Biblio

Artificial technology developed in recent years. It is an intelligent system that can perform tasks without human intervention. AI can be used for various purposes, such as speech recognition, face recognition, etc. AI can be used for good or bad purposes, depending on how it is implemented. The discuss the application of AI in data security technology and its advantages over traditional security methods. We will focus on the good use of AI by analyzing the impact of AI on the development of big data security technology. AI can be used to enhance security technology by using machine learning algorithms, which can analyze large amounts of data and identify patterns that cannot be detected automatically by humans. The computer big data security technology platform based on artificial intelligence in this paper is the process of creating a system that can identify and prevent malicious programs. The system must be able to detect all types of threats, including viruses, worms, Trojans and spyware. It should also be able to monitor network activity and respond quickly in the event of an attack.

DefendR is a Security operation used to block the access of the user to edit or overwrite the contents in our personal file that is stored in our system. This approach of applying a certain filter for the sensitive or sensitive data that are applicable exclusively in read-only mode. This is an improvisation of security for the personal data that restricts undo or redo related operations in the shared file. We use a mini-filter driver tool. Specifically, IRP (Incident Response Plan)-based I/O operations, as well as fast FSFilter callback activities, may additionally all be filtered with a mini-filter driver. A mini-filter can register a preoperation callback procedure, a postoperative Each of the I/O operations it filters is filtered by a callback procedure. By registering all necessary callback filtering methods in a filter manager, a mini-filter driver interfaces to the file system indirectly. When a mini-filter is loaded, the latter is a Windows file system filter driver that is active and connects to the file system stack.

In recent years, data security incidents caused by insider threats in distributed file systems have attracted the attention of academia and industry. The most common way to detect insider threats is based on user profiles. Through analysis, we realize that based on existing user profiles are not efficient enough, and there are many false positives when a stable user profile has not yet been formed. In this work, we propose personalized user profiles and design an insider threat detection framework, which can intelligently detect insider threats for securing distributed file systems in real-time. To generate personalized user profiles, we come up with a time window-based clustering algorithm and a weighted kernel density estimation algorithm. Compared with non-personalized user profiles, both the Recall and Precision of insider threat detection based on personalized user profiles have been improved, resulting in their harmonic mean F1 increased to 96.52%. Meanwhile, to reduce the false positives of insider threat detection, we put forward operation recommendations based on user similarity to predict new operations that users will produce in the future, which can reduce the false positive rate (FPR). The FPR is reduced to 1.54% and the false positive identification rate (FPIR) is as high as 92.62%. Furthermore, to mitigate the risks caused by inaccurate authorization for users, we present user tags based on operation content and permission. The experimental results show that our proposed framework can detect insider threats more effectively and precisely, with lower FPR and high FPIR.

Cloud computing is a fast growing field that provides the user with resources like software, infrastructure and virtual hardware processing power. The steady rise of cloud computing in recent times allowed large companies and even individual users to move towards working with cloud storage systems. However, the risks of leakage of uploaded data in the cloud storage and the questions about the privacy of such systems are becoming a huge problem. Security incidents occur frequently everywhere around the world. Sometimes, data leak may occur at the server side by hackers for their own profit. Data being shared must be encrypted before outsourcing it to the cloud storage. Existing encryption/decryption systems utilize large computational power and have troubles managing the files. This paper introduces a file system that is a more efficient, virtual, with encryption/decryption scheme using parallel encryption. To make encryption and decryption of files easier, Parallel encryption is used in place of serial encryption which is integrated with Identity-Based Encryption in the file system. The proposed file system aims to secure files, reduce the chances of file stored in cloud storage getting leaked thus providing better security. The proposed file system, OutFS+, is more robust and secure than its predecessor, OutFS. Cloud outsourcing takes place faster and the files can be downloaded to the OutFS+ instance on the other side. Moreover, OutFS+ is secure since it is a virtual layer on the operating system and can be unmounted whenever the user wants to.

A direct access (DAX) file system maximizes the benefit of persistent memory(PM)’s low latency through removing the page cache layer from the file system access paths. However, this paper reveals that data block allocation of the DAX file systems in common is significantly slower than that of conventional file systems because the DAX file systems require the zero-out operation for the newly allocated blocks to prevent the leakage of old data previously stored in the allocated data blocks. The retarded block allocation significantly affects the file write performance. In addition to this revelation, this paper proposes an off-critical-path data block sanitization scheme tailored for DAX file systems. The proposed scheme detaches the zero-out operation from the latency-critical I/O path and performs that of released data blocks in the background. The proposed scheme’s design principle is universally applicable to most DAX file systems. For evaluation, we implemented our approach in Ext4-DAX and XFS-DAX. Our evaluation showed that the proposed scheme reduces the append write latency by 36.8%, and improved the performance of FileBench’s fileserver workload by 30.4%, YCSB’s workload A on RocksDB by 3.3%, and the Redis-benchmark by 7.4% on average, respectively.

In the process of crowdsourced testing service, the intellectual property of crowdsourced testing has been faced with problems such as code plagiarism, difficulties in confirming rights and unreliability of data. Blockchain is a decentralized, tamper-proof distributed ledger, which can help solve current problems. This paper proposes an intellectual property right confirmation system oriented to crowdsourced testing services, combined with blockchain, IPFS (Interplanetary file system), digital signature, code similarity detection to realize the confirmation of crowdsourced testing intellectual property. The performance test shows that the system can meet the requirements of normal crowdsourcing business as well as high concurrency situations.

Virtual machine (VM) based application sandboxes leverage strong isolation guarantees of virtualization techniques to address several security issues through effective containment of malware. Specifically, in end-user physical hosts, potentially vulnerable applications can be isolated from each other (and the host) using VM based sandboxes. However, sharing data across applications executing within different sandboxes is a non-trivial requirement for end-user systems because at the end of the day, all applications are used by the end-user owning the device. Existing file sharing techniques compromise the security or efficiency, especially considering lack of technical expertise of many end-users in the contemporary times. In this paper, we propose MicroBlind, a security hardened file sharing framework for virtualized sandboxes to support efficient data sharing across different application sandboxes. MicroBlind enables a simple file sharing management API for end users where the end user can orchestrate file sharing across different VM sandboxes in a secure manner. To demonstrate the efficacy of MicroBlind, we perform comprehensive empirical analysis against existing data sharing techniques (augmented for the sandboxing setup) and show that MicroBlind provides improved security and efficiency.

In the smart grid, the sharing of power data among various energy entities can make the data play a higher value. However, there may be unauthorized access while sharing data, which makes many entities unwilling to share their data to prevent data leakage. Based on blockchain and ABAC (Attribute-based Access Control) technology, this paper proposes an access control scheme, so that users can achieve fine-grained access control of their data when sharing them. The solution uses smart contract to achieve automated and reliable policy evaluation. IPFS (Interplanetary File System) is used for off-chain distributed storage to share the storage pressure of blockchain and guarantee the reliable storage of data. At the same time, all processes in the system are stored in the blockchain, ensuring the accountability of the system. Finally, the experiment proves the feasibility of the proposed scheme.

Data leakage by employees is a matter of concern for companies and organizations today. Previous studies have shown that existing Data Leakage Protection (DLP) systems on the market, the more secure they are, the more intrusive and tedious they are to work with. This paper proposes and assesses the implementation of four technologies that enable the development of secure file systems for insider threat-focused, low-intrusive and user-transparent DLP tools. Two of these technologies are configurable features of the Windows operating system (Minifilters and Server Message Block), the other two are virtual file systems (VFS) Dokan and WinFsp, which mirror the real file system (RFS) allowing it to incorporate security techniques. In the assessment of the technologies, it was found that the implementation of VFS was very efficient and simple. WinFsp and Dokan presented a performance of 51% and 20% respectively, with respect to the performance of the operations in the RFS. This result may seem relatively low, but it should be taken into account that the calculation includes read and write encryption and decryption operations as appropriate for each prototype. Server Message Block (SMB) presented a low performance (3%) so it is not considered viable for a solution like this, while Minifilters present the best performance but require high programming knowledge for its evolution. The prototype presented in this paper and its strategy provides an acceptable level of comfort for the user, and a high level of security.

Security incident handling and response are essen-tial parts of every organization's information and cyber security. Security incident handling consists of several phases, among which digital forensic analysis has an irreplaceable place. Due to particular digital evidence being recorded at a specific time, timelines play an essential role in analyzing this digital evidence. One of the vital tasks of the digital forensic investigator is finding relevant records in this timeline. This operation is performed manually in most cases. This paper focuses on the possibilities of automatically identifying digital evidence pertinent to the case and proposes a model that identifies this digital evidence. For this purpose, we focus on Windows operating system and the NTFS file system and use outlier detection (Local Outlier Factor method). Collected digital evidence is preprocessed, transformed to binary values, and aggregated by file system inodes and names. Subsequently, we identify digital records (file inodes, file names) relevant to the case. This paper analyzes the combinations of attributes, aggregation functions, local outlier factor parameters, and their impact on the resulting selection of relevant file inodes and file names.

The paper considers the issue of increasing the level of trust to the user of the information system by applying profiling actions. The authors have developed the model of user behavior, which allows to identify the user by his actions in the operating system. The model uses a user's characteristic metric instead of binary identification. The user's characteristic demonstrates the degree to which the current actions of the user corresponding to the user's behavior model. To calculate the user's characteristic, several formulas have been proposed. The authors propose to implement the developed behavior model into the access control model. For this purpose, the authors create the prototype of the user action profiling system for Windows family operating systems. This system should control access to protected resources by analyzing user behavior. The authors performed a series of tests with this system. This allowed to evaluate the accuracy of the system based on the proposed behavior model. Test results showed the type I errors. Therefore, the authors invented and described a polymodel approach to profiling actions. Potentially, the polymodel approach should solve the problem of the accuracy of the user action profiling system.

The main goal of the system is to make it easier to standardize the style of program code written in C++. Based on the results of the review of existing static analyzers, in addition to the main requirements, requirements for the structure of stylistic rules were identified. Based on the results obtained, a system for static analysis of the C++ language has been developed, consisting of a set of modules. The system is implemented using the Python 3.7 programming language. HTML and CSS markup languages were used to generate html reports. To ensure that rules can be stored in the database, the MongoDB database management system and the pymongo driver module were used.

In high-performance computing (HPC), scientific applications often manage a massive amount of data using I/O libraries. These libraries provide convenient data model abstractions, help ensure data portability, and, most important, empower end users to improve I/O performance by tuning configurations across multiple layers of the HPC I/O stack. We propose SCTuner, an autotuner integrated within the I/O library itself to dynamically tune both the I/O library and the underlying I/O stack at application runtime. To this end, we introduce a statistical benchmarking method to profile the behaviors of individual supercomputer I/O subsystems with varied configurations across I/O layers. We use the benchmarking results as the built-in knowledge in SCTuner, implement an I/O pattern extractor, and plan to implement an online performance tuner as the SCTuner runtime. We conducted a benchmarking analysis on the Summit supercomputer and its GPFS file system Alpine. The preliminary results show that our method can effectively extract the consistent I/O behaviors of the target system under production load, building the base for I/O autotuning at application runtime.

The data-driven period produces more and more security-related challenges that even experts can hardly deal with. One of the most complex threats is ransomware, which is very taxing and devastating to detect and mainly prevent. Our research methods showed significant results in identifying ransomware processes using the honeypot concept augmented with symbolic linking to reduce damage made to the file system. The CIA (confidentiality, integrity, availability) metrics have been adhered to. We propose to optimize the malware process termination procedure and introduce an artificial intelligence-human collaboration to enhance ransomware classification and detection.

The efficiency of secure deletion is highly dependent on the data layout of underlying storage devices. In particular, owing to the sequential-write constraint of the emerging Shingled Magnetic Recording (SMR) technology, an improper data layout could lead to serious write amplification and hinder the performance of secure deletion. The performance degradation of secure deletion on SMR drives is further aggravated with the need to securely erase the file system metadata of deleted files due to the small-size nature of file system metadata. Such an observation motivates us to propose a secure-deletion and SMR-aware space allocation (SSSA) strategy to facilitate the process of securely erasing both the deleted files and their metadata simultaneously. The proposed strategy is integrated within the widely-used extended file system 4 (ext4) and is evaluated through a series of experiments to demonstrate the effectiveness of the proposed strategy. The evaluation results show that the proposed strategy can reduce the secure deletion latency by 91.3% on average when compared with naive SMR-based ext4 file system.

In recent years, more and more medical institutions have been using electronic medical records (EMRs) to improve service efficiency and reduce storage cost. However, it is difficult for medical institutions with different management methods to share medical data. The medical data of patients is easy to be abused, and there are security risks of privacy data leakage. The above problems seriously impede the sharing of medical data. To solve these problems, we propose a blockchain-based medical data sharing scheme with attribute-based searchable encryption, named BMDS. In BMDS, encrypted EMRs are securely stored in the interplanetary file system (IPFS), while corresponding indexes and other information are stored in a medical consortium blockchain. The proposed BMDS has the features of tamper-proof, privacy preservation, verifiability and secure key management, and there is no single point of failure. The performance evaluation of computational overhead and security analysis show that the proposed BMDS has more comprehensive security features and practicability.

Over the last few years, the world has been moving towards digital healthcare, where harnessing medical data distributed across multiple healthcare providers is essential to achieving personalized treatments. Though the efficiency and speed of the diagnosis process have increased due to the digitalization of healthcare data, it is at constant risk of cyberattacks. Medical images, in particular, seem to have become a regular victim of hackers, due to which there is a need to find a feasible solution for storing them securely. This work proposes a blockchain-based framework that leverages the InterPlanetary File system (IPFS) to provide decentralized storage for medical images. Our proposed blockchain storage model is implemented in the IPFS distributed file-sharing system, where each image is stored on IPFS, and its corresponding unique content-addressed hash is stored in the blockchain. The proposed model ensures the security of the medical images without any third-party dependency and eliminates the obstacles that arise due to centralized storage.

In this paper, a blockchain based scheme is proposed to provide registration, mutual authentication and data sharing in wireless sensor network. The proposed model consists of three types of nodes: coordinators, cluster heads and sensor nodes. A consortium blockchain is deployed on coordinator nodes. The smart contracts execute on coordinators to record the identities of legitimate nodes. Moreover, they authenticate nodes and facilitate in data sharing. When a sensor node communicate and accesses data of any other sensor node, both nodes mutually authenticate each other. The smart contract of data sharing is used to provide a secure communication and data exchange between sensor nodes. Moreover, the data of all the nodes is stored on the decentralized storage called interplanetary file system. The simulation results show the response time of IPFS and message size during authentication and registration.

People are dependent on Trusted Third Party (TTP) administration based Centralized systems for content sharing having a deficit of security, faith, immutability, and clearness. This work has proposed a file-sharing environment based on Blockchain by clouting the Interplanetary File System (IPFS) and Public Key Infrastructure (PKI) systems, advantages for overcoming these troubles. The smart contract is implemented to control the access privilege and the modified version of IPFS software is utilized to enforce the predefined access-control list. An application framework on a secure decentralized file sharing system is presented in combination with IPFS and PKI to secure file sharing. PKI having public and private keys is used to enable encryption and decryption of every file transaction and authentication of identities through Metamask to cryptographically recognize account ownership in the Blockchain system. A gas consumption-based result analysis is done in the private Ethereum network and it attains transparency, security managed access, and quality of data indicating better efficacy of this work.

In the distributed file sharing system, a large number of users share bandwidth, upload resources and store them in a decentralized manner, thus offering both an abundant supply of high-quality resources and high-speed download. However, some users only enjoy the convenient service without uploading or sharing, which is called free riding. Free-riding may discourage other honest users. When free-riding users mount to a certain number, the platform may fail to work. The current available incentive mechanisms, such as reciprocal incentive mechanisms and reputation-based incentive mechanisms, which suffer simple incentive models, inability to achieve incentive circulation and dependence on a third-party trusted agency, are unable to completely solve the free-riding problem.In this paper we build a blockchain-based distributed file sharing platform and design a nested incentive scheme for this platform. The proposed nested incentive mechanism achieves the circulation of incentives in the platform and does not rely on any trusted third parties for incentive distribution, thus providing a better solution to free-riding. Our distributed file sharing platform prototype is built on the current mainstream blockchain. Nested incentive scheme experiments on this platform verify the effectiveness and superiority of our incentive scheme in solving the free-riding problem compared to other schemes.

Our identity as a human being is determined by the documents, not by appearance or physicality. The most important thing to prove the identity of humans is to show a government-issued document. Generally, from birth to death humans are recognized by documents because they are born with a birth certificate and they die with a death certificate. The main problem with these documents is that, they can be falsified or manipulated by others. Moreover in this digital era, they are stored in a centralized manner, which is prone to a cyber threat. This study aims to develop a blockchain environment to create, verify, and securely share documents in a decentralized manner. With the help of bigchainDB, interplanetary file system (IPFS), and asymmetric encryption, this research work will prototype the proposed solution called blockchain-based digital locker, which is similar to the DigiLocker released by the Department of Electronics and Information Technology (DeitY), Govt. of India. BigchainDB will help in treating each document as an asset by making it immutable with the help of IPFS and asymmetric encryption, where documents can not only be shared but also verified.

Explainable Artificial Intelligence (XAI) generates explanations which are used by regulators to audit the responsibility in case of any catastrophic failure. These explanations are currently stored in centralized systems. However, due to lack of security and traceability in centralized systems, the respective owner may temper the explanations for his convenience in order to avoid any penalty. Nowadays, Blockchain has emerged as one of the promising technologies that might overcome the security limitations. Hence, in this paper, we propose a novel Blockchain based framework for proof-of-authenticity pertaining to XAI decisions. The framework stores the explanations in InterPlanetary File System (IPFS) due to storage limitations of Ethereum Blockchain. Further, a Smart Contract is designed and deployed in order to supervise the storage and retrieval of explanations from Ethereum Blockchain. Furthermore, to induce cryptographic security in the network, an explanation's hash is calculated and stored in Blockchain too. Lastly, we perform the cost and security analysis of our proposed system.

The relevance of data protection is related to the intensive informatization of various aspects of society and the need to prevent unauthorized access to them. World spending on ensuring information security (IS) for the current state: expenses in the field of IS today amount to \$81.7 billion. Expenditure forecast by 2020: about \$105 billion [1]. Information protection of military facilities is the most critical in the public sector, in the non-state - financial organizations is one of the leaders in spending on information protection. An example of the importance of IS research is the Trojan encoder WannaCry, which infected hundreds of thousands of computers around the world, attacks are recorded in more than 116 countries. The attack of the encoder of WannaCry (Wana Decryptor) happens through a vulnerability in service Server Message Block (protocol of network access to file systems) of Windows OS. Then, a rootkit (a set of malware) was installed on the infected system, using which the attackers launched an encryption program. Then each vulnerable computer could become infected with another infected device within one local network. Due to these attacks, about \$70,000 was lost (according to data from 18.05.2017) [2]. It is assumed in the presented work, that the software level of information protection is fundamentally insufficient to ensure the stable functioning of critical objects. This is due to the possible hardware implementation of undocumented instructions, discussed later. The complexity of computing systems and the degree of integration of their components are constantly growing. Therefore, monitoring the operation of the computer hardware is necessary to achieve the maximum degree of protection, in particular, data processing methods.

{Unikernel is smaller in size than existing operating systems and can be started and shut down much more quickly and safely, resulting in greater flexibility and security. Since unikernel does not include large modules like the file system in its library to reduce its size, it is common to choose offloading to handle file IO. However, the processing of IO offload of unikernel transfers the file IO command to the proxy of the file server and copies the file IO result of the proxy. This can result in a trade-off of rapid processing, an advantage of unikernel. In this paper, we propose a method to offload file IO and to perform file IO with direct copy from file server to unikernel}.

Live Linux distribution devices can hold Linux operating system for portability. Using such devices and distributions, one can access system or critical files, which otherwise cannot be accessed by guest or any unauthorized user. Events like file leakage before the official announcement. These announcements can vary from mobile companies to software industries. Damages caused by such vulnerabilities can be data theft, data tampering, or permanent deletion of certain records. This study uncovers the security flaws of operating system against live device attacks. For this study, we used live devices with different Linux distributions. Target operating systems are exposed to live device attacks and their behavior is recorded against different Linux distribution. This study also compares the robustness level of different operating system against such attacks.