryption operations and uploads the encrypted database to the cloud server, they require the user to request the data owner to decrypt the query results. In this paper, we propose a new scheme, which can accurately verify the search results. Meanwhile, the users can decrypt the query results independently. Furthermore, the proposed scheme supports a large number of data owners to upload their encrypted database to the cloud server, and it can efficiently verify the query results. Besides, we can prove that our proposed solution can achieve the desired security properties.