Practical SM2-Based Multisignature Scheme with Applications to Vehicular Networks

In vehicular networks, the increasing value of transportation data and scale of connectivity also brings many security and privacy concerns. Peer authentication and message integrity are two vital security requirements to ensure safe transportation system. Because of the constrained resources of the units performing the cryptographic components, the proposed security-enhancing schemes should be lightweight and scalable. In this paper, we present a multisignature scheme derived from the SM2 signature which enables a group of parties to collaboratively sign a message and generate a compact joint signature at the end. Our scheme requires no preprocessing or interactions among the parties before signing, and its performance matches or surpasses known ones in terms of signing time, verification time, and signature size. Therefore, our scheme is also suitable for vehicular networks, with the goal to enhance security with small computation and storage cost.

Single node repair algorithm for a multimedia cloud storage system based on network coding

Multimedia is inconvenient to use, difficult to maintain, and redundant in data storage. In order to solve the above problems and apply cloud storage to the integration of university teaching resources, this paper designs a virtualized cloud storage platform for university multimedia classrooms. The platform has many advantages, such as reducing the initial investment in multimedia classrooms, simplifying management tasks, making maximum use of actual resources and easy access to resources. Experiments and analysis show the feasibility and effectiveness of the platform. Aiming at the problems of the single-node repair algorithm of the existing multimedia cloud storage system, the limited domain is large, the codec complexity is high, the disk I/O (Input/Output) cost is high, the storage overhead and the repair bandwidth are unbalanced, and a network coding-based approach is proposed. Multimedia cloud storage. System single node repair algorithm. The algorithm stores the grouped multimedia file data in groups in the system, and performs XOR (exclusive OR) on the data in the group on the GF(2) finite field. When some nodes fail, the new node only needs to be connected. Two to three non-faulty nodes in the same group can accurately repair the data in the failed node. Theoretical analysis and simulation results show that the algorithm can reduce the complexity and repair of the codec, and reduce the disk I/O overhead. In this case, the storage cost of the algorithm is consistent with the storage cost based on the minimum storage regeneration code algorithm, and the repair bandwidth cost is close to the minimum bandwidth regeneration code algorithm.

Pengendalian Stok Spareparts Mobil Dengan Metode EOQ dan Min-Max Inventory

This research was conducted in the distributor of car spare parts and the object studied was car glass glue. This item is a product that experiences a stacking stock in the warehouse, so it needs inventory control to reduce the stacking stock. The character of the product which does not have expired date as long as it is not used and small size, the company never make an optimal estimate of the order, so the activity of ordering goods is only based on its own estimates. The method used in this research is EOQ to obtain the economical amount of the product to be ordered. The calculation process using EOQ method is done against 2019 sales data predicted to 2021 using Trend Linear forecasting method, with function form is Y=1,8776x+256,21. Furthermore, the minimum and maximum stock quantity is determined using the Min-Max Inventory method. From the result of the study found that the economic Q per ordered is 386 pcs with the frequency of bookings 8 times a year. The minimum inventory is 108 pcs and the maximum is 144 pcs with the amount of safety stock is 72 pcs and ROP is 108 pcs. By using EOQ method, the company can make savings of Rp3,939,330 per year and reduce storage cost by Rp10,119,635 per year.

Theory and application of encrypted sequential data processing: search and computation

Cloud Computing has seen a dramatic rise in adoption in the past decade amid se- curity and privacy concerns. One area of consensus is that encryption is necessary, as anonymization techniques have been shown to be unreliable. However, the processing of encrypted data has proven to be difficult. Briefly, the goal is to maintain security over remotely stored and accessed data while achieving reasonable storage cost and perfor- mance. Search is the most basic and central functionality of a privacy-protected cloud storage system actively being investigated. Recent works have looked at enabling more specialized search functions. In this thesis, we explore the problem of searching and pro- cessing of sequential data. We propose three solutions targeting textual data, with em- phasis respectively on security, storage cost and performance. Our first solution achieves a high level of security with reduced communication, storage and computational cost by exploiting properties of natural languages. Our second solution achieves a minimal storage cost by taking advantage of the space efficiency of Bloom filters. Both propos- als were also first to enable non-keyword search in phrases. Using a subsequence-based solution, our final phrase search scheme is currently the fastest phrase search protocol in literature. We also show how sequential data search schemes can be extended to in- clude auditing with minimal additional cost. The solution is capable of achieving proof of retrievability with unbounded number of audits. A sample application which enables searching and computing over target values of encrypted XML files is also demonstrated. In terms of media, we describe an encrypted cloud media storage solution that simultane- ously protects user privacy and enables copyright verification, and is the first to achieve security against dishonest participants. We also describe a framework where practical scalable privacy-protected copyright detection can be performed. Finally, an application of sequence querying over generic data in the form of an Anti-Virus over encrypted cloud storage is demonstrated. A private scanning solution and a public Anti-Virus as a ser- vice solution are described, noting that the technique can be conceptualized as a generic pattern matching solution on encrypted data. We also include some directions on future work and unexplored applications.

Theory and application of encrypted sequential data processing: search and computation

Cloud Computing has seen a dramatic rise in adoption in the past decade amid se- curity and privacy concerns. One area of consensus is that encryption is necessary, as anonymization techniques have been shown to be unreliable. However, the processing of encrypted data has proven to be difficult. Briefly, the goal is to maintain security over remotely stored and accessed data while achieving reasonable storage cost and perfor- mance. Search is the most basic and central functionality of a privacy-protected cloud storage system actively being investigated. Recent works have looked at enabling more specialized search functions. In this thesis, we explore the problem of searching and pro- cessing of sequential data. We propose three solutions targeting textual data, with em- phasis respectively on security, storage cost and performance. Our first solution achieves a high level of security with reduced communication, storage and computational cost by exploiting properties of natural languages. Our second solution achieves a minimal storage cost by taking advantage of the space efficiency of Bloom filters. Both propos- als were also first to enable non-keyword search in phrases. Using a subsequence-based solution, our final phrase search scheme is currently the fastest phrase search protocol in literature. We also show how sequential data search schemes can be extended to in- clude auditing with minimal additional cost. The solution is capable of achieving proof of retrievability with unbounded number of audits. A sample application which enables searching and computing over target values of encrypted XML files is also demonstrated. In terms of media, we describe an encrypted cloud media storage solution that simultane- ously protects user privacy and enables copyright verification, and is the first to achieve security against dishonest participants. We also describe a framework where practical scalable privacy-protected copyright detection can be performed. Finally, an application of sequence querying over generic data in the form of an Anti-Virus over encrypted cloud storage is demonstrated. A private scanning solution and a public Anti-Virus as a ser- vice solution are described, noting that the technique can be conceptualized as a generic pattern matching solution on encrypted data. We also include some directions on future work and unexplored applications.