False Security Research Articles

‘THE CALL IS COMING FROM INSIDE THE HOUSE’: SURVEYING THE FEAR FACTOR OF STRANGER DANGER THROUGH THE LENS OF NABOKOV’S LOLITA (1955)

‘The Call is Coming from inside the House’ trope, emblematic of betrayal, has permeated both visual and written narratives, evoking dread and questioning characters’ innocence. This paper critically explores the fear instilled by the stranger danger narrative, juxtaposing it with Vladimir Nabokov’s Lolita (1955) to underline the insidious nature of domestic abuse. While once a potent social warning, the overuse of the trope has desensitised audiences to domestic violence, rendering it banal. The narrative unpacks how social conditioning perpetuates fear, particularly among women and girls, confining them indoors with potential abusers. Drawing parallels between the narrative of Lolita and real-life instances of grooming and abuse, the paper elucidates how abusers manipulate victims into complicity. By examining Lolita as a lens through which to understand social dynamics, the paper prompts a revaluation of cultural tropes and their implications for gender relations and individual autonomy. Through Humbert Humbert’s manipulation of Lolita’s memories and perceptions, the paper highlights the pervasive control exerted by abusers. The paper advocates for a multilayered understanding of fear and safety, challenging the narratives that perpetuate gender-based violence. It critiques social responses to stranger danger, arguing that they perpetuate victim-blaming culture and fail to address root causes. By unpacking the parallels between the patriarchal culture and grooming tactics, the paper finally exposes the false security offered by domesticity, as in Lolita.

Likelihood of Success, the Science of War, and the False Security of a Technical Principle

I argue that it may be time to abandon the likelihood of success principle, a relative newcomer to the just war tradition. First, I am unconvinced of the normative value of the concept, especially when applied to states participating in defensive wars. Second, and more pragmatically, our lack of knowledge about what determines the outcomes and durations of wars, the application of a scientific-sounding concept to what is essentially a judgment of art may distort our moral reasoning. Estimating the chance that a particular war (or use of force) will generate the outcomes one hopes for is fiendishly difficult, and to be accurate, requires a knowledge of military and political science that few theorists possess. In its current form, the likelihood of success principle serves to reify existing power disparities and to render defensive wars apparently illegitimate.

False security expectations from banking innovations due to their dual role in increasing and decreasing the risk factors: the essence of the problem and its overcoming through the formation of situational diagnostics dichotomies

False security expectations from banking innovations due to their dual role in increasing and decreasing the risk factors: the essence of the problem and its overcoming through the formation of situational diagnostics dichotomies

Using a single neuropsychological task as a red flag creates false security.

Using a single neuropsychological task as a red flag creates false security.

Artificial intelligence enabled cyber security defense for smart cities: A novel attack detection framework based on the MDATA model

Smart cities have attracted a lot of attention from interdisciplinary research, and plenty of artificial intelligence based solutions have been proposed. However, cyber security has always been a serious problem, and it is becoming more and more severe in smart cities. The existing attack defense methods are not suitable for detecting multi-step attacks since the detection rules are limited and the efficiency is limited by a large number of false security alarms. Hence, an advanced solution is urgently needed to improve cyber security defense capability. In this paper, we propose a novel attack detection framework called ACAM. To better represent the cyber security knowledge, the framework is based on the MDATA model, which can represent dynamic and temporal–spatial knowledge better than the knowledge graph. The framework consists of the knowledge extraction module, the subgraph generation module, the alarm correlation module, and the attack detection module. These modules can remove false alarms and improve the detection capabilities of multi-step attacks. We implement the framework and conduct experiments on the cyber range platform, the experimental results validate the good performance of attack detection accuracy and efficiency. The framework can greatly improve the cyber security defense capabilities for smart cities.

Cybersecurity Misinformation Detection on Social Media: Case Studies on Phishing Reports and Zoom’s Threat

Prior work has extensively studied misinformation related to news, politics, and health, however, misinformation can also be about technological topics. While less controversial, such misinformation can severely impact companies’ reputations and revenues, and users’ online experiences. Recently, social media has also been increasingly used as a novel source of knowledgebase for extracting timely and relevant security threats, which are fed to the threat intelligence systems for better performance. However, with possible campaigns spreading false security threats, these systems can become vulnerable to poisoning attacks. In this work, we proposed novel approaches for detecting misinformation about cybersecurity and privacy threats on social media, focusing on two topics with different types of misinformation: phishing websites and Zoom’s security & privacy threats. We developed a framework for detecting inaccurate phishing claims on Twitter. Using this framework, we could label about 9% of URLs and 22% of phishing reports as misinformation. We also proposed another framework for detecting misinformation related to Zoom’s security and privacy threats on multiple platforms. Our classifiers showed great performance with more than 98% accuracy. Employing these classifiers on the posts from Facebook, Instagram, Reddit, and Twitter, we found respectively that about 18%, 3%, 4%, and 3% of posts were misinformation. In addition, we studied the characteristics of misinformation posts, their authors, and their timelines, which helped us identify campaigns.

Energy aware Clustered blockchain data for IoT: An end-to-end lightweight secure & Enroute filtering approach

Internet of things (IoT) include smart homes, smart buildings and smart factories, in which all the devices are connected over the internet through wireless network for data transmission or sharing. IoT faces many security challenges due to sharing the data in an open source. Security and energy are the most focusing challenges in IoT due to its resource constrained nature. IoT devices have low energy that is wasted by the attackers, and the data also gets hacked by the attacker, which leads to poor security. This paper proposed CLIENT (Clustered blockchain IoT with En-route) to provide energy efficient and secure communication. For that, this research proposed five processes. Such as Chaotic map based Elgamal authentication, credit score based clustering, capuchin search optimization based packets routing, signature based Enroute filtering and deep leaning based anomaly packet detection. First process is Chaotic Map based Elgamal Authentication, in which chaotic map is used in Elgamal key generation. Second process is Credit score based clustering which minimizes the complexity and overhead during packet transmission. Third process is Capuchin search optimization based packets routing which is used to select optimal route from cluster member to cluster head (CH). Fourth process is signature based Enroute filtering which used to detect and drop false report from the network. Edwards signature based digital signature algorithm (EdDSA) is used for verification purpose. And final process is deep learning based anomaly packets detection, this process used Katz centrality based feed forward small world neural network (FFSWNN) for packet classification (normal or malicious). All the transactions are stored in blockchain to enhance security. The proposed system implemented by using NS3. The result shows that proposed system achieves superior performance compared to existing works in terms of energy consumption, packet loss rate, end to end delay, routing overhead and network life time, precision, recall, accuracy, false alarm rate, encryption time, decryption time and security strength.

Deprescribing the Kt/V Target for Peritoneal Dialysis in the United States: The Path Toward Adopting International Standards for Dialysis Adequacy.

Deprescribing the Kt/V Target for Peritoneal Dialysis in the United States: The Path Toward Adopting International Standards for Dialysis Adequacy.

Potential challenges in AI application in the clinical setting

AbstractArtificial intelligence (AI) solutions have attracted much interests in ophthalmology. Whereas multiple papers have been published the translation to clinical ophthalmology is challenging. The present talk will summarize five key elements that hamper translation. 1. Applicability of AI solutions to external real world datasets. Convolutional neural networks (CNNs) may fail if they were trained on datasets that do not match the target population in terms of ethnicity, age, disease severity and/or diagnostic criteria. 2. Burden of false negatives and false positives. Although the Area under the Curve (AUC) for detection of disease is often high, the application of the CNN still results in many false positives due to the low prevalence. In addition, false security is feigned in false negatives. 3. Inadequate facilities. Whereas CNNs have often been proposed for screening, the screening facilities are frequently not in place. Establishing a screening facility is expensive and requires support from health care providers. 4. Inadequate image quality. Even the best CNN does not perform well if image quality is insufficient. Continuous training and quality control is an expensive task for achieving optimal results. 5. Human interaction studies. Little is known to which degree AI based solutions will be accepted by health care providers and by patients.

Adapting Belief Propagation to Counter Shuffling of NTTs

The Number Theoretic Transform (NTT) is a major building block in recently introduced lattice based post-quantum (PQ) cryptography. The NTT was target of a number of recently proposed Belief Propagation (BP)-based Side Channel Attacks (SCAs). Ravi et al. have recently proposed a number of countermeasures mitigating these attacks.In 2021, Hamburg et al. presented a chosen-ciphertext enabled SCA improving noise-resistance, which we use as a starting point to state our findings. We introduce a pre-processing step as well as a new factor node which we call shuffle node. Shuffle nodes allow for a modified version of BP when included into a factor graph. The node iteratively learns the shuffling permutation of fine shuffling within a BP run.We further expand our attacker model and describe several matching algorithms to find inter-layer connections based on shuffled measurements. Our matching algorithm allows for either mixing prior distributions according to a doubly stochastic mix matrix or to extract permutations and perform an exact un-matching of layers. We additionally discuss the usage of sub-graph inference to reduce uncertainty and improve un-shuffling of butterflies.Based on our results, we conclude that the proposed countermeasures of Ravi et al. are powerful and counter Hamburg et al., yet could lead to a false security perception – a powerful adversary could still launch successful attacks. We discuss on the capabilities needed to defeat shuffling in the setting of Hamburg et al. using our expanded attacker model.Our methods are not limited to the presented case but provide a toolkit to analyze and evaluate shuffling countermeasures in BP-based attack scenarios.

Using Digital Tools for Contact Tracing to Improve COVID-19 Safety in Schools: Qualitative Study Exploring Views and Experiences Among School Staff.

Throughout the pandemic, governments worldwide have issued guidelines to manage the spread and impact of COVID-19 in schools, including measures around social distancing and contact tracing. Whether schools required support to implement these guidelines has not yet been explored in depth. Despite the development of a range of technologies to tackle COVID-19, such as contact-tracing apps and electronic vaccine certificates, research on their usefulness in school settings has been limited. The aim of the study was to explore the needs of school staff in managing COVID-19 and their experiences and perspectives on technological support in relation to contact tracing. School staff are the ones likely to make key implementation decisions regarding new technologies, and they are also the ones responsible for using the new tools daily. Including both management staff and class teachers in the development of school-based technologies can lead to their successful adoption by schools. Semistructured interviews were conducted with UK school staff, including primary and secondary school teachers and school managers. Thematic analysis, facilitated by NVivo, was used to analyze the data. Two of the authors independently coded 5 (28%) of the interviews and reached a consensus on a coding framework. Via purposive sampling, we recruited 18 participants from 5 schools. Findings showed that primary schools did not perform contact tracing, while in secondary schools, digital seating plans were used to identify close contacts in the classroom and manual investigations were also conducted identify social contacts. Participants reported that despite their efforts, high-risk interactions between students were not adequately monitored. There was a need to improve accuracy when identifying close contacts in common areas where students congregate. Proximity tracking, use of access cards, and closed-circuit television (CCTV) emerged as potential solutions, but there were concerns surrounding false alerts, burden, and security. School staff have found it difficult to monitor and implement social distancing and contact-tracing provisions. There are opportunities for mobile digital technologies and CCTV to support school staff in keeping their students and colleagues safe; however, these must place minimal demands on staff and prioritize security measures. Study findings can help researchers and practitioners who work in different contexts and settings understand what particular challenges are faced by school staff, and inform further research on the design and application of digital solutions for contact tracing.

Offering false security: How the draft artificial intelligence act undermines fundamental workers rights

In April 2021, the European Commission published its first draft of the Proposal for a Regulation on Artificial Intelligence. Since AI in the work context has increasingly become important in organising work and managing workers, the AI Act will undoubtedly have an impact on EU and national labour law systems. One aim of the proposal is to guarantee ‘consistency with existing Union legislation applicable to sectors where high-risk Artificial Intelligence systems are already used or likely to be used in the near future’, which includes the EU social acquis. It could be argued that ensuring true consistency with EU law means guaranteeing that the way the AI Act will be implemented and applied will still allow the other pieces of EU labour law to fulfil their purpose. It is undeniable that the implementation of the AI Act will overlap with various fields of EU law, especially considering the increasing use of AI technology at work. Thus, this article seeks to identify ways to refine the AI Act, insofar as it impacts work. The contribution discusses the current AI Act as proposed in April 2021, thereby focusing on two particular areas, EU non-discrimination law and EU law on occupational health and safety (OSH), as these two areas are, more or less explicitly, addressed as legal fields in the AI Act. The article starts with taking the perspective of EU labour law influencing the development of AI systems used in the employment context. We argue that providers should respect EU labour law throughout the development of the AI system (section 2). Then, the areas where EU labour law and the AI overlap are identified, thereby viewing it from an employer's perspective, i.e., the user of the AI system (section 3). Using two specific EU labour law areas (the right not to be discriminated against and the right to healthy and safe working conditions) the article provides a first assessment of how the AI Act might influence work and the regulation thereof (section 4). Finally, the conclusion critically explores whether and to what extent AI in employment situations warrants particular attention (section 5).

High Incidence, Reinfections, and Active Syphilis in Populations Attending a Specialized HIV Clinic in Mexico, a Dynamic Cohort Study

Syphilis, a sexually transmitted infection, has reemerged in many vulnerable groups around the world. The objective of the current study was to determine the prevalence and incidence of syphilis among people who attended a specialized HIV clinic in Mexico from 2011 to 2015. Databases from the laboratory were analyzed, and the following four groups were formed: people seeking HIV-1 voluntary counseling and testing (VCT), people in prison (PPr), people living with HIV (PLWH), and patients from primary care clinics (others). The diagnosis of syphilis was made using the reverse algorithm; antibody titers were examined to determine the stage of infection. Baseline data were analyzed and, with follow-up information, a retrospective dynamic cohort was formed. Factors associated with the seroprevalence of syphilis and active syphilis were evaluated by the chi-square test. Moreover, risk factors for the incidence of syphilis were described. A total of 81,863 baseline individuals were analyzed. The seroprevalence of syphilis was 9.9% in the VCT group, 8.2% in the PPr group, 37.0% in the PLWH group, and 8.7% in the others group; the prevalence of active syphilis was 1.7–13.1%. A total of 11,124 people were followed up. The incidence (cases per 100 person-years) was 3.5 among the VCT group, 16.0 among the PLWH group, and < 0.1 among both the PPr and others groups, respectively; moreover, the frequency of reinfections was 11.1–24.4%. The high prevalence and incidence of syphilis, active syphilis, and reinfections among men, transgender people, individuals aged 20–39 years, and people with a history of HIV or hepatitis B suggest that it is critical to improve prevention, diagnosis, and treatment measures to stop the reemergence of syphilis. There are also new factors such as methamphetamine use, group sex, or contacting partners over the internet that are associated with syphilis. In addition, HIV preexposure prophylaxis could contribute to the increased incidence of syphilis by providing false security in the prevention of STIs, thereby increasing risky sexual behaviors.

White Whale, Black Swan

White Whale, Black Swan

Autonomous detection of malevolent nodes using secure heterogeneous cluster protocol

Surfing of internet by the users has been more vital from the inception of the network. However, the number of users using the internet is increasing gradually. As a result, it has also become a serious threat to users who are using the internet because due to the false information and security threat by malicious users. In this context, it is vital to provide the trusted information to the users. In order to achieve the same, the Heterogeneous Cluster-Based Secure Protocol (HCBSP) can be used to detect the malicious nodes and thereby, to provide a secure path for data transmission. Initially, the nodes are deployed, then clusters are formed and subsequently, the data are transmitted between cluster and base. The HCBSP operates over the cluster for effective attack detection and secures the data transmission in wireless network. This performance is evaluated and compared with the existing methods. Here, the result shows that the HCBSP is the most effective platform in detecting the malicious nodes with high accuracy rate.

Transcendence, chance and happiness

Transcendence, chance and happiness

The Reconfiguration of Urban Public–Private Spaces in the Mall: False Security, Antidemocratization, and Apoliticalization

In cities across the world, public spaces are being reconfigured, and their functions are being appropriated by private areas, such as shopping malls. The aim of the present article was to analyze this problem and, more specifically, to study shopping centers as secure spaces in cities, as well as the antidemocratic and apolitical nature of such malls. The study takes a positivist approach, beginning with the existing theoretical framework and using data from case studies to generate findings. The theoretical framework is established through a review of the literature, while the case study data are drawn from an analysis of news content from digital media and from autoethnography. The findings suggest malls are perceived as safe spaces, also in addition to being home to minor offenses, as well as a number of tragic events and crimes. Additionally, a growing number of demonstrations and political acts are being staged inside malls, which are seen as symbols of consumption and the neoliberal capitalist system. The owners and managers of shopping centers condone and permit the least conflictive acts and ban and repress the remainder, on occasions with the support of state security forces. The relocation of civic life to malls reduces the use of public spaces and erodes the value of the public sphere. The article ends by proposing public actions to reverse this process.

The Panama Canal and its False Security and Defence

The Panama Canal and its False Security and Defence

Rehabilitation of A Patient with Iatrogenesis After Facial Trauma - Case Report

The objective of this study is to report a clinical case of a female patient, melanoderma, 18 years old, referred to the FOA-UNESP surgery and traumatology team in 2013, reporting being a victim of a high-level fall in the attempted suicide. Clinical examination revealed loss of teeth 33, 32, 31, 41, 42, 43 and 44 and CT scan of the face revealed NOE, Lefort I and II and Lanelong fractures. The patient underwent a surgical procedure to reduce and fix fractures. The case was followed up after hospital discharge. A mandible CT was requested to install dental implants. Surgical planning was performed to install implants and make a surgical guide. 4 implants were installed in the region of teeth 32, 31, 41, 42, 43. Two years after the implant was installed, the patient returned to the institution reporting pain in tooth 45. The patient was referred by the screening sector to the endodontic team, which requested a new CT examination of the mandible, noting that the implants installed in the regions of teeth 33 and 44 had reached teeth 34 and 45, indicating the extraction of these teeth and removal of 2 implants. Surgical planning was performed and the extraction and removal surgery of the implants performed. After waiting for the healing period, the patient was referred to the dental prosthesis team and it was defined that reverse planning would be carried out to install the new implants and oral rehabilitation using a supported implant prosthesis. Thus, the impressions left by the case allow us to conclude that the use of a surgical guide, without prosthetic planning, provides the inexperienced surgeon with false security for the procedure, with reverse planning and professional experience essential for implant dentistry.

The Draft Artificial Intelligence Act (AI Act): Offering False Security to Undermine Fundamental Workers’ Rights

The Draft Artificial Intelligence Act (AI Act): Offering False Security to Undermine Fundamental Workers’ Rights