Integrity Verification Techniques Research Articles

클라우드 에지 환경에서 블록체인 서명 키를 이용한 무결성 검증 기법

클라우드 에지 환경에서 블록체인 서명 키를 이용한 무결성 검증 기법

An improved lattice based certificateless data integrity verification techniques for cloud computing

An improved lattice based certificateless data integrity verification techniques for cloud computing

Data Integrity Verification in Cloud Computing

High security is one of the major obstacles for opening up the new era of the long dreamed vision of Cloud computing as a utility. In today’s trend of cloud computing, all the sensitive applications and data are moved towards cloud infrastructure and data center that run on virtual computing resources in the form of virtual machine. These attributes poses many security challenges such as accessibility vulnerabilities, virtualization vulnerabilities and web application vulnerabilities. We primarily aim to achieve better data integrity verification technique for Data Storage as a Service (Daas) in cloud computing and help users to recognize the threats associated with their uses.

Blockchain Assisted Optimal Machine Learning Based Cyberattack Detection and Classification Scheme

With recent advancements in information and communication technology, a huge volume of corporate and sensitive user data was shared consistently across the network, making it vulnerable to an attack that may be brought some factors under risk: data availability, confidentiality, and integrity. Intrusion Detection Systems (IDS) were mostly exploited in various networks to help promptly recognize intrusions. Nowadays, blockchain (BC) technology has received much more interest as a means to share data without needing a trusted third person. Therefore, this study designs a new Blockchain Assisted Optimal Machine Learning based Cyberattack Detection and Classification (BAOML-CADC) technique. In the BAOML-CADC technique, the major focus lies in identifying cyberattacks. To do so, the presented BAOML-CADC technique applies a thermal equilibrium algorithm-based feature selection (TEA-FS) method for the optimal choice of features. The BAOML-CADC technique uses an extreme learning machine (ELM) model for cyberattack recognition. In addition, a BC-based integrity verification technique is developed to defend against the misrouting attack, showing the innovation of the work. The experimental validation of BAOML-CADC algorithm is tested on a benchmark cyberattack dataset. The obtained values implied the improved performance of the BAOML-CADC algorithm over other techniques.

Concurrent and Robust End-to-End Data Integrity Verification Scheme for Flash-Based Storage Devices

The amount of data generated by scientific applications on high-performance computing systems is growing at an ever-increasing pace. Most of the generated data are transferred to storage in remote systems for various purposes such as backup, replication, or analysis. To detect data corruption caused by network or storage failures during data transfer, the receiver system verifies data integrity by comparing the checksum of the data. However, the internal operation of the storage device is not sufficiently investigated in the existing end-to-end integrity verification techniques. In this paper, we propose a concurrent and reliable end-to-end data integrity verification scheme considering the internal operation of the storage devices for data transfer between high-performance computing systems with flash-based storage devices. To perform data integrity verification including data corruptions that occurred inside the storage devices, we control the order of I/O operations considering the internal operations of the storage devices. Also, to prove the effectiveness of the proposed scheme, we devise a prototype that injects faults on the specific layer of the storage stack and examines detection of faults. We parallelize checksum computation and overlap it with I/O operations to mitigate the overhead caused by I/O reordering. The experimental results show that the proposed scheme reduces the entire data transfer time by up to 62% compared with the existing schemes while ensuring robust data integrity. With the prototype implementation, our scheme detects failures on NAND flash memory inside storage devices that cannot be detected with the existing schemes.

Blockchain-based cross-user data shared auditing

In cloud storage, public auditing is a more popular data integrity verification technique since it allows users to delegate auditing tasks to a fully trusted third-party auditor (TPA). However, it is difficult to find such a TPA in practical application. Besides, the centralised auditing model makes TPA have to bear burdensome work pressure, which limits the practicability of existing schemes. In this paper, we firstly proposed a blockchain-based generalised shared auditing mechanism BCSA in the cross-user scenario, which aims at achieving available public auditing with a non-fully trusted TPA, and reducing the user's auditing fees and TPA's work pressure by allowing data users to share their auditing procedure with others. Furthermore, we initialise a concrete construction BCSAD with Diffie–Hellman protocol for the cross-user auditing scenario with different data. Likewise, we also propose a novel construction BCSAI for the cross-user auditing scenario with identical data, which utilises a password-authenticated key exchange (PAKE) protocol to achieve shared auditing and ciphertext deduplication, reducing data storage and auditing fees for data users and alleviating service pressure on the cloud server and TPA. Security and performance analysis evaluate the practicability of the proposed scheme.

Multi-Blockchain-Based IoT Data Processing Techniques to Ensure the Integrity of IoT Data in AIoT Edge Computing Environments.

As the development of IoT technologies has progressed rapidly recently, most IoT data are focused on monitoring and control to process IoT data, but the cost of collecting and linking various IoT data increases, requiring the ability to proactively integrate and analyze collected IoT data so that cloud servers (data centers) can process smartly. In this paper, we propose a blockchain-based IoT big data integrity verification technique to ensure the safety of the Third Party Auditor (TPA), which has a role in auditing the integrity of AIoT data. The proposed technique aims to minimize IoT information loss by multiple blockchain groupings of information and signature keys from IoT devices. The proposed technique allows IoT information to be effectively guaranteed the integrity of AIoT data by linking hash values designated as arbitrary, constant-size blocks with previous blocks in hierarchical chains. The proposed technique performs synchronization using location information between the central server and IoT devices to manage the cost of the integrity of IoT information at low cost. In order to easily control a large number of locations of IoT devices, we perform cross-distributed and blockchain linkage processing under constant rules to improve the load and throughput generated by IoT devices.

Hierarchical Multipath Blockchain Based IoT Information Management Techniques for Efficient Distributed Processing of Intelligent IoT Information

As cloud technology advances, devices such as IoT (Internet of Things) are being utilized in various areas ranging from transportation, manufacturing, energy, automation, space, defense, and healthcare. As the number of IoT devices increases, the safety of IoT information, which is vulnerable to cyber attacks, is emerging as an important area of interest in distributed cloud environments. However, integrity techniques are not guaranteed to easily identify the integrity threats and attacks on IoT information operating in the distributed cloud associated with IoT systems and CPS (Cyber-Physical System). In this paper, we propose a blockchain-based integrity verification technique in which large amounts of IoT information processed in distributed cloud environments can be guaranteed integrity in security threats related to IoT systems and CPS. The proposed technique aims to ensure the integrity of IoT information by linking information from IoT devices belonging to subgroups in distributed cloud environments to information from specific non-adjacent IoT devices and blockchain. This is because existing techniques rely on third-party organizations that the data owner can trust to verify the integrity of the data. The proposed technique identifies IoT information by connecting the paths of IoT pre- and subsequent blocks into block chains so that synchronization can be achieved between subgroups in distributed cloud environments. Furthermore, the proposed technique uses probabilistic similarity information between IoT information blocks to react flexibly to subgroups that constitute distributed clouds so that IoT information blocks are not exploited maliciously by third parties. As a result of performance evaluation, the proposed technique averaged 12.3% improvement in integrity processing time over existing techniques depending on blockchain size. Furthermore, the proposed technique has to hash the IoT information that constitutes a subgroup with probability-linked information, validating the integrity of large-capacity IoT information, resulting in an average of 8.8% lower overhead than existing techniques. In addition, the proposed technique has an average improvement of 14.3% in blockchain-based integrity verification accuracy over existing techniques, depending on the hash chain length.

Merkle Tree and Blockchain-Based Cloud Data Auditing

Cloud computing is the fastest growing and most promising field in the service provisioning segment. It has become a challenging task to provide security in the cloud. The purpose of this article is to suggest a better and efficient integrity verification technique for data referred to as cloud audit. The deployment of cloud storage services has significant benefits in the management of data for users. However, this raises many security concerns, and one of them is data integrity. Though public verification techniques serve the purpose they are vulnerable to procrastinating auditors who may not perform verifications on time. In this article, a cloud data auditing system is proposed. The proposed cloud data auditing system integrates Merkle Tree-based Cloud audit and the blockchain-based audit recording system, thus the core idea is to record each verification result into a blockchain as a transaction. Utilizing the time-sensitive nature of blockchain, the verifications are time-stamped after the corresponding transaction is recorded into the blockchain, which enables users to check whether auditors have performed the verifications at the prescribed time. The proposed cloud data auditing system is experimentally validated. The investigations with varied dataset size revealed less time taken, on an average of 0.25 milliseconds with the use of Merkle Tree. Further results reveal consistency of the data integrity checking.

Patterned Cipher Block for Low-Latency Secure Communication

Despite the increasing importance of network security, increasing Internet of Things (IoT) uptake and traffic tends to apply tighter resource constraints for cryptography. To cope with the constraints, security systems must choose between time cost and security. Cyber-attack model evolution and quantum computing technologies have severely limited current cryptography uptake and imposed too much overhead to operate effectively on lightweight communication environments. Therefore, we propose a new operation mode using multiple symmetric key ciphers alternately in a regularized order. The proposed design exploits lightweight cryptography methods, reducing encryption/decryption overhead compared to a single heavy cryptography approach, as well as avoiding exhaustive key extraction attack. Since sequences can change both time cost and security performance widely, the design can be applied to various situations, from the delay-constrained communications to highly secure networks. Our cryptography design incorporates patterned cipher block (PCB) operation, an integrity verification technique to identify if a ciphertext has been forged, handshaking protocol exchanging pattern information and a key using two-round communication, and pattern optimization to maximize the cryptographic performance. We confirmed the proposed operation mode numerically, and verified the outcomes experimentally, confirming that the proposed scheme outperformed current best practice cryptography.

UC/OS-II 운영체제의 보안 개선을 위한 자체 코드 무결성 검증 기법

uC/OS-II 운영체제의 보안 개선을 위한 자체 코드 무결성 검증 기법

A generic approach for integrity verification of big data

Data integrity verification is a primary issue for the prominent and unchallenged success of Big Data. The large scale of data includes extra security overheads on customers that used Big Data services. In Big Data environment, many security challenges have pinched out such as data security, malicious insider attack, cyber attack, and abuse of data. In this paper, we have analyzed and identified a novel data integrity verification technique that provides better performance, efficiency, and quick review of Big Data. The milestone of our work are algebraic signature, homomorphic tag, and Combinatorial Batch Codes (CBC). Homomorphic tag delegates a special verifiable value to each data blocks. CBC allocates integral data to store on Big Data servers. This research work used multiple third-party auditors for batch auditing which ensure data integrity in a Big Data environment. Our approach handles single point failure error of single Third Party Auditor (TPA) efficiently. Without using any additional data structure, it supports dynamic data operations. The security and performance analysis with comparative results show the genuine application of our approach within the latest Big Data environment.

A curious collaborative approach for data integrity verification in cloud computing

Data integrity verification with high security and minimal overhead is a primary prerequisite for expansion of luminous generation and perception of cloud computing. In present revolution, all the precise data and applications have conveyed towards cloud infrastructure and data center, which run on virtual computing resources in the form of virtual machine. The large scale use of virtualization brings additional security overhead for tenants of a public cloud service. In this paper, we suggested a better and efficient data integrity verification technique that help users to utilize data as a service in cloud computing. The building blocks of our technique are algebraic signature, homomorphic tag, and combinatorial batch codes. Homomorphic tags are assigned a particular verifiable value to each data blocks, which can help us for unleashed data operations on this blocks. The property of algebraic signature is used to aggregate data blocks for file operations. Combinatorial batch codes are used to assign and store integrated data into different distributed cloud server. To demonstrate our approach, we implement an application based on Hadoop and MapReduce framework. We tested this application based on various parameters. Our method has shown the tremendous improvement over the other state of the art methods. The experimental results are demonstrating the effectiveness of the proposed method for data integrity verification.

Cloud Audit: A Data Integrity Verification Approach for Cloud Computing

Cloud computing is the fastest growing and promising field in the sector of service provision. It is a very trendy situation for security implementation in the Cloud. Thus, security restrictions are increasing on users and service providers as the growth of Cloud environment. The purpose of this paper is to suggest a better and efficient integrity verification technique for data (referred as “Cloud Audit”). The building blocks of our technique are a variant of the Paillier homomorphic cryptography system with homomorphic tag and combinatorial batch codes. A Paillier Homomorphic Cryptography (PHC) system used to obtain homomorphic encryption on data blocks. Homomorphic tags along with the Paillier cryptography system assigns a special verifiable value to each data block, which helps us in unleashing data operations on this block. Combinatorial batch codes are used to assign and store integral data into different distributed cloud sever. To demonstrate our approach, we have implemented an application based on Hadoop and MapReduce framework. We have tested this application based on various parameters. Effectiveness of the proposed method has been shown by the experimental results. Our method has shown large improvement over the other modern methods.

A Literature Survey on Integrity Verification Techniques

A Literature Survey on Integrity Verification Techniques

An Integrity Checking Mechanism Using Physical Independent Storage for Mobile Device

The dissemination of smartphones is rapidly progressing and there are many similarities of smartphones and PCs in terms of security risks. Recently, in mobile network environment, there is a trend of increasing damages and now, there are lots of active research on a system that can comprehensively respond to this. As a way to prevent these risks, integrity checking method on operation system is being researched. As most integrity checking algorithms are classified by verification from the levels before booting the OS and at the time of passing on the control to the OS, in which, there are minor differences in the definitions of integrity checking or its methods. This paper researched the verification techniques for OS integrity that can be more fatal than apps in case of security issues, and suggests the integrity verification technique of OS using a boot loader and a physically independent storing device in the terminal.

부트로더와 물리적으로 독립된 저장장치를 이용한 모바일 운영체제 무결성 검증

본 논문에서는 보안의 문제가 발생 할 경우 앱보다 치명적일 수 있는 운영체제 무결성에 대한 검증 기법에 대해 연구하였다.최근 스마트폰의 보급은 급속도로 발전하고 있으며, PC와 유사한 서비스를 제공하는 단계까지 왔다. 그리고 그에 따르는 보안 위협도 PC와 유사한 부분이 많다. 최근의 모바일 네트워크 환경에서 단말기의 루트 권한 탈취 및 운영체제 위변조 등에 의한 피해가 날로 늘어나고 있는 추세이며 이를 종합적으로 대응할 수 있는 시스템에 대한 연구가 필요하다. 모바일 위협에 대한 피해를 막기 위한 방법으로 운영체제의 무결성을 검사하는 방법이 사용되기도 한다. 무결성 검증 알고리즘은 운영체제 부팅 이전 레벨에서의 검증과 제어권이 운영체제로 넘어간 시점에서의 검증으로 구분될 수 있다. 무결성 검증은 앱 무결성과 운영체제 무결성으로 나뉘어 볼 수 있는데, 본 논문에서는 부트로더와 단말기 내부의 물리적으로 독립된 저장장치를 이용하여 운영체제의 무결성을 검증하는 기법을 제안하였다. In this paper, we study the verification techniques for OS integrity that can be more fatal than applications in case of security issues. The dissemination of smartphones is rapidly progressing and there are many similarities of smartphones and PCs in terms of security risks. Recently, in mobile network environment, there is a trend of increasing damages and now, there are active researches on a system that can comprehensively respond to this. As a way to prevent these risks, integrity checking method on operation system is being researched. As most integrity checking algorithms are classified by verification from the levels before booting the OS and at the time of passing on the control to the OS, in which, there are minor differences in the definitions of integrity checking or its methods. In this paper, we suggests the integrity verification technique of OS using a boot loader and a physically independent storing device in the mobile device.

External integrity verification for outsourced big data in cloud and IoT: A big picture

As cloud computing is being widely adopted for big data processing, data security is becoming one of the major concerns of data owners. Data integrity is an important factor in almost any data and computation related context. It is not only one of the qualities of service, but also an important part of data security and privacy. With the proliferation of cloud computing and the increasing needs in analytics for big data such as data generated by the Internet of Things, verification of data integrity becomes increasingly important, especially on outsourced data. Therefore, research topics on external data integrity verification have attracted tremendous research interest in recent years. Among all the metrics, efficiency and security are two of the most concerned measurements. In this paper, we will bring forth a big picture through providing an analysis on authenticator-based data integrity verification techniques on cloud and Internet of Things data. We will analyze multiple aspects of the research problem. First, we illustrate the research problem by summarizing research motivations and methodologies. Second, we summarize and compare current achievements of several of the representative approaches. Finally, we introduce our view for possible future developments.

MEM-DnP—A Novel Energy Efficient Approach for Memory Integrity Detection and Protection in Embedded Systems

The pervasiveness of modern day embedded systems has led to the storing of huge amounts of sensitive information in them. These embedded devices often have to operate under insecure environments and are hence susceptible to software and physical attacks. Thus, security has been and will remain one of the prime concerns in the embedded systems. Although a lot of hardware and software techniques have been proposed to provide high levels of security, they are hampered by the trade-offs created by the design constraints in embedded systems. This paper presents a novel energy efficient approach for MEMory integrity Detection and Protection (MEM-DnP). The key feature of the proposed MEM-DnP is that it can be adaptively tuned to a memory integrity verification module by using a sensor module. This significantly reduces the energy overheads imposed on an embedded system as compared to the conventional memory integrity verification mechanisms. The simulation results show that the average energy saved in the combined detection and protection mechanism ranges from 85.5 % to 99.998 %. This is substantially higher compared to the results achieved in basecase simulations with traditional memory integrity verification techniques.

IVEC

This paper proposes a unified off-chip memory integrity protection scheme, named IVEC. Today, a system needs two independent mechanisms in order to protect the memory integrity from both physical attacks and random errors. Integrity verification schemes detect malicious tampering of memory while error correcting codes (ECC) detect and correct random errors. IVEC enables both detection of malicious attacks for security and correction of random errors for reliability at the same time by extending the integrity verification techniques. Analytical and experimental studies show that IVEC can correct single-bit errors and even multi-bit errors from one DRAM chip within a cache block read without any additional ECC bits, when the integrity verification is also required for security, effectively removing the memory and bandwidth overheads (12.5%) of typical ECC schemes. Alternatively, with parity bits, IVEC can provide even stronger error correction capabilities comparable to the traditional chip-kill correct, still with less overheads. For both cases, IVEC can use standard non-ECC DIMMs.