Illegal Modification Research Articles

Legal gaps and threats to public safety from free circulation of deactivated weapons using digital technologies: ways to improve criminal legislation

Relevance. Current weapons legislation of the Russian Federation does not take into account the impact of rapidly developing digital technologies on illegal arms trafficking. Deactivated weapons are freely sold on the Internet without the need for licensing, which creates legal gaps. Combined with the availability of information on weapon conversion and the availability of specialized components, these weapons can be easily modified to fire live ammunition, posing a serious threat to public safety.Purpose: to study is to study the public danger of free circulation of deactivated weapons using digital technologies, as well as to develop proposals for improving criminal and other legislation to increase the effectiveness of combating crime in this area.Objectives: include the analysis of legal gaps in the legislation regulating the circulation of deactivated weapons, the study of relevant judicial practice, the assessment of the impact of digital technologies on the distribution of deactivated weapons through Internet platforms and the availability of information on their modification, as well as the development of proposals for improving legislation and the differentiation of criminal liability.Methodology. The research is based on general scientific methods of analysis and synthesis, as well as formal-logical, formal-legal and methods of interpretation of legal norms.The results of the study show that the free circulation of deactivated weapons via the Internet creates conditions for their illegal modification and use for criminal purposes, which is confirmed by the analysis of judicial practice.Conclusions. The authors propose to tighten the legislation on the circulation of deactivated weapons by introducing mandatory licensing, strengthening control over their sale and circulation through digital platforms, and clarifying the differentiation of criminal liability for the illegal circulation and modification of weapons.

Visible watermarking for 3D models based on 3D Boolean operation

With the continuous expansion of the application field of 3D models and the convenience of model storage, transmission, and replication, the problems of illegal reproduction, illegal modification, and embezzlement faced by 3D models are gradually becoming severe, which has brought substantial economic losses to the producers of 3D models. Therefore, this study aims to develop a visible watermarking method for 3D model using 3D Boolean operation. First, based on TrueType font library, the 3D model of the watermark is generated through the extraction, positioning and combination of character outline. Next, the spatial registration between the watermark model and the 3D model was carried out according to the embedding position of the watermark. Finally, based on multiple 3D Boolean operations, the copyright information of the 3D watermark model is embedded into the 3D model in various modes, such as embossing, debossing, and surface mesh embedding. The experiments demonstrate that the method of this paper supports embedding watermark information in B-rep, CSG, and voxel models. This method can readily support business applications for visible watermarking of 3D models and has laid a good foundation for researching multipurpose 3D model watermarking algorithms supporting copyright notification and protection.

Design and implementation of secure student score system

The purpose of designing this system is to provide schools with a new way to make score certifications of a student and a safer way to search for a students previous academic scores. When a student is applying for a new school to further his study, the school always uses his previous academic scores to decide whether to enroll him. The current way for a school to mark a student and to search for a new students score record is depend on the student himself, which faces the problem of illegal modification and data leakage. The system mentioned in this paper can add a certification that includes the time information and score information. It can also use the digital signatures of teachers and headmasters to ensure that the scores are given by the corresponding teacher. This system does not include the direct Grade Point Average (GPA), but just includes the raw scores of each subject. Because different schools have different ways to turn the raw scores into a GPA and they also have different GPA upper limitations.

Blockchain-based decentralized supply chain system with secure information sharing

Supply chain management (SCM) has become an important way for the companies to improve the production efficiency and reduce the management cost. However, the existing SCM system is usually built and performed with the semi-trusted certificate authority, which may be susceptible to the collusion attack and tampering attack launched by the malicious certificate authority, resulting in illegal modification of product provenance record. Moreover, the lack of transparent and mutual trust among the stakeholders in the SCM system remains a great challenging issue. In this paper, we propose a blockchain-based decentralized supply chain system with secure information sharing, which can ensure the security of product provenance record without relying on any fully trusted intermediary. In our system, two validation mechanisms, i.e., one-way validation mechanism and transaction-based validation mechanism are built to help the stakeholders to perform the validation of product provenance record without accessing their original content. Furthermore, the blockchain-based smart contract is used to achieve secure registration, proper authentication and fair payment for all stakeholders, where the valid stakeholders can pay for the purchased products, automatically and reliably. Security analysis and performance evaluation demonstrate that our proposed scheme is secure, feasible and efficient with a limited and reasonable computation cost.

A blind watermarking approach based on hybrid Imperialistic Competitive Algorithm and SURF points for color Images’ authentication

Currently, we are in the area of the digital big data world. Every day, people share billions of images over Internet from various sources. Ensuring images’ authorship rights and illegal modification and/or reproductions become a challenge. Their protection must meet current and secure development needs of multimedia applications. In this paper, we propose an efficient watermarking scheme based on combining Imperialistic Competitive Algorithm (ICA), Speed Up Robust Features (SURF) points and Discrete Cosine Transform (DCT). The high complexity and inappropriate embedding area could lead to weak performance of watermarking schemas. To address these problems, an ideal watermarking embedding area was proposed using ICA to provide an optimized cost and complexity. The watermark was embedded into the DCT coefficients of the selected embedding areas. The watermark was extracted in a blind way to ensure color image’ authentication. Experimental findings demonstrate that the proposed approach achieves promising performance in terms of robustness and imperceptibility in almost cases. The average PSNR exceeds 61db regarding the imperceptibility. For the robustness measured by the correlation coefficients between the original watermark and the extracted is close to 1 in almost cases.

Data Verification in the Agent, Combining Blockchain and Quantum Keys by Means of Multiple-Valued Logic

Network control of autonomous robotic devices involves a vast number of secured data coding, verification, and identification procedures to provide reliable work of distant agents. Blockchain scheme provides here the model of the extended linked list for the verification of critical data, approved by quasi-random hash values assigned by external network nodes. And quantum lines are the source of high-quality quasi-random keys used as hash values. Discrete multiple-valued logic in such procedures is a simple and flexible tool to form the logic linked list, combining critical internal parameters of agents with data taken from external nodes. Such combination enlarges the set of possible schemes for data protection from illegal modifications and for data restoration.

Automatic fake document identification and localization using DE-Net and color-based features of foreign inks

Document examination is a vital mission for revealing illegal modifications that assist in the detection and resolution of criminal acts. Addition and alteration are more frequently used in handwritten documents. However, most of the documents have been modified with similar inks, and it is tough to detect or observe them with human eyes. As a result, there is a need for methods to automatically detect handwriting forgery to reach an accurate detection efficiently. In this paper, a novel and efficient method is proposed for automatically detecting altered handwritten documents and locating the fake part. Therefore, DE-Net is proposed to identify the forged document using a digitally scanned version of the document. Unlike the existing methods, a further localization schema is applied to locate the forged parts in the candidate forged document accurately. Where each forged document is segmented into objects. Color histograms of R, G, and B channels are used to generate a fused feature vector for each object. Then a structural similarity index (SSIM) is applied to detect the lower similarity parts as forged. The experimental results demonstrate that the proposed method can identify and localize foreign ink in handwritten documents with high performance.

VBlock: A Blockchain-Based Tamper-Proofing Data Protection Model for Internet of Vehicle Networks.

The rapid advancement of the Internet of Vehicles (IoV) has led to a massive growth in data received from IoV networks. The cloud storage has been a timely service that provides a vast range of data storage for IoV networks. However, existing data storage and access models used to manage and protect data in IoV networks have proven to be insufficient. They are centralized and usually accompanied by a lack of trust, transparency, security, immutability, and provenance. In this paper, we propose VBlock, a blockchain-based system that addresses the issues of illegal modification of outsourced vehicular data for smart city management and improvement. We introduce a novel collusion-resistant model for outsourcing data to cloud storage that ensures the network remains tamper-proof, has good data provenance and auditing, and solves the centralized problems prone to the single point of failure. We introduced a key revocation mechanism to secure the network from malicious nodes. We formally define the system model of VBlock in the setting of a consortium blockchain. Our simulation results and security analysis show that the proposed model provides a strong security guarantee with high efficiency and is practicable in the IoV environment.

CovidBChain: Framework for access-control, authentication, and integrity of Covid-19 data.

In the Covid-19 pandemic, information about the medical equipment such as personal protective equipment, ventilators, testing kits, oxygen cylinders, ICU beds, and patient diagnostic status is a black box for the patients. This article proposes a blockchain-assisted Covid-19 big data chain (CovidBChain) framework to handle the Covid-19 data, which is of colossal size (volume), coming from different sources (variety) and generated at every time instance (velocity). CovidBChain is proposed to protect electronic health records and Covid-19 equipment's information from illegal modification. CovidBChain provides transparency, access control, and integrity to Covid-19 data. The status of critical equipment like ventilator, Covid-19 beds, oxygen cylinder, and ICU status each such operation is integrated into the CovidBChain as a transaction. A prototype has been simulated using Ganache, Metamask, InterPlanetary File System, and Reactjs. The comparative assessment using proof-of-work (PoW) and proof-of-authority (PoA) deduces that the upload and retrieval time in PoA is less than PoW, while the transaction cost is more in PoW. The overhead of message exchange communication is reduced by a factor of in PoA as compared to the PoW approach. CovidBChain has been tested on the Ethereum official test network Ropsten for PoW and Goerli for PoA.

An Efficient Lightweight Image Encryption Scheme Using Multichaos

With an immense increase in Internet multimedia applications over the past few years, digital content such as digital images are stored and shared over global networks, the probability for information leakage and illegal modifications to the digital content is at high risk. These digital images are transferred using the network bandwidth; therefore, secure encryption schemes facilitate both information security and bandwidth issues. Hence, a state-of-the-art lightweight information security methodology is required to address this challenge. The main objective of this work is to develop a lightweight nonlinear mechanism for digital image security using chaos theory. The proposed scheme starts by changing a plain image into an encrypted image to improve its security. A block cipher, using lightweight chaos, has been added to achieve this objective for digital image security. We utilized multiple chaotic maps to generate random keys for each channel. Also, Arnold cat map and chaotic gingerbread map are used to add confusion and diffusion. During the permutation stage, image pixels are permuted, while in diffusion stage, pixels are distorted utilizing gingerbread map to add more security. The proposed scheme has been validated using different security parameter tests such as correlation coefficient tests (CC), whose results have been observed closer to zero and information entropy (IE) value is 7.99, respectively, which is almost equal to the ideal value of 8. Moreover, number of pixels changing rate (NPCR) obtained value is higher than 99.50%, while the unified average changing intensity (UACI) is 33.33. Other parameters such as mean absolute error (MAE), mean square error (MSE), lower value of peak to signal noise ratio (PSNR), structural content (SC), maximum difference (MD), average difference (AD), normalized cross-correlation (NCC), and histogram analysis (HA) is tested. The computed values of the proposed scheme are better. The achieved results after comparison with existing schemes highlight that the proposed scheme is highly secure, lightweight, and feasible for real-time communications.

Sanksi Hukum terhadap Pelaku Penyadapan Telepon Pintar atau Smartphone Melalui Aplikasi Android Modifikasi Ilegal yang Diinstal oleh Korban

Technological advances have resulted in illegal wiretapping crimes being carried out more easily, namely by utilizing illegal modification applications. The purpose of this research is to analyze the legal protection of the personal data of smartphone tapping victims as a result of installing an illegal modified android application made by the perpetrator and to examine criminal sanctions against smartphone tapping perpetrators through an illegal modified android application made by the perpetrator. This research uses a normative legal research method, using a statutory approach and a conceptual approach. There are two types of sources of legal materials in this research, namely primary sources of legal materials and secondary sources of legal materials. Primary legal materials come from statutory regulations related to the issues studied, while secondary legal materials come from law books and legal journals that are related to this research. The data collection technique used library techniques, which carried out a literature research on legal materials, both primary legal materials and secondary legal materials. From the results of the research, Indonesia does not have a law that specifically and legally regulates the protection of personal data. There are two forms of legal protection for the personal data of victims of illegal wiretapping, namely, preventive and repressive legal protection. Regarding wiretapping, it is regulated in the Telecommunications Law and the ITE Law. Both laws expressly prohibit illegal wiretapping and for those who do illegal wiretapping who use illegal modification applications can be subject to sanctions in accordance with article 50 of the ITE Law. The government is advised to further research the draft law before ratifying it so that there is no conflict of norms.

In-Memory Computation Based Mapping of Keccak-f Hash Function

Cryptographic hash functions play a central role in data security for applications such as message authentication, data verification, and detecting malicious or illegal modification of data. However, such functions typically require intensive computations with high volume of memory accesses. Novel computing architectures such as logic-in-memory (LIM)/in-memory computing (IMC) have been investigated in the literature to address the limitations of intense compute and memory bottleneck. In this work, we present an implementation of Keccak-f (a state-of-the-art secure hash algorithm) using a variant of simultaneous logic-in-memory (SLIM) that utilizes emerging non-volatile memory (NVM) devices. Detailed operation and instruction mapping on SLIM-based digital gates is presented. Through simulations, we benchmark the proposed approach using LIM cells based on four different emerging NVM devices (OxRAM, CBRAM, PCM, and FeRAM). The proposed mapping strategy when used with state-of-the-art emerging NVM devices offers EDP savings of up to 300× compared to conventional methods.

Blockchain-based privacy preserving e-health system for healthcare data in cloud

Cloud-assisted electronic health (e-health) system has played an important role in the management of healthcare data, which can provide efficient and convenient storage services for the patients to store their electronic health records (EHRs). However, there are the security challenges in the existing e-health system, where the malicious doctors may collude with cloud storage service provider (CSP) to tamper with the patients’ EHRs, or directly reveal the content of EHRs to other adversaries for profit. In this paper, we propose a blockchain-based privacy preserving e-health system to ensure the security and confidentiality of the patients’ EHRs. In the system, we introduce the pairing-based cryptography to generate the tamper-proof records of the EHRs and allow the patients to integrate them into the transactions deployed on the blockchain, which can make the patients’ EHRs verifiable and protect them from illegal modification. Moreover, we will design secure payment protocols by performing blockchain-based smart contracts, which can enable the patients and hospital to reliably pay for the diagnostic and storage service, respectively. Security analysis and the performance evaluation demonstrate that our proposed scheme is secure and efficient with a limited computation overhead.

Mitigation of Malware Effect using Cyber Threat Analysis using Ensemble Deep Belief Networks

Cybersecurity is a technique that entails security models development techniques to the illegal access, modification, or destruction of computing resources, networks, program, and data. Due to tremendous developments in information and communication technologies, new dangers to cyber security have arisen and are rapidly changing. The creation of a Deep Learning system requires a substantial number of input samples and it can take a great deal of time and resources to gather and process the samples. Building and maintaining the basic system requires a huge number of resources, including memory, data and computational power. In this paper, we develop an Ensemble Deep Belief Networks to classify the cybersecurity threats in large scale network. An extensive simulation is conducted to test the efficacy of model under different security attacks. The results show that the proposed method achieves higher level of security than the other methods.

A secure authorized deduplication scheme for cloud data based on blockchain

Deduplication scheme based on convergent encryption (CE) is widely-used in cloud storage system to eliminate redundant data. However, the adversaries can obtain the data by the brute-force attack, if the data belongs to a predictable set for CE. In addition, previous works usually introduce the third-party auditors to execute the data integrity verification, suffering from data disclosure by the auditors. In this paper, we propose a secure authorized deduplication scheme based on blockchain, which can ensure the confidentiality and security of the users' data stored on cloud servers. In our scheme, the users can utilize the smart contract to create a tamper-proofing ledger, which can protect the data from illegal modification. Meanwhile, the users can execute the integrity audit protocols to check the users’ data integrity by the smart contract. Moreover, a hierarchical role hash tree (HRHT) will be constructed to create the role key when the users upload their data to CSP, allowing the authorized users to access the data. Security analysis and performance evaluation demonstrate that our proposed scheme is resilient against the brute-force attack and the collusion attack, while it has limited computation overhead.

Evaluating the Prevalence of Illegal Structures Development in Osogbo, Southwest Nigeria

The study was designed to assess construction of illegal structures in Osogbo, Osun State, Nigeria. The specific objectives of the study include assessing the level of awareness of the respondents on national building regulation. The research examined the level of illegal structures in Osogbo and identified strategies to curb the incidence factors that account for the construction. In the methodology, a sample size of 142 was chosen for the study. Questionnaire administration and personal observation were deployed to elicit vital data from the respondents and the professional allies. Data generated from the survey were analyzed using the statistical tools such as descriptive statistics (percentages and frequencies) and the relative importance index. Findings revealed that 42% of the structures in Osogbo metropols was exclusively constructed without official permit or approval from relevant authorities; 58% of the existing structures had illegal modification whilst, illegal additions accounted for 71.7% of the structures. The findings of the survey indicated that institutional, physical, educational and socio-economic factors aided the proliferation of illegal development in the city. Observation further revealed that all the illegal structures in Osogbo were owned by the educated elites and such structures were either not completely occupied, thus attesting that the educated residents are major violators of building construction regulations. Findings further revealed that, imposition of high penalties on culprits by the local authority, automating of permit acquisition, monitoring and detection of illegal building operations are amongst the measures which could be instituted to address such a problem. The study concluded that there should be regular public education on building regulations. Moreover, there should be public-private partnership in curbing illegal structures and automating Permit acquisition, monitoring and detection of new structures by the authorities concerned.

The application of privacy protection and artificial intelligence technology in the information auxiliary system of the prevention and control of COVID-19/ 中华医学科研管理杂志

Objective The outbreak of novel coronavirus raised many problems in the auxiliary information system of epidemic prevention and control, which including the need to prevent key data from being illegal modification, traceability, lack of decision support systems at different levels, barriers to cross regional cooperation and low automation of case diagnosis. Methods In this paper, artificial intelligence, security computing supporting privacy protection, block chain and other emerging technologies are introduced into the epidemic prevention and control auxiliary information system. Results This paper discusses how to utilize modern cryptography and block chain technology to establish a traceability system that could assure the security of epidemic information; design a distributed decision support system; solve the privacy-preserving problems of Federated Learning based on SGX technology, and present a group architecture to alleviate the performance cost of SGX. Conclusions The schemes above can help to achieve the security and traceability of epidemic information, also improve the automation and decision-making efficiency of the auxiliary information system for epidemic prevention and control. Key words: Epidemic prevention and control; Privacy protection; Block chain; Artificial intelligence; Decision Support

Adaptive System to Improve Decision Making for Protecting Data Conveyed over WLAN

In the past two decades, the rapid growth of demand for wireless data communications has become evident due to the unreliability of wired data communications, which has become inadequate due to high costs and management monitoring of its security problems. Furthermore, such data may be intercepted when transmitted via wire connections with a negative attack and its contents changed with illegal modification. Therefore, due to these circumstances, there is an urgent need to protect data and achieve a wireless local area network (WLAN) for transmission. Data protection is therefore required through the design and implementation of a rigid algorithm that reduces the risk of hacking into wireless networks and prevents hackers from finding inevitable vulnerabilities in the data protection system. This research paper introduces a new technology to protect data from potential risks and provides a new “type” of encryption algorithms that minimizes these risks. This technology relies on the adoption of renewable rules proposed as production bases based on ambiguous logic to accomplish the construction of an intelligent data analysis system and move forward with appropriate protection decisions. The targeted packets for the local area network were captured and analyzed using open source software “WIRESHARK”. Unsupervised learning classifier was used to monitor the network and detect the malicious intruders. The flow data have been collected and features are extracted and analyzed to examine the transmitted packets which were classified and ranked to have a specific cluster. Minimizing and comprising risk taking in consideration the imprecise data which was achieved via fuzzy rules. The results were discussed and concluded that potential risks could be minimized by the production rules that control the proposed data for the transferred encryption system. MATLAB 2014 toolkit based on a laptop with an Intel I3 processor and 4GB RAM was used.

Cloud-assisted secure eHealth systems for tamper-proofing EHR via blockchain

The wide deployment of cloud-assisted electronic health (eHealth) systems has already shown great benefits in managing electronic health records (EHRs) for both medical institutions and patients. However, it also causes critical security concerns. Since once a medical institution generates and outsources the patients’ EHRs to cloud servers, patients would not physically own their EHRs but the medical institution can access the EHRs as needed for diagnosing, it makes the EHRs integrity protection a formidable task, especially in the case that a medical malpractice occurs, where the medical institution may collude with the cloud server to tamper with the outsourced EHRs to hide the medical malpractice. Traditional cryptographic primitives for the purpose of data integrity protection cannot be directly adopted because they cannot ensure the security in the case of collusion between the cloud server and medical institution.In this paper, a secure cloud-assisted eHealth system is proposed to protect outsourced EHRs from illegal modification by using the blockchain technology (blockchain-based currencies, e.g., Ethereum). The key idea is that the EHRs only can be outsourced by authenticated participants and each operation on outsourcing EHRs is integrated into the public blockchain as a transaction. Since the blockchain-based currencies provide a tamper-proofing way to conduct transactions without a central authority, the EHRs cannot be modified after the corresponding transaction is recorded into the blockchain. Therefore, given outsourced EHRs, any participant can check their integrity by checking the corresponding transaction. Security analysis and performance evaluation demonstrate that the proposed system can provide a strong security guarantee with a high efficiency.

Watermarking scheme using local binary pattern for image authentication and tamper detection through dual image

Watermarking scheme is an efficient solution to protect the multimedia document from unauthorized modification. Several watermarking scheme have been developed but authentication and tamper detection is still an important research issue. In this paper, a dual image‐based watermarking scheme has been developed using local binary pattern (LBP) to protect the multimedia document from illegal modification. The suggested method includes the following procedure: During watermark encoding the host image is partitioned into (3 × 3) nonoverlapping blocks. Then generate system vector (s) using LBP and perform XOR with secret watermark bits. Two bits authentication code is generated from S vector and embed within dual image depending in a shared secret key (δ). At the receiver end, the embedded watermark, authentication code, and original cover image can be successfully recovered from dual watermarked image. After that authentication process has been carried out by comparing extracted authentication code and the regenerated authentication code. The experimental results are compared with the state‐of‐the‐art methods to show the effectiveness of our proposed scheme. It is observed that the proposed scheme is secure and robust against different standard attacks meanwhile it can detect message integrity within the watermarked object.