Illegal Users Research Articles

A Compressed Domain Robust Video Watermarking Resists Geometric Attack

The widespread utilization of mobile devices and the proliferation of video content, facilitated by communication networks, has unfortunately led to issues such as data piracy, illegal usage, and unauthorized sharing. To address these challenges, digital watermarking emerges as a crucial tool, serving purposes such as authentication, maintaining integrity, and identifying rightful owners. In the realm of video watermarking, two primary categories exist: watermarking in the compressed domain and watermarking in the uncompressed domain. Compressed domain watermarking involves expedited data processing through partial video decoding, whereas uncompressed domain watermarking requires more time. This article proposes a novel video watermarking methodology designed specifically to withstand geometric attacks. The proposed method aims to dynamically embed watermarks within video content, thereby enhancing resilience against various geometric distortions. Geometric attacks, including scaling, rotation, cropping, and translation, pose significant challenges in digital watermarking and are thus a focal point of this research. The objective is to integrate this approach with complex video coding standards, leveraging compression domain techniques to fortify resistance against geometric attacks. Tests show that the suggested video watermarking system works well. Not only does it excel in safeguarding against geometric attacks, but it also mitigates perceptual quality degradation, thus ensuring a balance between robustness and visual fidelity. As the prevalence of video content continues to grow, robust watermarking techniques like the one presented here play a vital role in preserving intellectual property rights and ensuring the integrity of multimedia content in the digital age.

Combating Web Tracking: Analyzing Web Tracking Technologies for User Privacy

Behind everyday websites, a hidden shadow world tracks the behavior of Internet users. Web tracking analyzes online activity based on collected data and delivers content tailored to users’ interests. It gathers vast amounts of information for various purposes, ranging from sensitive personal data to seemingly minor details such as IP addresses, devices, browsing histories, settings, and preferences. While Web tracking is largely a legitimate technology, the increase in illegal user tracking, data breaches, and the unlawful sale of data has become a growing concern. As a result, the demand for technologies that can detect and prevent Web trackers is more important than ever. This paper provides an overview of Web tracking technologies, relevant research, and website measurement tools designed to identify web-based tracking. It also explores technologies for preventing Web tracking and discusses potential directions for future research.

Personal and social connection to psychedelics is associated with lower drug use stigma among psychiatrists in the United States

AbstractBackground and AimsThis study sought to identify patterns of psychedelic use among American psychiatrists, to compare the demographic variables across categories of social proximity and personal use, and to determine how these categories influenced psychiatrists' attitudes towards drugs and people who use drugs.MethodsRespondents (N = 180; mean age = 48.4 [SD = 16.2]; male = 65.5%; trainees = 24.1%) were recruited via email lists/listservs and personal networks (snowball sampling).ResultsApproximately one-third (32.8%) of psychiatrists reported Personal Connection (i.e., history of personal use and social connection) to psychedelics. Psychiatrists with Personal Connection to psychedelics were more likely to be younger (p = 0.006, ηp2 = 0.057) and have fewer years of practice (p = 0.008, ηp2 = 0.058). Almost all (92%) of those with No Connection to psychedelics were out of training, compared with only 8% of those in training. Those with Personal and Social Connection to psychedelics were more likely to disagree: that using illegal drugs is morally wrong (p < 0.001, ηp2 = 0.28), that illegal drug users should go to prison (p < 0.001, ηp2 = 0.15), are weak minded (p < 0.001, ηp2 = 0.10), have no future (p < 0.001, ηp2 = 0.12), are not well educated (F(2.0, 170) = 7.38. p < 0.001, ηp2 = 0.08), are dishonest (p < 0.001, ηp2 = 0.10), and that illegal drug users ‘make me angry’ (p < 0.001, ηp2 = 0.10).ConclusionsPersonal and social connection to psychedelics is associated with decreased stigma towards drug use and people who use drugs. Future research should examine whether proximity to psychedelic use impacts other factors (e.g., empathy, therapeutic alliance) involved in psychiatry training and practice.

Blockchain-based privacy-preserving public key searchable encryption with strong traceability

Public Key Searchable Encryption (PKSE) has essential applications in cloud storage because it allows users to search over encrypted data. To identify illegal users, many traceable PKSE schemes have been proposed. However, existing schemes cannot trace the keywords that illegal users searched and protect users’ privacy simultaneously. It is challenging to bind users’ identities and keywords while protecting their privacy. Moreover existing traceable PKSE schemes do not consider the unforgeability and immutability of trapdoor query records which leads to frame-up and denial. In this paper, to address these problems, we propose a blockchain-based privacy-preserving PKSE with strong traceability (BP3KSEST) scheme. The main features of our scheme are as follows: (1) authorized users can obtain trapdoors from trapdoor generation center without releasing their identities and keywords; (2) When required, a trusted third party (TTP) can trace both illegal users’ identities and the keywords which they searched; (3) trapdoor query records are unforgeable and immutable. This scheme is appropriate for scenarios where privacy must be addressed, e.g, electronic health record (EHR). We formalize the definition and security model of our BP3KSEST scheme. Furthermore, we present a concrete construction and prove its security. Finally, the implementation is conducted to analyze its efficiency.

Design of the pistol P1 weapon storage system shelf using fingerprint electronic system in the TNI-AD units

One of the most important aspects of preventing illegal usage of firearms is safe storage. An inventive way to guarantee that only authorized owners can access the firearms is to incorporate fingerprint technology into the design of electric firearm storage systems. The use of fingerprint technology to increase the security of gun storage is desperately needed. However, issues with the finger's health, such as stains, cuts, and dampness, can impair the accuracy of the detection. This study employs a quantitative methodology using five fingerprint detection situations to test the accuracy of the system. The Arduino ESP was used as the foundation for the system implementation throughout the nine months that the research was conducted at the Kodiklatad Poltekad Electronics Laboratory. According to the test results, the system has 100% accuracy in identifying five different fingerprint detecting scenarios. But limitations are implied by the system's incapacity to identify damp, damaged, or dusty fingertips. Consequently, further thought must be given to these circumstances in order to improve system reliability. The design of an electric gun storage unit using Arduino ESP-based fingerprint technology has the potential to increase the security of gun storage, but more work is needed to address some issues that limit detection accuracy

A multinomial logit model analysis of determinants of community forest management approaches: evidence from northern Ethiopia.

Abstract For efficient and sustainable forest management, community engagement and participation are crucial. Sustainable forest management requires decision-making, plantation, and management approaches, in addition to the importance of indigenous knowledge and community opinions. The study examined the determinants of community-based forest management practices in Ethiopian Raya-Alamata Woreda. A semi-structured questionnaire was given to 195 randomly chosen sample respondents as part of the survey in order to gather primary data. Additionally, key informants, development agents, woreda forest supervisors, and local administrators were interviewed. Secondary data were gathered from books, woreda agriculture office, and scientific publications. The data was analyzed using a multinomial logit model and descriptive statistics. The results showed that distance to the forest negatively influenced participation in decision-making, while sex, education, and TLU positively influenced it. Age, home proximity to the forest, market distance, and tropical livestock unit negatively influenced participation in plantation. Age, family size, forest location, and association membership positively influenced decision-making and management approaches. To promote all-inclusive forest management, the study recommends the distribution of forestry-related educational materials, legal action against illegal users, switching to alternative energy sources, and encouraging female-headed households.

Review on Verifiable Outsourcing of Industrial Internet Data in Securely Shared

With the rapid development of information technology, industrial Internet has also entered a rapid development stage. As cloud servers have huge storage space as well as powerful computing power, more and more resource-constrained factories outsource their data to cloud servers for computation and storage to reduce the burden of data owners. Industrial data contains information about industrially produced products, and the high value of such information attracts attacks from illegal users, which may lead to data leakage. In addition, cloud servers are not fully trustworthy; therefore, it is important to ensure the security and correctness of industrial Internet data during outsourced computation and storage for the healthy development of the industrial Internet. In this paper, we explore technical solutions to guarantee the security and correctness of industrial Internet data when outsourcing computation, to achieve the privacy protection of industrial Internet data.

Asymmetric fingerprinting protocol for vector map based on homomorphic encryption

ABSTRACT Most of the existing digital fingerprint algorithms for vector maps are symmetric fingerprint algorithms, and merchants may frame a legitimate buyer. An asymmetric fingerprinting protocol utilizing homomorphic encryption is proposed. First, the buyer encrypts his fingerprint. Then, this encrypted fingerprint and the merchant’s fingerprint are embedded into an encrypted vector map by the merchant. Finally, the encrypted data with the fingerprints of both parties is distributed to buyers. The buyer can use his private key to decrypt the encrypted data and get the Non-encrypted data with the fingerprints. In this way, merchants can track illegal users without the buyer’s fingerprint. Experimental results show that after various attacks, fingerprints can still be detected correctly.

Transmission Line Power Theft

Abstract: Generation, transmission and distribution of electrical energy involve many operational losses. We can defined the losses in generation technically but distribution and transmission losses cannot be precisely quantified with the sending end information. This illustrates the involvement of nontechnical parameter in transmission and distribution of electricity. Moreover technical losses occur naturally and are caused because of power dissipation in transmission lines, transformers, and other power system components. Technical losses in Transmission & Distribution are computed with the information about total load and the total energy bill. While technology in the raising slopes, we should also note the increasing immoral activities. The system prevents the illegal usage of electricity. At this point of technological development the problem of illegal usage of electricity can be solved without any human control using IoT. With the implementation of this system will save large amount of electricity, and there by electricity will be available for more number of consumer then earlier, in highly populated country such as India, China. Power theft can be defined as the usage of the electrical power without any legal contract with the supplier. To see it, a proposed system (current measurement and comparison) is proposed in which the distribution of family power is done indirectly from the distribution box to each house. Power theft is a persistent issue in many countries, leading to significant financial losses for utility companies and affecting the reliability of power supply. In this study, we propose a novel approach for detecting power theft in transmission lines using NodeMCU ESP8266, a low-cost Wi-Fi-enabled microcontroller, and Blynk IoT platform for remote monitoring and control.The proposed system involves installing current sensors at various locations along the transmission lines to measure the current flow. The NodeMCU ESP8266 is used as a data acquisition unit that collects the current data from the sensors and sends it to the Blynk IoT platform via Wi-Fi for real-time monitoring. The Blynk platform provides a user-friendly interface for visualizing the data and setting up alarms and notifications for abnormal current patterns, which could indicate power theft. The system can also track power consumption trends, identify abnormal usage patterns, and provide insights for optimizing power distribution. The proposed system has several advantages, including low-cost implementation, real-time monitoring, remote access, and easy customization through the Blynk platform. It has the potential to significantly reduce power theft, improve revenue collection for utility companies, and enhance the overall reliability of power supply in transmission lines. Further research and development can be done to optimize the system's performance and expand its applications in different power distribution scenarios.

Smart Energy Meter by Using IOT

Abstract: It is an IOT based paper electricity is one of the fundamental necessities of human beings which is commonly Used for Domestic, Agriculture, Industrial purpose. Power theft and Meter billings are biggest problems in recent days which causes a lot of loss to electricity board. If we can prevent these thefts we can save a lot of power. This is done by Smart Energy Meter by using IOT, present an efficient and cost-effective way to transfer the information of energy consumed by consumer wirelessly as well as it provides facilities to detect illegal usage of electricity. Smart Energy meter by using IOT basically consists of three major components namely controller, Wi- Fi, theft detection device. Whenever there is any fault or theft, the theft detector sensor detects the error. The controller plays a crucial role in keeping all the components in the working state. In this system the energy meter is connected to internet. The proposed system is capable of continuously monitoring and being notified about the number of units consumed to energy provider and consumer. The energy consumption is calculated automatically, and the bill is updated on the internet by using a network of internet of things. This automation can eliminate the manual work in electricity maintenance. In this paper mainly focuses on automatic billing, theft detection, power optimization and providing the relevant energy consumption information to user.

Research on the Gatekeeper Mechanism of Data Platforms under the Perspective of Data

Since the fifth technological revolution, represented by artificial intelligence, emerged, data has become an essential driving force for social operation and an important engine for economic growth. Data analysis activities based on artificial intelligence big data analysis models have significantly improved social productivity, especially in promoting the tertiary industry. Data analysis enables precise user targeting, thereby making services more rational and refined. However, while these platforms apply and analyze data, non-compliant usage, illegal usage, and even criminal activities are prevalent. Consequently, the gatekeeper mechanism has been introduced in China as a safeguard mechanism for data compliance, serving as a baseline system to protect people's fundamental rights. This paper aims to explore the rationality of the "gatekeeper mechanism" and how to ensure the smooth implementation of this measure.

Hepatitis B virus infection among illegal drug users in Enugu State, Nigeria: prevalence, immune status, and related risk factors

IntroductionHepatitis B virus infection poses a global health challenge, particularly in low- and middle-income African countries. Illicit drug use exacerbates the problem, with drug users having a higher HBV infection risk and maintaining a quiet transmission pool. This study aimed to determine HBV infection prevalence, immune status, and risk factors among illegal drug users in Enugu State, Nigeria.Materials and methodsA cross-sectional study was conducted in Enugu State, using privileged access interviewer methods to enroll drug users. Pre-tested structured questionnaires were administered after informed consent was obtained. Blood samples were tested for HBsAg, HBsAb, HBeAg, HBeAb, and HBcAb using immunochromatographic rapid test kits. Statistical analysis was performed using SPSS version 25.ResultsOne hundred drug users were recruited into the study. Overall, 7% of the drug users had HBV infection. 61% were found to be susceptible to HBV infection, 15% showed serological evidence of immunity from HBV vaccination and 1% developed natural immunity from HBV exposure. Significant risk factors for HBV infection were age less than 20 years, young age (≤ 20 years) at drug initiation, being single, injecting drugs more than or equal to 20 times per month and injecting with used syringes.ConclusionThis study shows high intermediate endemicity of HBV infection among drug users, low vaccination uptake, and high susceptibility to HBV infection. This calls for the urgent inclusion of drug users in national HBV vaccination campaigns and the adoption of the World Health Organization’s recommendations on the prevention of viral hepatitis among people who inject drugs.

Fabrication of an electrochemical sensing platform based on MWCNT-CONH-66-UiO and PEDOT:PSS for highly sensitive and rapid detection of sunset yellow

The out-of-range, overdose and illegal usage of sunset yellow azo dye in food will cause great damage to food safety and consumer health. In this work, a novel electrochemical sensing platform toward sunset yellow detection was prepared based on the amidated MWCNT-CONH-66-UiO and poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS). In MWCNT-CONH-66-UiO, the –NHCO- is produced by the amidation reaction between zirconium 2-amino terephthalate (UiO-66-NH2) and carbonylated multi-walled carbon nanotubes (MWCNT-COOH), which play significant role for the enhancement of the sensing properties of MWCNT-CONH-66-UiO/PEDOT:PSS composite. PEDOT:PSS acts as a conducting film coated on MWCNT-CONH-66-UiO and alleviates the electrooxidation of –NHCO-. The large specific surface area, good conductivity, and outstanding synergistic effect of the composite trigger off prominent sensing properties of MWCNT-CONH-66-UiO/PEDOT:PSS toward sunset yellow detection with the lowest detection limit as 3.3 nM and a sensitivity as 6.6 mA mM−1 cm−2 (active area of 0.15 cm2). Additionally, this sensor shows satisfactory results for sunset yellow detection in plain cake and marinating meat via DPV in comparison to the high-performance liquid chromatography method. The research results in this work will provide technical support for the rapid and efficient detection of azo dyes in food, animal feeds, and industrial wastewater.

Developing the Framework Using Deep Neural Network for Detection of Spam and Fake Spam Messages in Twitter

Social media plays vital role among the user communities for social gathering, entertainment, communication, sharing knowledge so on. Twitter is one such network to connect millions of users to share information. Nowadays, there are humpteen numbers of users using social media for social engagements. Due to the fact that wide publicity of individuals and products get viral in social media, everyone wish to use social media as a platform to promote their product. Furthermore, large number of people relies on social media contents to take decisions. Twitter is one of the social media platforms to post the media contents by the user. Spammers are illegal users intrude the twitter account and send the duplicate messages to promote advertisement, phishing, scam and personal blogs etc. In this paper, a novel spam detection mechanism is introduced to detect the suspicious users on twitter. The system has been designed such a way that it initially set with semi-supervised at the tweet level and update into supervised level for learning the input tweets to detect the spammers. The proposed system will also identify the type of spammers and will also remove duplicate tweets. We have applied with multi-classifier algorithms like naïve Bayesian, K-Nearest neighbor and Random forest into twitter data set and the performance is compared. The experimental result shows very promising results.

An attribute-based access control scheme using blockchain technology for IoT data protection

With the wide application of the Internet of Things (IoT), storing large amounts of IoT data and protecting data privacy has become a meaningful issue. In general, the access control mechanism is used to prevent illegal users from accessing private data. However, traditional data access control schemes face some non-ignorable problems, such as only supporting coarse-grained access control, the risk of centralization, and high trust issues. In this paper, an attribute-based data access control scheme using blockchain technology is proposed. To address these problems, attribute-based encryption (ABE) has become a promising solution for encrypted data access control. Firstly, we utilize blockchain technology to construct a decentralized access control scheme, which can grant data access with transparency and traceability. Furthermore, our scheme also guarantees the privacy of policies and attributes on the blockchain network. Secondly, we optimize an ABE scheme, which makes the size of system parameters smaller and improves the efficiency of algorithms. These optimizations enable our proposed scheme supports large attribute universe requirements in IoT environments. Thirdly, to prohibit attribute impersonation and attribute replay attacks, we design a challenge-response mechanism to verify the ownership of attributes. Finally, we evaluate the security and performance of the scheme. And comparisons with other related schemes show the advantages of our proposed scheme. Compared to existing schemes, our scheme has more comprehensive advantages, such as supporting a large universe, full security, expressive policy, and policy hiding.

Development of a lateral flow immunochromatography assay for the detection of fluoroacetamide in blood samples

Fluoroacetamide (FAM) has been employed as a rodenticide for an extended duration, leading to a multitude of incidents involving human ingestion poisoning. Currently, FAMs have been prohibited by nations globally; however, there are still instances of their illegal usage. Conventional instrument methods are characterized by their time-consuming nature and complex operational procedures, rendering them inadequate for meeting urgent diagnostic needs in patients with acute FAM poisoning. Therefore, there is an immediate need to develop a prompt, user-friendly, and precise immunoassay method for the diagnosis of acute poisoning induced by FAM. A lateral flow immunochromatography assay (LFIA) was developed in this study for the visual detection of FAMs in blood samples, representing the first report of such an approach. The method exhibited a cut-off value of 0.5 mg/mL under the optimized conditions, enabling the entire FAM detection process in blood samples to be completed within a mere 8 min without any pretreatment requirements. Notably, the results were easily discernible by visual inspection alone. These results indicate that the developed LFIA holds great promise as a convenient and rapid diagnostic tool for FAM poisoning diagnosis, thereby offering valuable support for subsequent treatment strategies.

Research on the significance of post a sports virtual community under Pseudo-environment—— Take the Douban group Sports Without Circle as an example

The network community formed by the Douban group once occupied an important part in the development process of China’s network community, but with the indefinite ban and suspension of a number of Douban groups and illegal users by the nationwide campaign to purify the online environment, the vigor of Douban users has gradually decreased, and new media such as Weibo, WeChat, and short videos are also emerging. It impacts the living environment of Douban. However, throughout the entire Douban platform, the group Sports Without Circle still maintains a strong activity and is currently the largest virtual community focusing on discussing sports events and athletes. With case studies, this article explores the causes of construction, interactive behaviour, communication characteristics, and operation mechanism of the Douban group Sports Without Circle under "Pseudo-environment", tries to explore the construction significance and positive social effects of the virtual community of sports culture, and puts forward a prospect for the future development of the Douban group in the era of media convergence.

Forensic Medical Procedure for Illegal Drug Users in Turkey

Forensic Medical Procedure for Illegal Drug Users in Turkey

A new lattice-based password authenticated key exchange scheme with anonymity and reusable key.

In this article, we propose a novel bilateral generalization inhomogenous short integer solution (BiGISIS)-based password-authenticated key exchange (PAKE) scheme for post-quantum era security. The hardness assumption of the constructed PAKE is based on newly proposed hard lattice problem, BiGISIS. The main aim of this article is to provide a solution for the post-quantum secure PAKE scheme, which is one of the open problems in the literature. The proposed PAKE is the first BiGISIS-based PAKE that satisfies anonymity and reusable key features. The bilateral-pasteurization (BiP) approach is used to obtain the reusable key, and anonymity is achieved thanks to the additional identity components and hash functions. The reusable key structure reduces the time in the key generation, and anonymity prevents illegal user login attempts. The security analysis is done by following the real-or-random (RoR) model assumptions. As a result of security examinations, perfect forward secrecy (PFS) and integrity are satisfied, and the resistance against eavesdropping, manipulation-based attack (MBA), hash function simulation, impersonation, signal leakage attack (SLA), man-in-the-middle (MitM), known-key security (KKS), and offline password dictionary attack (PDA) is captured. According to the comparison analysis, the proposed PAKE is the first SLA-resistant lattice-based PAKE with reusable key and anonymity properties.

Illuminating the dark corners: a qualitative examination of cryptocurrency’s risk

PurposeThe study provides a comprehensive understanding of the issues and illegal activities related to cryptocurrencies and their negative repercussions. This study aims to identify and classify cryptocurrency downsides using grounded theory and in-depth interviews. The study also analysed investors’ reluctance to invest in cryptocurrency. This pioneering qualitative study illuminates a deep and multifaceted criminal aspect of cryptocurrency.Design/methodology/approachThe study conducted in-depth interviews with respondents who have experience and knowledge of cryptocurrency investments. The interviews were recorded and transcribed. The analysis was performed using the NVivo 14 software in the study.FindingsThe study specified two major types of cryptocurrency’s negative aspects: barriers and illegal usage. Barriers to cryptocurrency investment include technological, security, trust, market-related and regulatory reasons. Terrorist funding, money laundering, fraud and ransom payments are all examples of illegal usage. The results of the word cloud analysis are consistent with the overall findings of the survey, which highlighted illegal usage as a prominent negative element of cryptocurrencies. It is a key reason why cryptocurrency is not included in investing portfolios by investors.Originality/valueThe study’s findings provide useful insights for policymakers to develop better methods for successfully mitigating risks and ensuring responsible and sustainable usage of cryptocurrencies. In addition, the study could serve as a stepping stone for more cryptocurrency-related studies, contributing to the development of a more complete and nuanced comprehension of this emergent technology and its societal effects.