Constructing collaborative desktop storage caches for large scientific datasets

Data integrity issues in pharmaceutical industry: Common observations, challenges and mitigations strategies

Cloud storage service supplies people with an efficient method to share data within a group. The cloud server is not trustworthy, so lots of remote data possession checking (RDPC) protocols are proposed and thought to be an effective way to ensure the data integrity. However, most of RDPC protocols are based on the mechanism of traditional public key infrastructure (PKI), which has obvious security flaw and bears big burden of certificate management. To avoid this shortcoming, identity-based cryptography (IBC) is often chosen to be the basis of RDPC. Unfortunately, IBC has an inherent drawback of key escrow. To solve these problems, we utilize the technique of certificateless signature to present a new RDPC protocol for checking the integrity of data shared among a group. In our scheme, user's private key includes two parts: a partial key generated by the group manager and a secret value chosen by herself/himself. To ensure the right public keys are chosen during the data integrity checking, the public key of each user is associated with her unique identity, for example the name or telephone number. Thus, the certificate is not needed and the problem of key escrow is eliminated too. Meanwhile, the data integrity can still be audited by public verifier without downloading the whole data. In addition, our scheme also supports efficient user revocation from the group. The security of our scheme is reduced to the assumptions of computational Diffie-Hellman (CDH) and discrete logarithm (DL). Experiment results exhibit that the new protocol is very efficient and feasible.

As we increasingly rely on information infrastructures to support critical operations in different areas, data integrity in overlay networks has significant importance with potentially rigorous consequences. Different attacks on data integrity aims to degrade availability of the secure and unmodified data to the network system. Gossip, or epidemic, protocols have emerged significantly to implement highly scalable and resilient reliable network system. Data integrity techniques in gossip protocol can have a significant role in order to secure data from an adversary. This paper describes an approach to represent and detect threats regarding data integrity in gossip based overlay networks. Establishing secure links between pairs of directly connected gossip nodes is an important issue for building overlay networks. This paper systematically identifies important security requirements of symmetric key setup. A preconfigured master key scheme is proposed that can satisfy the data integrity requirements if the master key has not been compromised. In this approach preconfigured master key is used in order to generate symmetric keys which are used to incorporate integrity checks.

The rapid digitalization of healthcare systems has led to an unprecedented accumulation of sensitive patient data across various platforms, exposing the industry to growing risks of data breaches, unauthorized access, and integrity compromise. Ensuring the security, privacy, and trustworthiness of healthcare data is paramount to maintaining patient confidentiality and enhancing clinical decision-making. This study proposes a conceptual framework that synergistically integrates Blockchain technology and Artificial Intelligence (AI) to enhance healthcare data security. The framework is designed to address key challenges such as data integrity, access control, real-time threat detection, and secure interoperability across healthcare stakeholders. Blockchain, with its decentralized and immutable ledger capabilities, provides a robust foundation for tamper-proof data storage and transparent audit trails. Smart contracts are employed to automate access controls and ensure compliance with regulatory requirements. AI, on the other hand, plays a critical role in intelligent threat detection and anomaly monitoring. By leveraging machine learning algorithms, the framework can identify suspicious patterns, detect insider threats, and predict potential breaches in real time. The proposed architecture comprises four core components: Secure data ingestion, blockchain-based data storage, AI-powered analytics, and a privacy-preserving access management layer. The framework also incorporates role-based authentication and homomorphic encryption techniques to enhance data privacy while supporting authorized data sharing. Case scenarios such as electronic health record (EHR) exchange and remote patient monitoring are used to demonstrate the practicality and scalability of the model. This integrated approach not only ensures the confidentiality, integrity, and availability of healthcare data but also fosters trust among patients, providers, and regulatory bodies. The framework aligns with global healthcare data standards and complies with regulations such as HIPAA and GDPR. Future directions include the deployment of federated learning models to further decentralize AI training while maintaining data privacy across institutions.

Now a days every industry needs more income with less investment behind infrastructure. Here, the new era of Cloud computing comes where the user can have everything on rent and "pay as go" fundamental. Cloud users are able to store their valuable data on Cloud premises and make themselves free from local burden. While users data is available on Cloud servers, it is very important for the user that data must be secure when it is in transition and even after it has been stored on server. Most of the researchers think for the user centric(side) scenario i.e mainly consider the security issue related to Cloud users like Integrity checking, Authentication, Versioning Etc. On the other hand, some researchers provide their view related to working of Cloud service providers i.e. Database encryption, Security based on Metadata, Data Obfuscation Etc. To have proper confidentiality, Security and integrity of data, this paper presents two techniques, that is: Encryption, authentication at client side as well as Data Obfuscation at server side. Encryption helps user to provide secrecy to its data when it is transferred in the network. Data obfuscation helps service provider to secure the users data on his premises. By applying these two techniques, the user and Service provider gets maximum protection against intruders and unauthorized access.

In this paper, the role of optical interconnects in high performance computing systems is explored. A Network-of- Workstations (NOW) consists of a collection of commodity workstations or high-end Personal Computers (PCs) interconnected with a high bandwidth Local Area Network (LAN). Due to technological advances, it has been argued that NOWs can offer cost-effective high performance computing systems, ranging from low-end interactive computing to high-end parallel computing. Over the last decade the industry has been moving in this direction: Commercial high end computing systems such as the Silicon Graphics Origin 2000 multiprocessor support up to 512 dual-processor nodes interconnected with a scalable network. In this paper, we argue that when NOWs are enhanced with a new generation of very high bandwidth optical networks, they can provide supercomputer-class performance at a fraction of the cost. We describe the architectures of ring-based and star-based multi- terabit optical networks for multiprocessor systems, and discuss their impact on system performance. These networks exploit the CMOS/VCSEL optoelectronic integrated circuit technology to yield exceptionally large bandwidths with small form factors and potentially low cost. We view these new optical networks as the key to the future evolution of multiprocessor systems, and we believe that such systems can open a new era of exceptionally high performance computing.

Cloud computing offers a kind of on-demand computing method that lets users use IT resources such as network, operating system, hardware, software, application and so on when needing them. However, cloud computing faces many security issues including data integrity, data confidentiality and access control. Recently, Barsoum et al. presents a cloud-based data access scheme that allows the data owner to benefit from the facilities offered by the CSP and enables indirect mutual trust between them. They declare that their scheme can assure data integrity, newness and CSP's defense. However, through our security analysis, their scheme still has some security vulnerabilities. It will easily suffer from the integrity attack, newness attack and CSP's defense attack. In other words, Although CSP have corrupted the outsourced data or ignore the data-updated request issued by the owner, the CSP is able to cheat authorized user into passing through the integrity checking, On the contrary, the owner also accuses CSP of having corrupted the outsourced data, whereas in reality the CSP not.

Data integrity verification (DIV) is one of the primary security checks for data stored on cloud servers. Cloud users have assured the safety of their data with frequent checking of data integrity. In this paper, we provide an efficient and effective DIV approach that offers effective and privacy-preserving audit structure. The main building components of our approach are a multi-power variant of the Paillier cryptography system with homomorphic tag. The Paillier cryptography system along with homomorphic tag assigns a unique and verifiable value to each data block, which helps performing dynamic data operations in cloud environment. To demonstrate our approach, we have implemented an application on Hadoop and MapReduce framework. We have tested this application with respect to the different parameters. The efficiency of the proposed method has been shown through the experimental results. Our method has shown a good improvement over those of the other modern systems.

To secure the communication between web servers there are different methods used to protect the communication and data. Confidentiality in Web communications can be achieved by using an encrypted, secure channel. End to end authentication can be done using routing protocols. To establish a secured channel between two end points , Source authentication, Data integrity and data confidentiality and Protection against replay attack are the security features used. A secured communication is achieved from client to IIS, between the web servers and within web servers. In this paper three methods namely core defense, boundary defense and distributed defense are dealt with in order to secure the communication so that illegal access to data, unauthorized access to data and DDoS attack in a network can be avoided. In order to achieve data integrity, confidentiality and securitythe communication between web servers is secured.

Full Disk Encryption (FDE) has become a widely used security feature. Although FDE can provide confidentiality, it generally does not provide cryptographic data integrity protection. We introduce an algorithm-agnostic solution that provides both data integrity and confidentiality protection at the disk sector layer. Our open-source solution is intended for drives without any special hardware extensions and is based on per-sector metadata fields implemented in software. Our implementation has been included in the Linux kernel since the version 4.12.

Cryptanalysis of an integrity checking scheme for cloud data sharing

Cloud computing plays an important role in the computing world as it provides a cost-effective way of delivering services to customers through the internet. The Cloud Service Providers (CSPs) offer an enormous amount of storage space with low cost and eliminates the data management burden of the customers. As the operational details are not transparent, the CSPs may be untrusted. They may steal the user data, tamper the data, remove the rarely accessed data or hide the data loss by duplicating the data. In such cases, data integrity fails and needs to be addressed. The emerging fog computing paradigm extends the cloud platform to provide services for IoT applications. So the data integrity verification techniques are not only to be incorporated over the cloud but also to be extended for fog computing. This survey discusses the various data integrity checking methodologies for both cloud and fog environment.

Recently released Intel processors have been equipped with hardware instruction tracing facilities to securely and efficiently record the program execution path. In this paper, we study a case for data integrity checking based on Intel Processor Trace (Intel PT), the instruction tracing facility on x86 processors. We incorporate software instrumentation and hardware instruction tracing to guarantee fine-grained data integrity without frequently switching the processor mode. We incorporate the idea in a system named DTrace which provides primitives to instruct Intel PT to capture the data load and store events, even current Intel PT implementations only record control transfers. The trace is analyzed before the program makes security-sensitive operations. We apply DTrace in several case studies to show that the primitives that DTrace provides are easy to use and help to enhance data integrity in applications. We further evaluate DTrace with several microbenchmarks to show the time cost that DTrace’s data tracing operation incurs. We also evaluate DTrace on Nginx to show the performance impact when Nginx is enhanced in security to provide the integrity during the runtime execution for programmer-defined security sensitive data. We find the performance overhead that DTrace incurs for the data tracing is moderate.

Hash algorithms play a major role in ensuring data authenticity and integrity in many applications such as digital signature verification, password hashing, SSL handshake, integrity checking, blockchain applications. Although many popular hash algorithms exist such as MD-5, SHA-0, SHA-1, SHA-2. Among these SHA-2 is the most important hash family. Nowadays, blockchain technology is becoming more and more popular in the Internet world which uses SHA-256 (an algorithm of SHA-2 family). The key factor behind the success of the blockchain is the Proof-of-Work (PoW) consensus algorithm in which a hash value of a specific complexity is computed using SHA-256. It requires extensive computing resources and consumes a lot of power. Therefore, in this paper, FPGA-based hardware architecture for SHA-256 computation is synthesized and simulated on Verilog HDL for better resource management. Along with this the power and time consumed in different FPGA families have been analyzed.

This paper describes a novel engine, called PE-ICE (Parallelized Encryption and Integrity Checking Engine), enabling to guarantee confidentiality and integrity of data exchanged between a SoC (System on Chip) and its external memory. The PE-ICE approach is based on an existing block-encryption algorithm to which the integrity checking capability is added. Simulation results show that the performance overhead of PE-ICE remains low (below 4%) compared to block-encryption-only systems (which provide data confidentiality only).