Cybersecurity Awareness and Training Programs for Racial and Sexual Minority Populations: An Examination of Effectiveness and Best Practices

The purpose of this research study was to examine the barriers of cybersecurity awareness and training programs for racial and sexual minority populations. The findings suggest that lack of representation is a significant barrier to the effectiveness of cybersecurity awareness and training programs. Many programs are designed by and for people from dominant racial and gender groups, which makes it difficult for minority populations to relate to the information presented. As a result, it is crucial to incorporate diverse perspectives into the development of materials to improve engagement and effectiveness. The study also found that language and cultural barriers pose challenges to minority populations' participation in cybersecurity awareness and training programs. Minority populations may speak languages other than English, making it challenging to access information and training materials. Additionally, cultural differences may lead to different understandings of cybersecurity risks and how to mitigate them. To overcome these barriers, training programs should provide resources in multiple languages and build cultural competence into the curriculum. Access to resources was also identified as a barrier to participation in cybersecurity awareness and training programs. Minority populations may have limited access to technology and the internet, preventing them from participating in training programs and protecting themselves from cyber threats. This barrier can be addressed by partnering with community organizations to increase access to resources and providing training programs in a variety of formats that can be accessed through different mediums. The study also found that fear of discrimination is a significant barrier to participation in cybersecurity awareness and training programs. Minority populations may be hesitant to participate in these programs due to fear of discrimination or mistreatment based on their race or sexual orientation. Therefore, it is essential to create a safe and inclusive environment in cybersecurity training programs that promotes diversity, equity, and inclusion. The study found that lack of trust is a critical barrier to participation in cybersecurity awareness and training programs. Minority populations may have less trust in institutions and government agencies due to past experiences of discrimination, leading to lower engagement in cybersecurity awareness and training programs. Thus, building trust through transparent and inclusive communication strategies can promote increased participation and engagement in these programs

Factors Influencing Cybersecurity Risk Among Minority-Owned Small Businesses

Small businesses are increasingly becoming targets of cyberattacks. Minority-owned small businesses may face additional challenges when it comes to cybersecurity, due to factors such as limited resources and lack of awareness. Therefore, it is important to understand the specific factors that influence cybersecurity risk among minority-owned small businesses in order to develop effective strategies to protect them from cyber threats. This study aimed to identify the factors influencing cybersecurity risk among minority-owned small businesses. The variables examined were lack of resources, lack of awareness, use of outdated technology, limited training, and targeted attacks. A multiple regression analysis was conducted with a sample size of 252 minority-owned small businesses. The results showed that all of the variables were statistically significant in predicting cybersecurity risk. Lack of resources, lack of awareness, and use of outdated technology were found to be significant predictors of cybersecurity risk. Limited training and targeted attacks were also significant predictors. These findings suggest that minority-owned small businesses are vulnerable to cybersecurity risks due to a combination of factors, including limited resources, lack of awareness, outdated technology, and inadequate training. Therefore, it is important for small business owners to prioritize cybersecurity and invest in the necessary resources and training to protect their businesses from cyber threats

Enhancing E-commerce Security: The Effectiveness of Blockchain Technology in Protecting Against Fraudulent Transactions

This study aims to investigate the effectiveness of blockchain technology in securing e-commerce transactions and protecting against fraud. The study examines the application of blockchain technology in various e-commerce platforms and identifies its potential to enhance transaction security and reduce the risk of fraud. The study found that blockchain technology offers several advantages in securing e-commerce transactions. One of the key findings is that the immutable nature of blockchain records ensures that transaction data cannot be tampered with once it has been recorded. This makes it almost impossible for fraudsters to manipulate e-commerce transactions, ensuring the authenticity and integrity of the data. The study also found that cryptographic security is a crucial aspect of blockchain technology that enhances e-commerce transaction security. The use of digital signatures, hash functions, and encryption algorithms ensure that transactions are secure and private, preventing unauthorized access to transaction data. Decentralized consensus is another key finding of this study. The study found that the validation and confirmation of transactions by a network of nodes rather than a central authority makes it difficult for fraudsters to manipulate or alter transactions since they would need to compromise a large number of nodes to do so. The study further discovered that the automation of e-commerce transactions using smart contracts enhances transaction security and reduces the risk of fraud. Smart contracts automate the execution of e-commerce transactions, ensuring that they are carried out according to pre-defined rules and conditions, eliminating the need for intermediaries and reducing the risk of fraud. The study identified that the traceability of transactions and their associated data using blockchain technology makes it easier to identify and investigate fraudulent activities

Psychological Effects of Cybercrime on Minorities: Short-Term and Long-Term Impacts

Objective: The objective of this study was to examine the psychological effects of cybercrime on individuals who belong to minority groups. Method: This study utilized a literature review approach to analyze previous research on the topic. A range of databases were searched, including PubMed and PsycINFO. Results: The findings of this study indicated that cybercrime can have both short-term and long-term psychological effects on individuals who belong to minority groups. The short-term effects include fear and anxiety, loss of trust, and post-traumatic stress disorder (PTSD). Long-term effects include chronic stress, depression and anxiety, social isolation, and financial impacts. Conclusion: This study highlights the importance of addressing the psychological effects of cybercrime on minorities through supportive services such as counseling, therapy, and community support. Additionally, measures should be taken to prevent cybercrime and provide justice to victims. It is crucial to recognize the impact of cybercrime on minority individuals and provide adequate support to mitigate the psychological effects

Development of Internet Protocol Traceback Scheme for Detection of Denial-of-Service Attack

To mitigate the challenges that Flash Event (FE) poses to IP-Traceback techniques, this paper presents an IP Traceback scheme for detecting the source of a DoS attack based on Shark Smell Optimization Algorithm (SSOA). The developed model uses a discrimination policy with the hop-by-hop search. Random network topologies were generated using the WaxMan model in NS2 for different simulations of DoS attacks. Discrimination policies used by SSOA-DoSTBK for the attack source detection in each case were set up based on the properties of the detected attack packets. SSOA-DoSTBK was compared with a number of IP Traceback schemes for DoS attack source detection in terms of their ability to discriminate FE traffics from attack traffics and the detection of the source of Spoofed IP attack packets. SSOA-DoSTBK IP traceback scheme outperformed ACS-IPTBK that it was benchmarked with by 31.8%, 32.06%, and 28.45% lower FER for DoS only, DoS with FE, and spoofed DoS with FE tests respectively, and 4.76%, 11.6%, and 5.2% higher performance in attack path detection for DoS only, DoS with FE, and Spoofed DoS with FE tests, respectively. However, ACS-IPTBK was faster than SSOA-DoSTBK by 0.4%, 0.78%, and 1.2% for DoS only, DoS with FE, and spoofed DoS with FE tests, respectively. Keywords: DoS Attacks Detection, Denial-of-Service, Internet Protocol, IP Traceback, Flash Event, Optimization Algorithm

Fighting Cybercrime After \u3cem\u3eUnited States v. Jones\u3c/em\u3e

In a landmark non-decision last term, five Justices of the United States Supreme Court would have held that citizens possess a Fourth Amendment right to expect that certain quantities of information about them will remain private, even if they have no such expectations with respect to any of the information or data constituting that whole. This quantitative approach to evaluating and protecting Fourth Amendment rights is certainly novel and raises serious conceptual, doctrinal, and practical challenges. In other works, we have met these challenges by engaging in a careful analysis of this “mosaic theory” and by proposing that courts focus on the technologies that make collecting and aggregating large quantities of information possible. In those efforts, we focused on reasonable expectations held by “the people” that they will not be subjected to broad and indiscriminate surveillance. These expectations are anchored in Founding-era concerns about the capacity for unfettered search powers to promote an authoritarian surveillance state. Although we also readily acknowledged that there are legitimate and competing governmental and law enforcement interests at stake in the deployment and use of surveillance technologies that implicate reasonable interests in quantitative privacy, we did little more. In this Article, we begin to address that omission by focusing on the legitimate governmental and law enforcement interests at stake in preventing, detecting, and prosecuting cyber-harassment and healthcare fraud

Anti- Forensics: The Tampering of Media

In the context of forensic investigations, the traditional understanding of evidence is changing where nowadays most prosecutors, lawyers and judges heavily rely on multimedia signs. This modern shift has allowed the law enforcement to better reconstruct the crime scenes or reveal the truth of any critical event.In this paper we shed the light on the role of video, audio and photos as forensic evidences presenting the possibility of their tampering by various easy-to-use, available anti-forensics softwares. We proved that along with the forensic analysis, digital processing, enhancement and authentication via forgery detection algorithms to testify the integrity of the content and the respective source of each, differentiating between an original and altered evidence is now feasible. These operations assist the court to attain higher degree of intelligibility of the multimedia data handled and assert the information retrieved from each that support the success of the investigation process

Computer Vision for Multimedia Geolocation in Human Trafficking Investigation: A Systematic Literature Review

The task of multimedia geolocation is becoming an increasingly essential component of the digital forensics toolkit to effectively combat human trafficking, child sexual exploitation, and other illegal acts. Typically, metadata-based geolocation information is stripped when multimedia content is shared via instant messaging and social media. The intricacy of geolocating, geotagging, or finding geographical clues in this content is often overly burdensome for investigators. Recent research has shown that contemporary advancements in artificial intelligence, specifically computer vision and deep learning, show significant promise towards expediting the multimedia geolocation task. This systematic literature review thoroughly examines the state-of-the-art leveraging computer vision techniques for multimedia geolocation and assesses their potential to expedite human trafficking investigation. This includes a comprehensive overview of the application of computer vision-based approaches to multimedia geolocation, identifies their applicability in combating human trafficking, and highlights the potential implications of enhanced multimedia geolocation for prosecuting human trafficking. 123 articles inform this systematic literature review. The findings suggest numerous potential paths for future impactful research on the subject

A Framework for Identifying Host-based Artifacts in Dark Web Investigations

The dark web is the hidden part of the internet that is not indexed by search engines and is only accessible with a specific browser like The Onion Router (Tor). Tor was originally developed as a means of secure communications and is still used worldwide for individuals seeking privacy or those wanting to circumvent restrictive regimes. The dark web has become synonymous with nefarious and illicit content which manifests itself in underground marketplaces containing illegal goods such as drugs, stolen credit cards, stolen user credentials, child pornography, and more (Kohen, 2017). Dark web marketplaces contribute both to illegal drug usage and child pornography. Given the fundamental goal of privacy and anonymity, there are limited techniques for finding forensic artifacts and evidence files when investigating misuse and criminal activity in the dark web. Previous studies of digital forensics frameworks reveal a common theme of collection, examination, analysis, and reporting. The existence and frequency of proposed frameworks demonstrate the acceptance and utility of these frameworks in the field of digital forensics. Previous studies of dark web forensics have focused on network forensics rather than hostbased forensics. macOS is the second most popular operating system after Windows (Net Marketshare, n.d.); however, previous research has focused on the Windows operating system with little attention given to macOS forensics. This research uses design science methodology to develop a framework for identifying host-based artifacts during a digital forensic investigation involving suspected dark web use. Both the Windows operating system and macOS are included with the expected result being a reusable, comprehensive framework that is easy to follow and assists investigators in finding artifacts that are designed to be hidden or otherwise hard to find. The contribution of this framework will assist investigators in identifying evidence in cases where the user is suspected of accessing the dark web for criminal intent when little or no other evidence of a crime is present. The artifact produced for this research, The Dark Web Artifact Framework, was evaluated using three different methods to ensure that it met the stated goals of being easy to follow, considering both Windows and macOS operating systems, considering multiple ways of accessing the dark web, and being adaptable to future platforms. The methods of evaluation v included experimental evaluation conducted using a simulation of the framework, comparison of a previously worked dark web case using the created framework, and the expert opinion of members of the South Dakota Internet Crimes Against Children taskforce (ICAC) and the Division of Criminal Investigation (DCI). A digital component can be found in nearly every crime committed today. The Dark Web Artifact Framework is a reusable, paperless, comprehensive framework that provides investigators with a map to follow to locate the necessary artifacts to determine if the system being investigated has been used to access the dark web for the purpose of committing a crime. In the creation of this framework, a process itself was created that will contribute to future works. The yes/no, if/then structure of the framework is adaptable to fit with workflows in any area that would benefit from a recurring process