Property Theft Research Articles

Mapping Real-World Use of the Onion Router

Since its inception, The Onion Router (TOR) has been discussed as an anonymizing tool used for nefarious purposes. Past scholarship has focused on publicly available lists of onion URLs containing illicit or illegal content. The current study is an attempt to move past these surface-level explanations and into a discussion of actual use data; a multi-tiered system to identify real-world TOR traffic was developed for the task. The researcher configured and deployed a fully functioning TOR “exit” node for public use. A Wireshark instance was placed between the node and the “naked” internet to collect usage data (destination URLs, length of visit, etc.), but not to deanonymize or otherwise unmask TOR users. For 6 months, the node ran and collected data 24 hr per day, which produced a data set of over 4.5 terabytes. Using Python, the researcher developed a custom tool to filter the URLs into human-readable form and to produce descriptive data. All URLs were coded and categorized into a variety of classifications, including e-commerce, banking, social networking, pornography, and cryptocurrency. Findings reveal that most TOR usage is rather benign, with users spending much more time on social networking and e-commerce sites than on those with illegal drug or pornographic content. Likewise, visits to legal sites vastly outnumber visits to illegal ones. Although most URLs collected were for English-language websites, there were a sizable amount for Russian and Chinese sites, which may demonstrate the utilization of TOR in countries where internet access is censored or monitored by government actors. Akin to other new technologies which have earned bad reputations, such as file-sharing program BitTorrent and intellectual property theft or cryptocurrency Bitcoin and online drug sales, this study demonstrates that TOR is utilized by offenders and non-offenders alike.

China Chipmaking Industry’s Countermeasures Toward U.S. Sanctions and the Most Recent Achievements

The Sino-US technology war has greatly impacted China’s technological sector, including the semiconductor industry, which is instrumental in the production of technological products that are crucial in commercial and military technology. Previous research has failed to explore the specific development situation and development prospects of the leading emerging technology companies in China. Hence, this research aimed at addressing the identified gap in the literature on the Sino-US technology war, using a case study approach that focused on three main companies in China’s RF chip industry: Maxscend, Vanchip, and Microgate. Generally, the results reveal that although China’s domestic RF chip industry has grown rapidly in preparation for self-sufficiency, local companies in the industry are still facing several obstacles that are hindering self-sufficiency, mainly competition from the US, Japan, and other developed RF chip industries. Consistent with previous research, this case study urges the Chinese government to continue providing subsidies to its semiconductor industry and ensure that local technology companies have adequate funding for their development projects. Additionally, this case study proposes that the Chinese government should collaborate with local technology companies to increase human capital, since inadequate human capital is identified as a key barrier in China’s progress toward achieving self-sufficiency. Furthermore, China should make improvements in explicit knowledge transfers, as advancements in aspects such as intellectual property theft will assist local companies in keeping pace with the competition in the global semiconductor industry.

AutoCRW: Learning based robust watermarking for smart city applications

AbstractDeep learning has become a promising model in the industry due to its superior learning accuracy and efficiency. In addition to conventional applications, such as fraud detection, natural language processing, image classification and reconstruction, object detection and segmentation this model can be widely used for data hiding, that is, watermarking. Existing transformed‐domain‐based watermarking provided better robustness toward attacks. In this article, an interesting autoencoder convolutional neural network (CNN)‐based watermarking technique, AutoCRW, is proposed, which can prevent intellectual property theft of digital images. First, the autoencoder functionality of CNN generates two versions of the same image, namely positive and negative version of the images, which decompose by a transformed domain scheme. Then, watermark information is embedded into the output images, which can be extracted to realize copyright protection and ownership verification. Finally, a denoising convolutional neural network (DnCNN) is employed over the extracted mark to ensure the robustness of the watermarking system. Extensive experiments demonstrate that the proposed algorithm has high invisibility and good robustness against several attacks.

A New Optimal Method for the Secure Design of Combinational Circuits against Hardware Trojans Using Interference Logic Locking

Effective resistance to intellectual property theft, reverse engineering, and hardware Trojan insertion in integrated circuit supply chains is increasingly essential, for which many solutions have been proposed. Accordingly, strong attacks are also designed in this field. One way to achieve the above goal is obfuscation. The hardware obfuscation method hides the primary function of the circuit and the normal Netlist from the attacker by adding several key gates in the original Netlist. The functionality circuit is correct only if the correct key is applied; otherwise, the circuit is obfuscated. In recent years, various obfuscation methods have been proposed. One is logic locking, the most prominent hardware protection technique since it can protect against untrusted items. Logic locking induces functional and structural changes to a design even before the layout generation. We secured the circuit against hardware Trojan insertion with a secure logic locking method based on the insertion of key gates in interference mode. We call our proposed method Secure Interference Logic Locking, SILL. SILL is based on minimum controllability in paths with maximum fan-out. In this method, we have reduced the number of key gates required for circuit obfuscation and created the maximum Hamming distance between normal and obscure outputs. In addition, the key gates are added to the circuit’s complete interference, and the AES algorithm is used to generate the key. Our proposed method, SILL, was simulated in the Vivado simulation environment; the algorithms used in this method were prepared in VHDL language and designed to allow parallel execution, then applied on the original Netlist of the ISCAS85 benchmark circuits. By analyzing and comparing the results of this simulation to recent works, the amount of hardware consumption has decreased (about 5% space consumption and about a 0.15-nanosecond time delay). Then, the SAT attack algorithm was tested on ISCAS85 benchmark circuits that were obfuscated with SILL. The execution time of the attack in the second attempt was 0.24 nanoseconds longer compared to similar recent works, and it timed out in the fourth attempt. The resistance of our proposed method, having less hardware overhead and higher speed is more effective against SAT attacks than the existing conventional methods.

Network intrusion detection system for DDoS attacks in ICS using deep autoencoders

Anomaly detection in industrial control and cyber-physical systems has gained much attention over the past years due to the increasing modernisation and exposure of industrial environments. Current dangers to the connected industry include the theft of industrial intellectual property, denial of service, or the compromise of cloud components; all of which might result in a cyber-attack across the operational network. However, most scientific work employs device logs, which necessitate substantial understanding and preprocessing before they can be used in anomaly detection. In this paper, we propose a network intrusion detection system (NIDS) architecture based on a deep autoencoder trained on network flow data, which has the advantage of not requiring prior knowledge of the network topology or its underlying architecture. Experimental results show that the proposed model can detect anomalies, caused by distributed denial of service attacks, providing a high detection rate and low false alarms, outperforming the state-of-the-art and a baseline model in an unsupervised learning environment. Furthermore, the deep autoencoder model can detect abnormal behaviour in legitimate devices after an attack. We also demonstrate the suitability of the proposed NIDS in a real industrial plant from the alimentary sector, analysing the false positive rate and the viability of the data generation, filtering and preprocessing procedure for a near real time scenario. The suggested NIDS architecture is a low-cost solution that uses only fifteen network-based features, requires minimal processing, operates in unsupervised mode, and is straightforward to deploy in real-world scenarios.

ПІДТВЕРДЖЕННЯ РОЗМІРУ ЗБИТКУ, ЗАВДАНОГО ВНАСЛІДОК ЗНИЩЕННЯ, ПОШКОДЖЕННЯ, РОЗКРАДАННЯ МАЙНА ПІДПРИЄМСТВ, ЯКІ ПЕРЕБУВАЛИ НА ТИМЧАСОВО ОКУПОВАНИХ ТЕРИТОРІЯХ АБО В РАЙОНАХ ПРОВЕДЕННЯ БОЙОВИХ ДІЙ

During the entire period of the full-scale invasion of the Russian Federation on the territory of Ukraine, every day the country's economy loses property owned by private individuals, legal entities, territorial communities, and the state. In order to compensate for property lost during wartime, which was destroyed, stolen, damaged, it is important to correctly and timely document all the processes that preceded and caused the destruction or damage of such property. Equally important during martial law is the correctness and timeliness of documentation of lost property located in territories not controlled by Ukraine (temporarily occupied). The correctness and timeliness of documenting the loss, destruction or theft of enterprise property is quite relevant, since the state is currently developing new or improving already developed mechanisms and procedures for compensation for losses (damages) that were caused as a result of the introduction of hostilities into the territory of business entities or and temporary occupation of the territory where these subjects are located. For the purpose of documentary confirmation of the fact of destruction, theft and damage to the property of enterprises, a forensic economic examination is conducted, one of the tasks of which is to document the extent of the shortage of goods and material values at enterprises and their structural units. The enterprise must document the results of destruction, damage, theft of property. For this purpose, appropriate entries are made in the accounting and reporting documents, and at the same stage it is essential to carry out an inventory, since the way to check the actual availability of the company's property is to carry out an inventory. Inventory is an independent way of actually controlling the movement of goods and material values and ensuring the reality of accounting data. Conducting research on the lack of goods and material values that were the result of military (combat) actions is a rather painstaking, responsible process that requires a forensic expert to carefully study both regulatory and legal acts with a check of their validity at the time of the inventory, as well as accounting and reporting documents.

Material-level countermeasures for securing microfluidic biochips.

Flow-based microfluidic biochips (FMBs) have been rapidly commercialized and deployed in recent years for biological computing, clinical diagnostics, and point-of-care-tests (POCTs). However, outsourcing FMBs makes them susceptible to material-level attacks by malicious actors for illegitimate monetary gain. The attacks involve deliberate material degradation of an FMB's polydimethylsiloxane (PDMS) components by either doping with reactive solvents or altering the PDMS curing ratio during fabrication. Such attacks are stealthy enough to evade detection and deteriorate the FMB's function. Furthermore, material-level attacks can become prevalent in attacks based on intellectual property (IP) theft, such as counterfeiting, overbuilding, etc., which involve unscrupulous third-party manufacturers. To address this problem, we present a dynamic material-level watermarking scheme for PDMS-based FMBs with microvalves using a perylene-labeled fluorescent dye. The dyed microvalves show a unique excimer intensity peak under 405 nm laser excitation. Moreover, when pneumatically actuated, the peak shows a predetermined downward shift in intensity as a function of mechanical strain. We validated this protection scheme experimentally using fluorescence microscopy, which showed a high correlation (R2 = 0.971) between the normalized excimer intensity change and the maximum principal strain of the actuated microvalves. To detect curing ratio-based attacks, we adapted machine learning (ML) models, which were trained on the force-displacement data obtained from a mechanical punch test method. Our ML models achieved more than 99% accuracy in detecting curing ratio anomalies. These countermeasures can be used to proactively safeguard FMBs against material-level attacks in the era of global pandemics and diagnostics based on POCTs.

ViMDH: Visible-Imperceptible Medical Data Hiding for Internet of Medical Things

Over the recent years, volume of medical images and related digital records, called electronic medical records, generated, shared, and stored by different intelligent devices, sensors, and Internet of medical things networks, to name a few, has drastically increased. Such records are shared by cloud providers for storage and further processing. However, an increasingly serious concern is the illegal copying, modification, and forgery of medical records. This article presents a visible and imperceptible medical data hiding technique, namely ViMDH, which can prevent to intellectual property theft of medical records. The carrier image is visibly marked with logo mark, which is suitable for owner identification and avoid illegal duplication, and then an imperceptible data hiding based on nonsubsampled shearlet transform (NSST), redundant discrete wavelet transform (RDWT), and multiresolution singular value decomposition is introduced. Finally, key-based encryption scheme designed by RDWT-RSVD ensure the security of the watermarking system. Under the experimental evaluation, our ViMDH is not only visible and imperceptible, but also has a satisfactory advantage in robustness and security compared with the traditional watermarking schemes.

THE USE OF NFT TOKENS IN THE ERA OF DIGITAL TRANSFORMATION: PROSPECTS FOR IMPLEMENTATION

Purpose. The aim of the article is to study the peculiarities of NFT for the development of modern business and other important processes related to the preservation and protection of property rights for the implementation of digital assets. Methodology of research. This study is based on scientific research on the formation and functioning of NFT tokens in the digital market. The study employed various methods including dialectical analysis, expert evaluation of publications and opinions, statistical analysis of NFT token dynamics, system analysis for theoretical generalisations and establishing structural links between the elements of the studied system, and abstract and logical methods for formulating conclusions and recommendations and others. Findings. The article examines the importance of using NFT tokens as a technologically important tool for preserving ownership based on non-reciprocity, which allows you to secure these rights for token owners and preserve the originality of the objects of application of these tokens. This, in turn, involves establishing the value of implementing technologies in art, culture, musical works, as well as in the field of virtual reality, collecting objects, and including, in the real sector of the economy, connecting the data of digital assets with the real services of corporations. Originality. The article substantiates the essence of NFT tokens, their value and features of application based on non-reciprocity technology, which reveals the scientific and practical significance of their application. The ability to use these tokens to authenticate and trace the provenance of digital content, address issues related to plagiarism and intellectual property theft, increase trust in digital assets, and preserve information integrity indicates that NFT technology is the digital certificate of authenticity that proves creation of assets, the right to own them, records and stores the history of transactions or accounting of trading operations. Practical value. The main provisions of the article can be used by domestic business entities to determine the priority areas of digitization and future potential developments based on NFT technologies using the experience of leading leaders in this field. Further research can be aimed at introducing this technology into the business processes of companies that plan to promote their brand on the global market, tokenize their own services, and digitize business processes using customer engagement. Also, NFT technology is changing the key role in the development of virtual reality, in particular the ideas on the basis of which Metaverses are being developed. Key words: NFT token, NFT technology, blockchain, Web 3.0, digital assets.

Public transport stops and crime within the city space. The case of Stare Bałuty in Łódź

The goals of the study presented in the article draw attention to the role of public transport stops in the spatial distribution of crime in the Stare Bałuty estate in Łódź, Poland. Answers are provided to the questions of spatio-temporal structure of criminal acts committed within the estate, the influence zone of transport stops as well as the assessment and effects of environmental crime predictors in their vicinity. Crime location quotient (LQC) was used to assess the intensity of crime and identify the influence zone that attracts certain categories of crimes to the vicinity of stops. The influence of environmental predictors on the level of threat was identified and assessed on the basis of B. Czarnecki’s method. The variables used in the analysis initially spanned 739 crimes and 53 public transport stops evaluated with regard to 20 safety aspects and their impact on the pro-crime effects on the scale of location as well as various forms and functions of urban development. A strong negative influence of public transport stops ‒ attracting various categories of crime, mostly property theft ‒ was discovered. The negative influence of stops on the concentration of crime within 200 metres is reinforced by the existence of environmental crime predictors. The recommendations and discussions resulting from the findings should influence the policy of crime prevention on the level of object location, management and the maintenance of socio-spatial order in the vicinity.

The Peasant Revolution in Naddniprianshchyna (1917–1920) on the pages of «The Chervona Kalyna Chronicle»

The purpose of the article is to explore and evaluate the attitude towards the events of the peasant revolution in Naddniprianshchyna among the eyewitnesses – soldiers of the Galician units, participants of the national liberation movement of 1914–1921 in «Greater Ukraine». Research methods: historical-chronological, comparative, and descriptive. The main results: the article reveals the specifics of the military-historical memoirs published on the pages of the journal «The Chervona Kalyna Chronicle», as a source of the history of the Peasant revolution in Naddniprianshchyna. Four categories of authors writing for «The Chervona Kalyna Chronicle» on peasant issues were identified: participants of the Ukrainian national movement in Naddniprianshchyna (M. Mykhailyk, F. Meleshko, Ya. Vodianyi); prisoners of war of the Austro-Hungarian army and the Legion of Ukrainian Sich Riflemen (S. Stechyshyn, V. Struk); senior officers of the «Kyiv» Sich Riflemen (I. Andrukh and I. Vyslotskyi); foremen and riflemen of the UGA (Ukrainian Galician Army). The first two categories of authors were either local residents or lived among the peasantry for a long time and painted a coherent, albeit contradictory, picture of the development of events in the Ukrainian countryside in 1917 – early 1918: their main concern was the activation of national-democratic forces and the growth of social struggle in peasants against landlords, radicalization of military-political confrontation. The authors of the third category, who came from the ranks of the Ukrainian Sich Riflemen, pointed out the indifferent attitude of the peasants to the national idea, traced the evolution of the attitudes of the peasantry of Naddniprianshchyna under the conditions of the Hetmanate of P. Skoropadskyi and other political regimes. The fourth group of authors (the UGA soldiers) is the largest. Their articles are devoted to the turning points in the development of the Ukrainian revolution: the transition to Zbruch, the typhus epidemic, and the split of the UGA, alliances with the Volunteer Army of A. Denikin and the Bolsheviks. Against the background of these military and political events, the problem of relations between the military and the peasantry can be clearly traced throughout the entire path of the UGA. The UGA soldiers focused their attention on such negative phenomena among the peasants as desertion, reluctance to fight for Ukrainian statehood, theft of military property, and hostile attitude towards sick soldiers. At the same time, the UGA soldiers contributed to the growth of the national consciousness of the population of Naddniprianshchyna. The mosaic fragments of relations with the peasantry, which contain memories, diaries, and essays of the UGA soldiers, are a valuable source of the history of the Peasant revolution in Naddniprianshchyna in 1917–1920. Practical significance: the results of the research can be useful in conducting general studies on the peasantry, compiling textbooks, and training manuals, in the preparation of lectures and seminar courses in institutions of higher education, and in local history workshops. Scientific innovation: for the first time, a complex of military-historical memoirs published in the «The Chervona Kalyna Chronicle» has been summarized and considered in the context of peasant research discourse and, in particular, the peasant revolution. Type of the article: research.

Insider Threat Detection Using Machine Learning Approach

Insider threats pose a critical challenge for securing computer networks and systems. They are malicious activities by authorised users that can cause extensive damage, such as intellectual property theft, sabotage, sensitive data exposure, and web application attacks. Organisations are tasked with the duty of keeping their layers of network safe and preventing intrusions at any level. Recent advances in modern machine learning algorithms, such as deep learning and ensemble models, facilitate solving many challenging problems by learning latent patterns and modelling data. We used the Deep Feature Synthesis algorithm to derive behavioural features based on historical data. We generated 69,738 features for each user, then used PCA as a dimensionality reduction method and utilised advanced machine learning algorithms, both anomaly detection and classification models, to detect insider threats, achieving an accuracy of 91% for the anomaly detection model. The experimentation utilised a publicly available insider threat dataset called the CERT insider threats dataset. We tested the effect of the SMOTE balancing technique to reduce the effect of the imbalanced dataset, and the results show that it increases recall and accuracy at the expense of precision. The feature extraction process and the SVM model yield outstanding results among all other ML models, achieving an accuracy of 100% for the classification model.

Model of Execution Trace Obfuscation Between Threads

Advanced reverse analysis tools have significantly improved the ability of attackers to crack software via dynamic analysis techniques, such as symbol execution and taint analysis. These techniques are widely used in malicious fields such as vulnerability exploitation or theft of intellectual property. In this paper, we present an obfuscation strategy called “execution trace obfuscation,” wherein the program execution trace repeatedly switches between multiple threads. Our technique realizes equivalent code transformation by abstracting the obfuscation problems into pruning, cloning, and coloring problems in graph theory. Based on this, we further propose the cascade encryption of a function that depends on execution trace information with a key derived from the function address calculation process, followed by removing this key from the program. We have implemented a compiler-level system that inputs a source program and automatically generates an obfuscated file. Finally, random test proves the universality of obfuscation algorithm and verify the system’s performance. Results shows that our system can effectively interfere advanced reverse analysis tools.

A Neural Network-Based Cognitive Obfuscation Toward Enhanced Logic Locking

Logic obfuscation is introduced as a pivotal defense against multiple hardware threats on Integrated Circuits (ICs), including reverse engineering (RE) and intellectual property (IP) theft. The effectiveness of logic obfuscation is challenged by the recently introduced Boolean satisfiability (SAT) attack and its variants. A plethora of countermeasures has also been proposed to thwart the SAT attack. Irrespective of the implemented defense against SAT attacks, large power, performance, and area overheads are indispensable. In contrast, we propose a cognitive solution: a neural network-based unSAT clause translator, SATConda, that incurs a minimal area and power overhead while preserving the original functionality with impenetrable security. SATConda is incubated with an unSAT clause generator that translates the existing conjunctive normal form (CNF) through minimal perturbations such as the inclusion of pair of inverters or buffers or adding a new lightweight unSAT block depending on the provided CNF. For efficient unSAT clause generation, SATConda is equipped with a multi-layer neural network that first learns the dependencies of features (literals and clauses), followed by a long-short-term-memory (LSTM) network to validate and backpropagate the SAT-hardness for better learning and translation. Our proposed SATConda is evaluated on ISCAS85 and ISCAS89 benchmarks and is seen to defend against multiple state-of-the-art successfully SAT attacks devised for hardware RE. In addition, we also evaluate our proposed SATCondas empirical performance against MiniSAT, Lingeling and Glucose SAT solvers that form the base for numerous existing deobfuscation SAT attacks.

Learning to Find Usages of Library Functions in Optimized Binaries

Much software, whether beneficent or malevolent, is distributed only as binaries, sans source code. Absent source code, understanding binaries' behavior can be quite challenging, especially when compiled under higher levels of compiler optimization. These optimizations can transform comprehensible, "natural" source constructions into something entirely unrecognizable. Reverse engineering binaries, especially those suspected of being malevolent or guilty of intellectual property theft, are important and time-consuming tasks. There is a great deal of interest in tools to "decompile" binaries back into more natural source code to aid reverse engineering. Decompilation involves several desirable steps, including recreating source-language constructions, variable names, and perhaps even comments. One central step in creating binaries is optimizing function calls, using steps such as inlining. Recovering these (possibly inlined) function calls from optimized binaries is an essential task that most state-of-the-art decompiler tools try to do but do not perform very well. In this paper, we evaluate a supervised learning approach to the problem of recovering optimized function calls. We leverage open-source software and develop an automated labeling scheme to generate a reasonably large dataset of binaries labeled with actual function usages. We augment this large but limited labeled dataset with a pre-training step, which learns the decompiled code statistics from a much larger unlabeled dataset. Thus augmented, our learned labeling model can be combined with an existing decompilation tool, Ghidra, to achieve substantially improved performance in function call recovery, especially at higher levels of optimization.

International and domestic experience of intellectual property legal protection on the Internet and separate methods of police crimes detection in this area

The history of the development of international legislation and the conclusion of international treaties regarding the protection of intellectual property, starting with the Berne Convention on the Protection of Literary and Artistic Works, was considered. The World Convention on Copyright, the Agreement on Trade Aspects of Intellectual Property Rights, and the Copyright Agreement of the World Intellectual Property Organization were analyzed. An attempt to sign an Anti-Counterfeiting Trade Agreement was tracked. The history of the adoption of laws on the protection of intellectual property in the USA “On Combating Online Piracy” (SOPA) and “On Prevention of Real Network Threats to Economic Creativity and Theft of Intellectual Property” (PIPA) was studied.
 The legal framework of the EU regarding the protection of intellectual property rights on the Internet, in particular Directive No. 2019/789 of the European Parliament and the Council dated April 17, 2019, which establishes the application of the provisions of copyright and related rights to individual online broadcasts of broadcasting organizations and retransmissions of radio and television programs, and Directive No. 2019/790 of the European Parliament and the Council dated April 17, 2019 on copyright and related rights in the single digital market were concidered. The legislative framework of Ukraine aimed at protecting intellectual property rights and preventing illegal distribution of media content was analyzed, in particular the Laws of Ukraine “On Copyright and Related Rights” and “On State Support of Cinematography”. Forms of illegal distribution of media content are defined. An analysis of telecommunication means on the Internet identification methods during forensic telecommunications examination was carried out. The methods used now were considered, and their main shortcomings were described. Alternative methods of identification were proposed.

Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform

Historically, threat information sharing has relied on manual modelling and centralised network systems, which can be inefficient, insecure, and prone to errors. Alternatively, private blockchains are now widely used to address these issues and improve overall organisational security. An organisation’s vulnerabilities to attacks might change over time. It is utterly important to find a balance among a current threat, the potential countermeasures, their consequences and costs, and the estimation of the overall risk that this provides to the organisation. For enhancing organisational security and automation, applying threat intelligence technology is critical for detecting, classifying, analysing, and sharing new cyberattack tactics. Trusted partner organisations can then share newly identified threats to improve their defensive capabilities against unknown attacks. On this basis, organisations can help reduce the risk of a cyberattack by providing access to past and current cybersecurity events through blockchain smart contracts and the Interplanetary File System (IPFS). The suggested combination of technologies can make organisational systems more reliable and secure, improving system automation and data quality. This paper outlines a privacy-preserving mechanism for threat information sharing in a trusted way. It proposes a reliable and secure architecture for data automation, quality, and traceability based on the Hyperledger Fabric private-permissioned distributed ledger technology and the MITRE ATT&CK threat intelligence framework. This methodology can also be applied to combat intellectual property theft and industrial espionage.

Cybercrime and its Violation of Digital Platform Security: An Islamic Law Perspective

The sophistication of today's technology has seen an increase in the demand for online services involving various matters. Although this has a positive impact, this sophistication is potentially misused by certain parties for criminal purposes. Cybercrime is a modern crime that is increasing along with the enlightenment of communication and information technology. Property theft crimes include hacking, scamming, phishing, forgery of credit cards and bank account cards, and illegal money transfers. Cyber crimes are becoming more prevalent nowadays. Therefore, this study is important in exploring the violation of cybercrime on digital platform security form Islamic law perspective. Thus, this study aims to identify the forms of cybercrime in today's digital platforms and their punishment through Islamic law. The study was conducted qualitatively using literature data such as theses and journals to examine the elements of cybercrime according to Islamic law. The study's findings were analyzed inductively to determine today's cybercrime punishments on digital platforms. The change of criminal background from physical to digital format is a new thing that previous Muslim scholars did not discuss. However, the four basic principles of crime set, namely the concept of digital property, transfer of property, invasion of control, and no doubt allow the perpetrator to be convicted of the crime of theft according to Islamic law if they meet the conditions set. Further field research is proposed to obtain more authentic data related to the violation of cyber crime among digital platform’s user.

Analisis Viktimologi Terhadap Tindak Pidana Pencurian Kendaraan Di Tanjungpinang Kepulauan Riau

This paper will discuss the victimization analysis of the role of the victim in the occurrence of the crime of theft of two-wheeled vehicles with a case study of decision number: 29/Pid.B/2022/PN Tpg located in Tanjungpinang City. The background of this research is the crime of theft of property in this case two-wheeled vehicles with the aim of this research is to analyze how the role of the victim so that a crime occurs. The method used is descriptive analysis with secondary data sources. Theft is an act done intentionally to take other people's property against the law. This crime is classified as a crime against property that gives results and is classified as having a decent economic value for the perpetrators. This study will discuss victimization starting from the definition, scope, involvement, and perspective of the victim's responsibility. The conclusion is that crime does not necessarily arise from the perpetrator but the victim also provides an opportunity by leaving the motorbike key depending on the motorbike in a quiet and unsupervised yard.

Legal foundations of the organization and activities of the Ukrainian SSR police in 1949–1950s

The main aspects of the structure of the police in 1949–1950 and the main directions of its activity have been studied. The changes in the Criminal Procedure Code of the Ukrainian SSR guided by the police in the performance of their law enforcement functions have been highlighted. It has been noted that the structure of local police bodies in the regions of Ukraine in the post-war period was of the same type, but could differ depending on operational conditions in the number of regular units. The most important change in the structure of the Ministry of Internal Affairs during this period was the transfer of the police to the Ministry of State Security in October 1949. The activities of the police were controlled and regulated by decisions and resolutions of the Communist Party of Ukraine. First of all, it concerned the selection of personnel and education of police personnel. The central governing body of the police was the Main Directorate of the Police. The police departments of the Union republics, regions, large cities, district departments and branches, military units of the police were subordinate to it. At the same time, the heads of these police bodies held the positions of deputy people’s commissars of internal affairs of the republics, heads of regional NKVD (People’s Commissary of Internal Affairs) departments, heads of departments and NKVD departments of cities and districts.
 The causes of crime in the specified period have been analyzed. Considerable attention has been paid to the work of the police in combating crime, which was carried out in the following areas: 1) prevention and detection of crimes by structural units of the police (criminal investigation and fight against theft of socialist property and speculation); 2) conducting inquiries and performing a number of investigative functions. Factors that did not allow the police to fully perform their functions in the fight against crime were: 1) insufficient use of scientific and technical means; 2) lack of an extensive agent-informant network; 3) lack of professional personnel; 4) violation of “socialist legality” during inquiry and investigation; 5) involvement of operatives of criminal investigation and employees of anti-theft of socialist property and speculation of the BRSVS (the department for combating embezzlement of socialist property and speculation) to perform functions that are not specific to them. The practical activity of police bodies for the protection of public order was determined by the following directions: 1) administrative activity (patrol in populated areas, compliance with the rules of the passport and permit system, regulation of street traffic); 2) involvement of state institutions, public organizations and citizens in cooperation; 3) creation of voluntary formations - police assistance brigades and public order protection groups.