Unauthorized Person Research Articles

Data protection enhancement in smart grid communication: An efficient multi-layer encrypting approach based on chaotic techniques and steganography

In this study, a multi-layer encryption system is proposed through which sensitive and important data in smart grids can be secured from unauthorized persons as well as cyber threats. The suggested system is analyzed using fundamental performance assessment metrics say as average processing times across ten runs, peak signal-to-noise ratio (PSNR), and root mean square error (RMSE). The encryption process involves hiding the data encrypted by a digital dictionary and the advanced encryption standard (AES) algorithm in an image. In this way, AES encryption suggests rapid processing with a short average time per each block; similarly, the decryption technique, which includes the dictionary and AES decryption also renders the results in a justified computational time nominating it as a practical approach. It is worth noting that the small key era and dictionary construction instances provoke innovations in the general efficiency of the encryption mechanism. The conducted study, based on recorded values for PSNR, RMSE, UACI, and NPCR, demonstrates that the proposed multi-layer encryption system, which incorporates dictionary encryption and AES, is a robust and a fast method to shield important information and attaining a balance between protection and computational time.

Accounting Information Technology and its Role in Raising the Level of Professional Performance of Internal Auditing

This research aims to know the role of information technology in improving the performance of internal auditing, by highlighting the obstacles facing the use of information technology during internal auditing and understanding the extent of the internal auditor's awareness, Due to the importance that provides in improving audit services and explaining its role in providing accurate results and large information with high efficiency, in addition to the impact of information technology in reducing internal audit risks as a result of the large size of economic units and the diversity of their legal forms due to the great development occurring in all economic sectors. This led to the need for the internal auditor to provide services with the highest quality, one of the most important results that were reached is that information technology works to improve auditing procedures and reducing the risk by monitoring the computer performance daily with operational activities and confidentiality of information and the inability to access important information for unauthorized persons. Among the most important recommendations is the necessity for internal auditors to be Awareness of the importance of this technology when performing auditing services and reducing the risk when monitoring computer performance daily with operational activities, the confidentiality of information, and the inability to access important information except for authorized persons. The research concluded that the hypotheses are correct.

Data access control for named data of health things

The internet of health things (IoHT) represents an innovative network concept that significantly improving healthcare. However, security and privacy are the main concerns of IoHT because the transmitted health data is often sensitive data about patients’ health status, which needs to be secured and protected from unauthorized users and any leakage. Named data networking (NDN) is considered the most promising architecture for the future internet that perfectly fits with the requirements of IoHT systems, especially regarding security and privacy. In this paper, we exploit the fundamental features of NDN to design a robust system for IoHT to ensure secure communication and access to health data. This system presents a content access control model, which prevents attackers and unauthorized users from accessing health data, allows only authorized users to access these data, and prevents users from accessing “corrupted” or “fake” content. The simulation results show that the proposed mechanism slightly delays the secure retrieval of health data. However, this delay is tolerable since the mechanism protects the health data from unauthorized persons and those who try to inject untrusted data into the network.

Systematic survey on data security in wireless body area networks in IoT healthcare system.

In the Internet of Things (IoT) healthcare sector, the wireless body area network (WBAN) is being used to optimize medical results by tracking and treating patients as they go about their daily lives. Health insurance has also been one of the cybercriminal's main goals. The Systematic Review of IoT Healthcare systems particularly wireless body area networks is significant, to reach the benefits and challenges faced by existing methods in the domain. This study provides a systematic survey of WBAN data protection. Various types of devices are used in medical science to detect and diagnose diseases. The network is an integral part of medical science in today's era. In medical sciences, sensors take data from a problematic place like cancerous cells. This research discussed a lot of techniques in the literature review. Most of them are not able to fulfill the requirements. If an unauthorized person reaches the data that can be a severe issue, like the diagnosed disease was blood cancer, and after unauthorized access manipulation can change even the diagnosed issue in the database. A doctor can prescribe the medication based on provided data that has been manipulated by unauthorized persons. Several existing schemes are explored in the literature to determine how the protection of sharing patients' healthcare data can be improved. The systematic literature review (SLR) of multiple security schemes for WBAN is presented in this survey paper.

Patient Data Hiding and Transmitting during COVID-19 for Telemedicine Application using Image Steganography.

After the COVID-19 pandemic, every individual needs to be more aware of their health. The condition of the human body is ged based on various health reports like X-rays, CT scan, and MRI scans. Moreover, due to misplacement or loss of medical reports, there is a high probabaility of improper diagnosis. In order to avoid improper diagnosis, a novel data-hiding technique is proposed in this work. In the proposed method, the patient's health records are hidden using polynomial theory in the patient photograph. This is used by doctors in telemedicine for better treatment at the right time. Image steganography is useful for hiding secret images and also for generating secret keys. This enables only the authorized people (patient and corresponding doctor) to access the reports using secret keys. Four secret images (medical reports of the patient) are successfully embedded onto a single cover image (patient photo) with good quality. After embedding, the stego images look like cover images so that unauthorized persons will not be able to access the data, and hence, safe transmission is being carried out. A patient's medical report plays an important role in proper medical treatment. Particularly in telemedicine, the safe transmission of patient reports without any loss or damage is necessary. The proposed method embeds reports of a patient in his/her photo and transmitsthem to the destination safely with a quality of 45.5 dB. This hiding method is helpful to avoid cyber crimes, illegal transactions, malpractices etc.

METHODOLOGY FOR IMPROVING THE CYBER THREAT PROTECTION SYSTEM

The article presents the results of a study of the enterprise information security system and the development of proposals for its implementation. The article considers security as a system that includes tools and processes used by organizations to protect information. This includes policy settings that prevent unauthorized persons from accessing business or personal information. Information security is positioned as a growing and developing industry, covering a wide range from network and infrastructure protection to testing and auditing. The article analyzed IT products designed to ensure information security that are used in small and medium-sized businesses, explored problem areas and current applications that entrepreneurs use. One of the most pressing problems in the IT industry today, in the era of big data, is the rapid growth of the volume of unstructured content. Virtually every corporate data center (Docs) has file servers, corporate portals, Microsoft Exchange folders, network and cloud storage locations that contain many documents, including the content of important information. In addition, the repeated increase in volume and the growing variety of information stored and processed significantly complicates the task of managing this data.

Firearm Storage Behaviors - Behavioral Risk Factor Surveillance System, Eight States, 2021-2022.

Secure firearm storage might help reduce access by children and other unauthorized users and the related risk for injury or death. Information about state-specific prevalence of firearm storage practices can be used to develop secure storage messages and programs; however, such information is often unavailable. Data from the Behavioral Risk Factor Surveillance System, by respondent characteristics, were used to estimate prevalence of keeping firearms in or around the home and related storage practices for eight states that administered the firearm safety module in 2021 or 2022. Overall, 18.4% (California) to 50.6% (Alaska) of respondents reported that a firearm was kept in or around their home. Among those with a firearm in or around the home, 19.5% (Minnesota) to 43.8% (North Carolina) reported that a firearm was stored loaded. Across all eight states, approximately one half of those with a loaded firearm stored at least one loaded firearm unlocked. Among respondents with a child and a loaded firearm in the home, 25.2% (Ohio) to 41.4% (Alaska) reported that a loaded firearm was stored unlocked. Variability in firearm storage practices highlights the importance of local data and suggests opportunities to tailor prevention efforts to specific population groups to reduce risk for firearm handling by children without adult supervision, and other unauthorized persons.

Performance Evaluation of Laguerre Transform and Neural Network-based Cryptographic Techniques for Network Security

As the world evolves day by day with new technologies, there is a need to design a secure network in such a way that intruders and unauthorized persons should not have access to the network as well as information regarding the personnel in any firm. In this study, a new cryptographic technique for securing data transmission based on the LaplaceLaguerre polynomial (LLP) is developed and compared to an existing auto-associative neural network technique (AANNT).The performance of the LLPT and AANNT was tested with some selected files in a MATLAB environment and the results obtained provided comparative information (in respect of AANNT versus LLPT) as follows: encryption time (1.67 ms versus 3.9931s), decryption time (1.833 ms versus 2.1172s), throughput (26.2975 Kb/s versus 0.01098 Kb/s), memory consumption (3.349 KB versus 15.958 KB). From the compared results, it shows that AANNT offers a faster processing time, higher throughput, and takes up less memory space than the LLPT. However, cryptanalysis of the AANNT is possible if the network's weight and design are known; hence, the technique is unreliable for ensuring the data integrity and confidentiality of encrypted data. The proposed LLP cryptographic algorithm is designed to provide a higher security level by making the LLP algorithm computationally tedious to invert using the standard Laplace transform inversion method. When compared to the AANN-based cryptographic technique, cracking the algorithm to uncover the encryption key takes time. This shows the strength and robustness of the proposed LLP cryptographic algorithm against attacks, as well as its suitability for solving the problem of data privacy and security when compared to the AANN-based cryptographic algorithm.

Surveillance System with Human Intrusion Detection

Security in restricted areas is essential for protecting valuable assets, sensitive information, ensuring the safety from intruders. Traditional security systems have many limitations, where they cannot authenticate whether the entered person is an intruder or not. To address this challenge by implementing a real-time face recognition- based surveillance system, is the goal of this project. Realtime Intrusion detection system provides surveillance for restricted and confidential areas with help of face recognition and detection, when an intruder or unauthorized person enters the area, this system will give an alert to the respective in charge through various channels, including email, messaging services, and direct phone calls. In this system, the OpenCV python library along with several algorithms are used to abstract the facial features and to take the input dataset. For face detection, the system utilizes SCRFD and YOLO, and it employs Arcface for accurate face recognition. This technique ensures the system can distinguish between an intruder and an authorized individual entering the secured area. This proactive approach enhances surveillance efficiency and reinforces the safety and integrity of restricted areas. For instance, when an individual enters the restricted area, the system captures and analyses their face. It then verifies whether the detected face matches any authorized faces in the registered user database. If there’s no match, the system identifies the person as an intruder and promptly sends an alert to the designated authority. To enhance accessibility, a user-friendly graphical interface (GUI) has been developed using Python’s Tkinter.

Review of Data Security and Privacy in Cloud Computing

Cloud computing, thus, ensure more healthy demand for cloud services, certain measures against threats in order to protect information must be taken. In essence, the current paper seeks to extend knowledge regarding the improvement of paradigms of cloud computing with particular focus on the aspect of certification of authentic users and protection of the contents that are hosted in these environments. It mentions a new approach in the context of the authentication method that was deployed for the purpose of the AAA certification is presented there along with the watermarking and this RSA algorithms to enhance the security of the cloud file-sharing. This concept is far more effective than the conventional access policies that are top down and cal beforehand for systematic risk avoidance; hence, it helps to minimize the chances of an organization being vulnerable to various risks by right management. Iturbide’s data loss prevention technique eliminates the probability of losing sensitive information to the rest of the world as well as other unauthorized persons or organizations regaining access to privileged keys while Shamir’s secret sharing algorithm- polynomial interpolation ensures that the generation of keys is not a time-consuming exercise. In order to address the issues of persistent security threats in cloud computing paradigm, the proposed model includes computation, encryption and access to improve the overall security of cloud environment. However, these measures have been implemented, some of them can offer the best security when it comes to the ever-evolving threat. To maintain the privacy of clients’ data in the CL reinforcement learning, the paper suggests the use of homomorphic encryption for privacy-preserving RL inference. Therefore – as a result of the work – the necessity of implementing the suggested security model for the cloud computing environments as well as protecting the data and enhancing the level of trust in cloud solutions is stated. Keywords - QoS (Quality of Service), Energy Efficiency, Ontology, AAA (Authentication, Authorization, and Accounting), RSA Algorithm, RSA Algorithm, ReDCIM (Reconfigurable Digital Computing-In-Memory) Processor, tableopencache, LSTM (Long Short-Term Memory)

Hybrid Cryptosystem using Lattice Permutation and Chaos Logistic Mapping for Image Security

Every platform of business uses online services and are increasing. Wired and wireless networks are becoming popular day by day. With this the sensitive data is carried over internet on daily basis. Due to rapid growth of networks, information security becomes more important. Hence, there is every chance of misleading the data by unauthorized parties. So, there is need to provide security for the data and cryptography is the science that helps in providing security. Encryption algorithm plays a crucial role in information security. This paper briefly describes a new hybrid system to enhance security. In this work along with traditional operations Lattice permutation is used in encryption process. For key generation Chaos Logistic Mapping is used that shows more resistance while breaking key by unauthorized persons. Services like online transactions may be largely protected with this type of newly proposed hybrid systems.

BANKS SHORT MESSAGE SERVICE THREATS NOTIFICATION SYSTEM ON ANDROID BASED PHONE

This research is carried out for the development and implementation of an end-to-end encrypted Short Message Service (SMS) App, utilizing a hybrid cipher algorithm, driven by the notable insecurity observed in SMS communications on mobile devices. SMS is a widely used communication method, and the primary goal of this study is to create a system (App) for end-to-end encrypted SMS. Loss of phones is becoming vulnerable for threats, because we store vital records in android and these records are secret such that no other third party is required to see them, such as Bank SMS, Event Notification etc. Also this information can be compromised if android phone is been lost and found by the criminals. Kidnapping activity is serious case happening in northern part of Nigeria, so if a phone is being lost and discovered how financed he is (the device holder), there is any means of bank account compromisation as that would allow the bank to give some information about the account because of the registered SIM card inserted in android devices (phones). This system is aimed to secure Bank SMS by not allowing an unauthorized person to views the banks SMS, but all other SMS can be view. Whenever the Banks SMS is received by the Android phone, the system will encrypt it and can only be viewed if using correct decryption key, a notification will be sent to the owner other phone if more than two attempt to view the message is made, using a Hybrid Cipher...

Evaluatıon of forensic medical aspects of medical interventions and damages caused by unauthorized persons

BackgroundMedical interventions are procedures that are conducive to creating danger on people’s life and body immunity due to their characteristics. We aimed to raise awareness and make contributions by revealing the fact that serious bodily and mental harms occur due to medical interventions by the ones who do not have the authority to perform. MethodsWe evaluated 210 cases appealled to our institution between the years of 2017 and 2022 who suffered damage after medical interventions by people who do not have any authorization or license. The damages that occurred in the cases were evaluated in terms of medical and legal aspects. Analysis of the data were done with SPSS 25.0 for Windows and the statistical alpha significance level were accepted as p < 0.05. Results76.7% of the cases were women, 87.1% were young individuals under the age of 40 Of the medical interventions, 91.9% were for aesthetic/cosmetic purposes (laser epilation, tattoo removal, botox, dermapen, cold lipolysis), 8.1% were for therapeutic purposes (bone setter intervention, tooth extraction/prosthesis, intramuscular injection, cupping pull) was found. It was found that 87.1% of the medical interventions were performed in beauty salons, 12.9% in hairdressers, home, medical markets, pharmacies and dental clinics. ConclusionsAll over the world and in our country, serious bodily and mental injuries occur in people after medical interventions by unauthorized persons. Therefore, it is necessary to see this situation as an important problem, and raise awareness in the society to make legal arrangements.

Proposed Development of NTRU Public Key Cryptosystem

As life progresses and develops, cryptography has become an indispensable science. The development of this science has given flexibility and security in exchanging information and data of various kinds by making it difficult for unauthorized persons to access them. In this paper, we proposed a new NTRU-like encryption scheme using a different mathematical structure for the public key, as well as for text encryption and decryption to have more resistance to attacks, which makes this method suitable for many applications.

A Compact Hardware Design and Implementation on FPGA Based Hybrid of AES and Keccak SHA3-512 for Enhancing Data Security

Data security means protecting important information from unauthorised persons. In a security system, cryptography is the most secure method. Cryptography has many kinds, but the Advanced Encryption Standard (AES) is the most secure system. If combined with AES and Secure Hash Algorithm-3-512Bits (SHA3-512), it becomes compact, more secure, and more authenticated for data communications. The proposed methodology is a hybrid cryptography technique that combines AES with the SHA3-512 algorithm. This system becomes a strong, secure system and produces a strong cipher text. The proposed method AES/SHA3-512 is Hardware implementation on the Artix-7 FPGA family yields the lowest cost and highest hardware efficiency with a reduction in area usage of LUT 18.49%, Flip Flops 0.83%, and IO 3.8%. The proposed architecture is synthesised and simulated using the Vivado 2017.2 version Tool.

Health Chain Connect

Electronic medical records are medical records of patient stored digitally on the internet. Patient information is stored in the blockchain, and this information is stored as a block of data in the blockchain. Encrypted using the AES algorithm used to encrypt all patient data. Blockchain networks are used in healthcare to exchange patient information and increase the efficiency, security, and transparency of medical information sharing in healthcare. Security, decentralized and transparency, the three main features of blockchain technology, make all applications secure and inaccessible to unauthorized persons.

INTELLIGENT FIELD AUTOMATION SYSTEM

The economy of India is a developing diverse economy. Nowadays, India grades second worldwide in farm production. Farming and connected areas like forestry and fisheries accounted for 13.7% of the GDP (gross domestic product) in 2013, about 50% of the workforce. The economic contribution of agriculture to Indias GDP is steadily declining with the countrys broad-based economic growth. Agriculture is the broadest economic sector and it has an importantplace in the overall socio-economic fabric of India.The prime concern being played is that deficiency of water, not just any water, but potable water. Agriculture automation [1] is the procedure of using several technical apparatuses to improve and automate agricultural dealings. This toolis essentially proposed to improve the labor-intensive and time-consuming agricultural procedures that farmers all over the world face. Farmers may gain more time and resources to devote in their properties with the support of farm automation and agriculture technology growths.This system is used to provide water to the field according to the need of soil by measuring the soil moisture level and atmospheric humidity level [2]. This systemavoids the wastage of water and electricity. The power consumption and water consumption can be controlled by a single motor, water tanks and some valves. Pump water to various water tanks by using single motor, valves and from multiple wells. The unauthorized persons intervention to the field, current atmospheric temperature level and moisture level of soil and animal attack can be remotely monitored and can be take necessary actions[3].

RANCANG BANGUN APLIKASI STEGANOGRAFI UNTUK MENGAMANKAN PESAN MENGGUNAKAN METODE LEAST SIGNIFICANT BIT (LSB) BERBASIS ANDROID

The Internet, an interconnected network, has become one of the most widespread data communications medias in the world. With the development of various illegal information retrieval techniques, many people try to get information that does not belong to them. Various techniques to protect sensitive information from unauthorized persons are widely used to protect important information. Steganography is a technique for hiding message files from the public who know their existence. This technique is often used to avoid suspicion or people who want to know the contents of the message file. Steganography is the science and technique of writing hidden messages so that no one else knows about their existence. Therefore, the application of plain-text steganography is inserted into the Least Significant Bit (LSB) encrypted image carrier. This allows mobile users to send the author's message to the recipient securely..

An Enhancement of Identity Based Conditional Privacy-preserving Authentication Process in Vehicular Ad Hoc Networks

In general, Vehicular Ad hoc Networks (VANETs) are permitting the communication between one vehicle with neighboring vehicles, infrastructure, and Road-Side Unit (RSU). In this, vehicle platoon is commonly known as the vehicle driving pattern it categorizes the batching of the vehicle in the on the trot fashion. It has been reviewed as an effective resolution to mitigate the reduction in traffic blockage and to widen the opulence of the travel. However, the malicious activities of any unauthorized person in VANET are increased the damage to authorized vehicles. In this manuscript, the Identity based Conditional Privacy-Preserving Authentication (ID-CPPA) signature scheme is proposed to detect the malignant command vehicle very efficiently by the consumer vehicle. In this, the proposed ID-CPPA method uses one-way hash functions for improving the efficiency of Road-Side Unit (RSU) signing and verification of a messages. In order to provide better concealment to the vehicle, Phase Truncated Fourier Transform based asymmetric encryption algorithm (PTFT-AE) is proposed. Thus, the proposed ID-CPPA-PTFT-AE approach has achieved 28.96%, 37.58%, 31.36% higher security rate and 25.8%, 37.9%, 42.6% lower delay than the existing MPDC-LPNS, PPSR-GS, and WCAA-TST methods respectively.

An Active Learning Approach for Detecting Customer Induced Damages in Motherboards with Deep Neural Networks

Identifying Customer Induced Damage (CID) is a key part in warranty programs of electronics manufacturers. CID is defined as any damage in the unit performed by an unauthorized person including the customer in a Printed Circuit Board (PCB). In such cases, damaged units are not covered by warranty. The inspection of CIDs is usually performed by humans which may be costly and error prone. Modern computer vision techniques for object detection using deep neural networks can automatically and accurately detect CIDs on PCBs. The training of such networks requires a large labeled dataset of image examples of CIDs. Daily, hardware factories and repair centers generate hundreds of unlabeled images. Labeling them manually is laborious and time-consuming. Therefore, it is crucial to label the minimum amount of images such that the trained neural network can achieve comparable accuracy as if it were trained with the whole dataset. To this end, we propose an active learning approach that selects the most informative images for the object detector. For that, our approach is based on the uncertainty of the object detector, i.e., it selects new images based on class probability distribution given by the object detector. Also, we tackle some challenges that are intrinsic to this problem: i) it is a multiclass object detection problem since there are many types of defects; ii) there is a class accuracy imbalance; iii) there is a focus on recall, e.g. false positives are less harmful than false negatives, and iv) there are many images with no object which should not be selected for labeling. We evaluate this approach by using it to iteratively sample data, train and evaluate a model, and compare it with randomly sampled data. The results show that our method consistently outperforms random sampling by an average margin of 21.6%, proving to be a viable alternative for reducing the labeling cost and increasing detection accuracy in this domain.