Entire File Research Articles

A Novel Model for Protecting the Privacy of Digital Images in Cloud Using Permutated Fragmentation and Encryption Algorithms

Maintaining privacy is becoming increasingly challenging due to growing reliance on cloud services and software, respectively. Our data is stored in a virtual environment on unreliable cloud machines, making it susceptible to privacy breaches if not handled properly. Encrypting data before uploading it can be a solution to this problem, but it can be time-consuming. However, all of the encryption methods used to safeguard digital data so far did not fulfillment privacy and integration requirements. This is because encryption cannot function independently. Data that is encrypted and stored on a single cloud server can still be accessed by attackers, compromising the privacy of the data. In this paper, we propose a new model based on the user's classification of privacy level. The proposed model divides the digital file into multiple fragments and separately encrypts each fragment; each fragment is encrypted as separated blocks. Additionally, permutation is implemented on encrypted fragments because they are stored in the cloud with replication fragments on another cloud service. This approach ensures that even if the attacker’s gains access to one fragment, they would not be able to access the entire file, thereby safeguarding the privacy of the data.

Mount SMB.pcap: Reconstructing file systems and file operations from network traffic

File system and network forensics are fundamental in forensic investigations, but are often treated as distinct disciplines. This work seeks to unify these fields by introducing a novel framework capable of mounting network captures, enabling investigators to seamlessly browse data using conventional tools. Although our implementation supports various protocols such as HTTP, TLS, and FTP, this work will particularly focus on the complexities of the Server Message Block (SMB) protocol, which is fundamental for shared file system access, especially within local networks.For this, we present a detailed methodology to extract essential file system data from SMB network traffic, aiming to reconstruct the share's file system as accurately as the original. Our approach goes beyond traditional tools like Wireshark, which typically only extract individual files from SMB transmissions. Instead, we reconstruct the entire file system hierarchy, retrieve all associated metadata, and handle multiple versions of files captured within the same network traffic. In addition, we also investigate how file operations impact SMB commands and show how these can be used to accurately recreate user activities on an SMB share based solely on network traffic. Although both methodologies and implementations can be applied independently, their combination provides investigators with a comprehensive view of the reconstructed file system along with the corresponding user activities extracted from network traffic.

Intelligent privacy‐preserving data management framework for medicine supply chain system

AbstractIn today's era, the pharmaceutical industry has integrated blockchain to secure the sensitive information of medicines, wherein public and private blockchains are used to preserve the security and privacy of the medicine supply chain data. However, conventional blockchains often limit scalability due to limited storage. Moreover, blockchain has loopholes; for example, it is not able to prove the validity of the data prior to being stored in the blockchain, which leads to fake data being added to the blockchain. As a result, it causes an issue of data provenance. Motivated by this, the proposed framework incorporated artificial intelligence (AI) algorithms to enhance the efficiency of the medicine supply chain data. The proposed framework integrated machine learning (ML) and blockchain, where ML classifies the valid and invalid data of the medicine supply chain, whereas blockchain stores only valid data and maintains its security and privacy. This identification helps the blockchain to verify medicine supply chain data before adding it to the blockchain. Additionally, we employed an InterPlanetary file system (IPFS) that saves medicine supply chain data and computes its hash to offer decentralized storage. Further, this hash data is stored on a private Hyperledger Fabric blockchain, which requires minimal storage instead of storing an entire large file. This minimal storage optimizes the process of data storage and retrieval in the Hyperledger Fabric blockchain, which enhances the scalability of the proposed framework. Finally, the result of the proposed framework is assessed in two phases: ML and blockchain, wherein the ML model's performance is measured by statistical measures and the blockchain‐based result is assessed using several performance parameters such as throughput is around (618 transactions per second), latency (0.12 s), response time (11 s) and data rate (282 Mbps).

Implementasi Algoritma Rivest Shamir Adleman (RSA) Untuk Keamanan Data Rekam Medik Penyakit Pasien Rumah Sakit

Medical records are records of the who, what, where, and how of patient care while in hospital. One aspect of the use of medical records is the documentation aspect, namely medical records contain important information that is useful for various parties. Medical records contain data regarding past and present health and contain health professional notes regarding the patient's current condition in the form of physical findings, results of diagnostic and therapeutic procedures and patient responses. Medical record documents belong to doctors, dentists and health service facilities, while the contents of medical records belong to the patient. What can be given, recorded or duplicated by the patient is a summary of the medical record. Patients have the right to know the contents of medical records, however, the entire medical record file can only be held by authorized health/medical records officers and cannot leave the location of the health facility. This aims to maintain medical confidentiality (because medical information can be misused) and prevent medical records from being lost or damaged. To overcome this problem, a computerized system is needed that is able to secure medical record data so that unauthorized parties cannot read it. One technique that can be used to secure medical record data is cryptography. Cryptography comes from Greek which consists of the words kryptos which means hidden and graphia which means something written so that cryptography can be interpreted as something written in secret or hidden.. In applying the Rivest Shamir Adleman (RSA) method in securing medical record data at home Mitra Sejati Medan Hospital, namely by inserting program coding from Shamir Adleman's Rivest method into the programming language used. Next, form a public and private key, then carry out the encryption process for medical record data

DATA FINDING, SHARING AND DUPLICATION REMOVAL IN THE CLOUD

Deduplication involves eliminating duplicate or redundant data to reduce stored data volume, commonly used in data backup, network optimization, and storage management. However, traditional deduplication methods have limitations with encrypted data and security. The primary objective of this project is to develop new distributed deduplication systems that offer increased reliability. In these systems, data chunks are distributed across the Hadoop Distributed File System (HDFS), and a robust key management system is utilized to ensure secure deduplication with slave nodes. Instead of having multiple copies of the same content, deduplication removes redundant data by retaining only one physical copy and referring other instances to that copy. The granularity of deduplication can vary, ranging from an entire file to a data block. The MD5 and 3DES algorithms are used to enhance the deduplication process. The proposed approach in this project is the Proof of Ownership (POF) of the file. With this method, deduplication can effectively address the issues of reliability and label consistency in HDFS storage systems. The proposed system has successfully reduced the cost and time associated with uploading and downloading data, while also optimizing storage space. Key Words: Cloud computing, data storage, file checksum algorithms, computational infrastructure, duplication.

CLOUD BASED DUPLICATION REMOVAL SYSTEM

Deduplication involves eliminating duplicate or redundant data to reduce stored data volume, commonly used in data backup, network optimization, and storage management. However, traditional deduplication methods have limitations with encrypted data and security. The primary objective of this project is to develop new distributed deduplication systems that offer increased reliability. In these systems, data chunks are distributed across the Hadoop Distributed File System (HDFS), and a robust key management system is utilized to ensure secure deduplication with slave nodes. Instead of having multiple copies of the same content, deduplication removes redundant data by retaining only one physical copy and referring other instances to that copy. The granularity of deduplication can vary, ranging from an entire file to a data block. The MD5 and 3DES algorithms are used to enhance the deduplication process. The proposed approach in this project is the Proof of Ownership (POF) of the file. With this method, deduplication can effectively address the issues of reliability and label consistency in HDFS storage systems. The proposed system has successfully reduced the cost and time associated with uploading and downloading data, while also optimizing storage space. Key Words: Cloud computing, data storage, file checksum algorithms, computational infrastructure, duplication.

Streamlining remote nanopore data access with slow5curl.

As adoption of nanopore sequencing technology continues to advance, the need to maintain large volumes of raw current signal data for reanalysis with updated algorithms is a growing challenge. Here we introduce slow5curl, a software package designed to streamline nanopore data sharing, accessibility, and reanalysis. Slow5curl allows a user to fetch a specified read or group of reads from a raw nanopore dataset stored on a remote server, such as a public data repository, without downloading the entire file. Slow5curl uses an index to quickly fetch specific reads from a large dataset in SLOW5/BLOW5 format and highly parallelized data access requests to maximize download speeds. Using all public nanopore data from the Human Pangenome Reference Consortium (>22 TB), we demonstrate how slow5curl can be used to quickly fetch and reanalyze raw signal reads corresponding to a set of target genes from each individual in large cohort dataset (n = 91), minimizing the time, egress costs, and local storage requirements for their reanalysis. We provide slow5curl as a free, open-source package that will reduce frictions in data sharing for the nanopore community: https://github.com/BonsonW/slow5curl.

Ensuring Data Integrity And Security In Diverse Cloud Environments To Prevent Duplicacy.

Data deduplication is a valuable technique for compressing and minimizing data duplication during data transfers, especially in cloud environments. By eliminating redundant data, it optimizes transmission capacity and reduces memory usage. To ensure the integrity of sensitive data, encryption is applied throughout the deduplication process. The SHA algorithm is commonly used for storing text data during deduplication. It generates security bits by padding the text and computes a hash consisting of hexadecimal, string, and integer data. Hash-based deduplication involves hashing the entire file and treating the hash values of text data as unique identifiers. This allows clients to identify duplicate data within the cloud. The Proof-of-Work (PoW) algorithm is widely utilized in blockchain networks like Bitcoin and Ethereum. Its primary function is to verify transactions through a process called mining. Miners engage in competition to solve complex mathematical problems, and the first one to find a solution is granted the right to add a new block to the blockchain. PoW relies on cryptographic hashing, such as the SHA-256 hashing function, to validate and secure transactions. On the other hand, the Proof of Retrievability (PoR) algorithm finds application in cloud computing systems. It serves as a consensus mechanism, ensuring that cloud storage providers store and retrieve data accurately. PoR enables cloud providers to demonstrate to consumers that their files can be fully recovered. This algorithm incorporates cryptographic proofs that validate the integrity and availability of the stored data. In cloud storage, deduplication is often implemented using the Memory mapping technique (MPT). This allows multiple data owners to store the same data in a single copy, enhancing storage efficiency. To maintain data security, encryption is applied both before and during the deduplication process, ensuring that sensitive information remains protected. In summary, data deduplication is a powerful method for compressing data, minimizing duplication, and optimizing transmission capacity. With encryption techniques and hash-based identification, it provides secure and efficient deduplication in cloud environments, while memory deduplication and MPT support further enhance performance and storage efficiency.

An Application to Improve the Performance and Security in Cloud by File Division Technique

Cloud computing has transformed the modern business landscape by providing scalable, flexible, and cost-effective solutions for data storage and processing. However, relying on external cloud providers to manage and protect sensitive data has raised significant security concerns, namely the risk of data breaches. To address these issues and optimize system performance concurrently, this research project introduces a novel approach that combines data fragmentation and replication in the cloud environment. Data fragmentation involves breaking down large files into smaller fragments or pieces, each of which contains only a portion of the original data. The fragments are then dispersed across multiple cloud nodes to ensure that no single node stores an entire file. This fragmentation and replication strategy reduces the potential risk of data exposure during a security breach. Data replication across multiple nodes improves system performance in addition to providing security benefits. Replicating data fragments facilitates more efficient data distribution and retrieval, thereby reducing response times and enhancing overall system performance. This paper provides a comprehensive overview of the methodology employed in this approach, highlighting its fundamental concepts, potential benefits, and key security considerations, such as the importance of data isolation and encryption. By combining data fragmentation and replication, organizations can strengthen their cloud data security while improving system performance, providing a comprehensive answer to the challenges posed by cloud computing.

FileDAG: A Multi-Version Decentralized Storage Network Built on DAG-Based Blockchain

Decentralized Storage Networks (DSNs) can gather storage resources from mutually untrusted providers and form worldwide decentralized file systems. Compared to traditional storage networks, DSNs are built on top of blockchains, which can incentivize service providers and ensure strong security. However, existing DSNs face two major challenges. First, deduplication can only be achieved at the directory-level. Missing file-level deduplication leads to unavoidable extra storage and bandwidth cost. Second, current DSNs realize file indexing by storing extra metadata while blockchain ledgers are not fully exploited. To overcome these problems, we propose FileDAG, a DSN built on DAG-based blockchain to support file-level deduplication in storing multi-versioned files. When updating files, we adopt an increment generation method to calculate and store only the increments instead of the entire updated files. Besides, we introduce a two-layer DAG-based blockchain ledger, by which FileDAG can provide flexible and storage-saving file indexing by directly using the blockchain database without incurring extra storage overhead. We implement FileDAG and evaluate its performance with extensive experiments. The results demonstrate that FileDAG outperforms the state-of-the-art industrial DSNs considering storage cost and latency.

Concurrent encryption and lossless compression using inversion ranks

For secure and efficient transmission or storage, data files are commonly compressed and encrypted. In this work, we introduce a cost-effective encryption method of files as a built-in component of a lossless compression algorithm, thus avoiding the added cost of employing two separate processes. We have shown in earlier studies that preprocessing data with Burrows–Wheeler Transformation followed by Inversion Ranking transformation in advance of the utilization of an entropy coder resulted in an extremely effective general-purpose lossless compression technique. In our proposed algorithm, we isolate the inversion frequency vector obtained from the Inversion Ranking transformation and transmit the compressed file. Since the inversion frequency vector is necessary for decompression, we use it as our secret key and transmit it over a secure channel. Compared to the size of a data file, its frequency vector is rather small. Thus, encrypting only the inversion frequency vector, instead of the entire compressed file, results in substantial savings in computational cost. We demonstrate that the proposed technique is effective and resistant to common attacks on image and audio data sets.

No-regret Caching via Online Mirror Descent

We study an online caching problem in which requests can be served by a local cache to avoid retrieval costs from a remote server. The cache can update its state after a batch of requests and store an arbitrarily small fraction of each file. We study no-regret algorithms based on Online Mirror Descent (OMD) strategies. We show that bounds for the regret crucially depend on the diversity of the request process, provided by the diversity ratio R/h , where R is the size of the batch and h is the maximum multiplicity of a request in a given batch. We characterize the optimality of OMD caching policies w.r.t. regret under different diversity regimes. We also prove that, when the cache must store the entire file, rather than a fraction, OMD strategies can be coupled with a randomized rounding scheme that preserves regret guarantees, even when update costs cannot be neglected. We provide a formal characterization of the rounding problem through optimal transport theory, and moreover we propose a computationally efficient randomized rounding scheme.

A Distributed Caching Approach for Minimizing Average Transmission Delay in Ultra-Dense Networks

Caching at the network edge is a promising approach to alleviate the backhaul congestion pressure and reduce transmission delay in ultra-dense networks (UDNs). However, the existing content caching methods do not fully explore and exploit potential caching and computation capabilities. In this paper, we propose a distributed caching approach as well as the corresponding content addressing method. Furthermore, a problem of caching optimization with the target to minimize the average transmission delay is investigated. We transform this nondifferentiable nonlinear programming problem into a linear programming problem. Then we utilize an Alternating Direction Method of Multipliers (ADMM) algorithm to solve this problem. Simulation results reveal that the proposed algorithm can converge to the global optimum and our proposed distributed caching approach reduce the average transmission delay significantly. In popular caching strategy, the average transmission delay in our proposed method decreases over 30% and 50% when compared with caching maximum distance separable (MDS) packets and caching entire files, respectively.

Assessment of Forensic Medical Expert’s Involvement in Primary Crime Scene Investigation in Nairobi

It is of great importance to include Forensic Medical Experts (FMEs) in Primary Crime Scene (PCS) investigation team especially in murder, rape and defilement in investigation framework. The criminal justice system in Kenya has not been effective due to the shortage of FMEs as well as the poor specialization among forensic experts and police officers in implementing Medico-legal services within the country. This research sought to assess the need to involve FMEs in PCS investigation in Starehe sub-county, which comprises of five stations, for the purpose of improving the quality of criminal investigation in the country. A systematic random sampling technique of case files brought back from court was used. The sample size was calculated by dividing the entire case files by interval. There were one hundred and thirty-five (135) case files numbered from one to one hundred and thirty-five (135), then picked at an interval of two from a random number. Sixty-seven (67) case files were sampled, studied and analyzed. Three hypotheses were developed to be tested. The main objective was to assess forensic medical expert’s involvement in PCS investigation in starehe police division, Nairobi County, Kenya. Data analysis was done using SPSS and presented with tables, and narrative. From the tested hypothesis we were able to discover that the FMEs in Kenya are not well trained and professional in the use of SOPs for collecting forensic evidence at PCS H1 (p=0.754); the Kenyan criminal justice system framework does not involve FMEs at all primary stages of investigations H2 (p=0.878); Cases in Kenyan courts are not very successful without the use of FMEs H3 (p=0.247). Involvement of the FMEs in primary crime scenes investigation ensures that there is adequate and sufficient evidence to prosecute criminals convicted of such criminal acts. Cases without forensic evidence component failed to secure a conviction indicating that their absence impacts the quality of evidence submitted to present a sound case to prosecute offenders. FMEs should respond alongside police crime scene investigators and be linked to crime scenes at all stages of investigation to collect forensic evidence to identify suspects responsible for committing criminal activities at the PCS. Forensic evidence should be presented by a qualified professional who complies with standards that enhance efficiency and fairness. The forensic medical evidence at the primary crime scene is best armed with skills, knowledge and tools that are required to aid the investigators to make maximum use of scanty resources available with regard to collection and analysis of biological and chemical evidence. There should be clearer guidelines on the steps to follow in regard to evidence collection. The results of this study will be used by policy makers and health care providers to improve forensic evidence gathering for better and successful prosecution.

Module extraction and DLL hijacking detection via single or multiple memory dumps

A memory dump contains the current state of a system's physical memory at the time of its acquisition. Among other things, it contains the processes that were running at the time of acquisition. These processes can share certain functionalities provided by shared object files, which are internally represented by modules in Windows. However, each process only maps in its address space the functionalities it needs, and not the entire shared object file. In this way, the current tools for extracting modules from existing processes in a memory dump from a Windows system obtain the partial content of a shared object file instead of the entire file. In this paper we present two tools, dubbed Modex and Intermodex, which are built on top of the Volatility 3 framework. These tools allow a forensic analyst to extract a 64-bit module from one or more Windows memory dumps as completely as possible. To achieve this, they aggregate the contents of the same module loaded by multiple processes that were running in the same memory dump or in different dumps (we called it intradump and interdump, respectively). Additionally, we also show how our developed tools are useful to detect dynamic-link library (DLL) hijacking attacks, a widely used attack on Windows where attackers trick processes into loading a malicious DLL instead of the benign one.

Ransomware: Analysis of Encrypted Files

Ransomware is a type of malware that damage the system by encrypting all the files existing in the computer. To get access, the victim has to pay a ransom to get a key to decrypt his data. When the virus is running in machine, the user cannot stop it on the first try, so he may lose his entire files. One of the goals of this work is to detect ransomware based on encrypted files in real time and to minimize the cost of losing files. We will try to do an analysis of a received file (without opening it and seeing its contents). This scanning action can prevent a ransomware from spreading in the system. Most Ransomware files are sent in “.exe” format, but in this work, we will try to use other file formats that can accept malware, for example, .doc or .docx, .xls or .xlsx, .ppt or .pptx, .jpg, etc. In fact, an attacker can focus only on the files that contain useful data. In this paper, we are going to identify the types of files if they are suspicious or normal (without opening them) from their headers. For that first, we are going to analyze each extension separately (.docx, .exe, .pptx, .xlsx, .jpg, etc.) by identifying their headers and signatures. Then we will take several files with different extensions to analyze them by doing a program who detect if a file is benign or suspicious.

The Petition of Ambassador Āqā Ḥasan as a Source on the Micro‑History of Russian‑Iranian Relations in the Middle of the 17th Century

The paper is devoted to the document form RSAAA (Russian State Archive of Ancient Documents) from the archive files related to the arrival in Russia in 1645 of the ambassador Aqa Hasan. Of the entire file (491 folios), this is the only document drawn up in Persian. It is interesting that this document did not relate with the main purpose of the embassy's arrival — the financial claims of the Russian side against the rulers of Iran, the proceedings on which lasted from 1629 to 1645. The Ambassador asked for help both in solving everyday issues and in overcoming difficulties associated with logistics and the movement of goods. It is noteworthy that one of the articles of the petition, dedicated to the fate of the Khorasan captive, was not included in the Russian translation, made by the translator of the 18th century, and, accordingly, was not included in the report to the tsar.

Study of bypassing Microsoft Windows Security using the MITRE CALDERA Framework

Background: Microsoft Windows Security is a recently implemented safeguard for the Windows operating systems, including the latest versions of Windows10 and 11. However, there is a major shortcoming in this system to stop Advanced Persistent Threat (APT). These are government-financed groups that are funded to attack other government entities. Following the initial security breach, the hacked Windows device is used to access the rest of the network devices in order to transfer data to external storage (Exfiltration). Methods: In this work, we have tested the Microsoft Windows Security system using MITRE CALDERA and ATT&CK frameworks and explain how APT groups are able to bypass Windows Security. Results: In this study we used "54ndc47" agent through GoLang feature in MITRE CALDERA platform to test and bypass Microsoft Windows Security systems (MS Windows 10). Through it, we were able to bypass the Windows Security system and display entire files in the victim's device. Conclusions: In this paper, we have provided recommendations to Microsoft to improve their Windows Security tool through the use of Artificial intelligence (AI).

Blockchain-Assisted Conditional Anonymity Privacy-Preserving Public Auditing Scheme With Reward Mechanism

In real-world scenarios, in order to encourage one to report others crimes, judicial department usually rents independent cloud storage spaces to receive the precious evidences from whistleblowers. Since the uploaded data are not controlled by cloud users, remote data integrity is very important. Public cloud auditing enables an auditor to periodically check the integrity of outsourcing data on behalf of users, without retrieving the entire data file. However, most existing data auditing schemes have potential security vulnerabilities, and thus cannot defense many security attacks (e.g., the man-in-the-middle attack). Meanwhile, it is significant to protect whistleblower’s identity privacy, reward the real data uploader, and further trace the responsibility of slanders accurately. From the aforementioned requirements, we present an efficient blockchain-assisted conditional anonymity privacy-preserving public auditing (BA-CAPPPA) scheme with reward mechanism. The Ethereum blockchain is integrated into BA-CAPPPA to enhance the security level of the whole public auditing mechanism. Theoretical analysis results show that the BA-CAPPPA achieves man-in-the-middle attack resistance, storage correctness guarantee, data privacy-preservation, conditional identity anonymity, and reward mechanism. Performance evaluations and comparisons demonstrate that BA-CAPPPA could outperform some state-of-the-art data auditing schemes.

HERO-Trial: Integration of self-hypnosis in an enhanced recovery after surgery program: A prospective randomized trial (115)

<b>Objectives:</b> Self-hypnosis (SH) induces patients into a relaxed state that may include feelings of dissociation through deep breathing and guided imagery. Studies have shown that SH can reduce patient distress prior to surgery and postoperative pain and anxiety. We evaluated whether adding SH to our enhanced recovery after surgery (ERAS) pathway was feasible and if it could improve patient-reported pain and anxiety and further decrease opioid use. <b>Methods:</b> Patients scheduled for open gynecologic surgery were randomized to either standard ERAS care or ERAS + SH. The 20-minute, 3D, SH audio recording was based on a well-validated medical hypnosis script. Patients in the SH arm were asked to listen to the audio file at least twice before surgery, although they had access to use it ad-lib after consent. The feasibility endpoint was defined as 60% of patients listening to the entire SH audio file in the preoperative holding area. The primary effectiveness outcome was worst pain on POD 1 (24-hour recall) on a 0-10 scale, assessed with the MDASI-PeriOpGYN. Secondary outcomes included anxiety, quality of life, symptom burden, time to the first opioid, quality of recovery (QoR-15), and morphine equivalent daily dose (MEDD) on POD 0-3. Hypnotic suggestibility was assessed by the Tellegen Absorption scale. Expectations and manageability of postoperative symptoms were assessed by the Side-Effect Expectancy Questionnaire (SEEQ). Satisfaction with the SH experience was evaluated. Summary statistics, Fisher's exact test (categorical variables), and Wilcoxon rank-sum test (continuous variables) were utilized. <b>Results:</b> A total of 152 patients were randomized and 138 had surgery and were evaluable (ERAS: <i>n</i> = 67; ERAS+SH: <i>n</i> = 71) (Table 1). Incorporation of SH was considered feasible, with 77.5% of ERAS+SH patients able to listen to the entire SH audio file in the preoperative holding unit. The study was stopped early due to futility in achieving the primary effectiveness outcome (pain on POD1). There were no significant differences in the primary outcome of worst pain on POD 1 (ERAS: 6/10; ERAS+SH: 7/10) (p=.70). The median age was 61 years in the ERAS arm and 54 years in the ERAS+SH arm (Table 1 for demographics). There were no significant differences in ERAS compliance, anesthesia type, or length of stay. No significant differences between the groups were noted on expectations, perceived ability to manage postoperative symptoms or hypnotic suggestibility. Median scores on the five satisfaction questions were 8/10 or above. There were no differences in median preoperative anxiety scores between the arms (ERAS: 4, IQR: 1-6; ERAS+SH: 4, IQR: 3-7). In the ERAS+SH arm, anxiety scores decreased significantly after the SH intervention in the preoperative holding unit -2 points (IQR:-3,-1) to a median score of 2 (p<.001). There were no significant differences in median MEDD on POD 0-3 between the two arms (daily median MEDD ranged from 0-15) or time to the first opioid. The quality of recovery score on the day of discharge was not significantly different between groups (ERAS: 110, IQR: 92-127; ERAS+SH: 107, IQR: 88-121). <b>Conclusions:</b> Incorporating SH into an ERAS pathway was feasible with high levels of satisfaction. While the SH intervention led to a statistically and clinically significant decrease in self-reported anxiety levels preoperatively, there were no group differences in self-reported pain, quality of recovery, time to the first opioid, or hospital MEDD. Given the ease of accessing and listening to an audio file, this SH intervention can be easily integrated into perioperative care to decrease preoperative anxiety.