Future Attacks Research Articles

Indoor air quality improvement in COVID-19 pandemic: Review

IntroductionThe advent of COVID-19 has impinged millions of people. The increased concern of the virus spread in confined spaces due to meteorological factors has sequentially fostered the need to improve indoor air quality. ObjectiveThis paper aims to review control measures and preventive sustainable solutions for the future that can deliberately help in bringing down the impact of declined air quality and prevent future biological attacks from affecting the occupant’s health. MethodologyAnontology chart is constructed based on the set objectives and review of all the possible measures to improve the indoor air quality taking into account the affecting parameters has been done. ObservationsAn integrated approach considering non-pharmaceutical and engineering control measures together for a healthy indoor environment should be contemplated rather than discretizing the available solutions. Maintaining social distance by reducing occupant density and implementing a modified ventilation system with advance filters for decontamination of viral load can help in sustaining healthy indoor air quality. ConclusionThe review paper in the main, provides a brief overview of all the improvement techniques bearing in mind thermal comfort and safety of occupants and looks for a common ground for all the technologies based on literature survey and offers recommendation for a sustainable future.

Detect and Classify the Unpredictable Cyber-Attacks by using DNN Model

Machine learning techniques are often used to develop IDS by detecting and deploying fast and automated network attacks to torpedoes and host standards. However, there are many problems, as severe attacks change all the time and occur at very high levels that require a lot of resolution. There are many malicious packages available for further investigation by the cybersecurity community. However, one completed study did not provide a complete analysis to apply different machine learning algorithms on different media packages. Because of the persistent methods of attack and the dynamic nature of malware, it is important to systematically update and approve malicious packages that are available to the public. This paper explores the DNN, a type of comprehensive learning model, promoting flexible and appropriate IDS for detecting and deploying expected and unpredictable online attacks. Sustainable industrial development and rapid development of attacks need evaluation for some data developed over the years using static and dynamic methods. This type of research can help determine the best algorithm to identify future attacks. Comparative data for some commonly available malware provides a comprehensive comparison of DNN experiences with other class machine learning classifications. The best network parameters and network topologies for DNN are selected using the KDDCup 99 package with this hyperparameter selection method. The DNN model, which works well on KDDCup 99, works on other data, such as the NSL-KDD memory test. Our DNN model teaches how to transfer IDS information functions from multicultural.Multidisciplinary representations in a variety of encryption. Complex tests have shown that DNN performs better than conventional machine learning classification. Finally, we present a large and hybrid DNN torrent structure called Scale-Hybrid-IDS-AlertNet, which can be used to effectively monitor the impact of network traffic and host-level events to warn directly about cyber-attacks.

Patient Perspectives on the Benefits and Risks of Percutaneous Coronary Interventions: A Qualitative Study.

BackgroundGrowing evidence for coronary stents in patients with stable coronary artery disease (CAD) suggests that the benefits of stents are uncertain. The goal of this study was to assess patients’ informational needs and how patients react to information about the uncertain benefit of stents to CAD patients.MethodsSemi-structured qualitative interviews (N=20) were conducted with patients with stable CAD who received a recent stent. Data were coded and analyzed using a mixed inductive-deductive approach.ResultsSome patients mistakenly believed that the purpose of their stent was to prevent a future heart attack, and few were previously aware of the uncertain benefit. Nearly all patients perceived positive outcomes from their procedure, even if their symptoms persisted. Some patients had difficulty accepting evidence that stents may not reduce the risk of heart attack or reliably improve symptoms. Nonetheless, patients still expressed a desire to receive new information about the uncertain benefits of stents and wanted to have received this information early in their care.ConclusionMany patients with stable CAD do not understand the intended benefit of coronary stents and want to be informed of the evidence of uncertain benefit of coronary stents, even if this would not change their decision. Improved communication and patient education tools are needed to better inform patients. An intervention providing patients with this information early has the potential to solve these problems.

The use of family networks in suicide terrorism: a case study of the 2018 Surabaya attacks

ABSTRACT This article investigates the use of family networks in suicide terrorism using the 2018 Surabaya suicide attacks as a case study. The Surabaya attacks were the first case in the region that involved entire family networks including parents and their young children. The main aim of the article is to provide an understanding of the use of family networks in suicide terrorism particularly that of women and children and explore the implications that it has for the region. It is argued that there are numerous advantages of using women and children in suicide terrorism which will continue to be exploited by terrorist groups. A simplified model of motivating factors for suicide attackers is proposed and it is found that the three main motivating factors are ideology, socio-cultural factors and personal crises. The Surabaya case shows that individuals may be motivated to carry out suicide attacks primarily by a misconstrued religious ideology rather than motivations that are nationalistic in nature. The Surabaya case is not an isolated case and the use of family networks is likely to be a growing trend in future suicide attacks.

Post-quantum MACsec in Ethernet Networks

The demand on MACsec in Ethernet is increasing substantially since MACsec fits well for industrial applications which require strong security as well as efficiency. To provide a long-term security, the MACsec protocol should be resistant to future attacks including quantum attacks. In this paper, MACsec is analysed under a quantum attack scenario. To achieve 128-bit quantum security, AES (Advanced Encryption Standard) algorithms defined in MACsec should mandate to use 256-bit keys. On the other hand, classical public-key cryptosystems in MKA are not secure at all against quantum attacks so that they need to be replaced by post-quantum crypto schemes in a quantum world. We propose an authenticated post-quantum key establishment protocol which is suitable for long-term secure MACsec. The proposed protocol is used in the hybrid mode, an ephemeral key exchange, and an end-to-end encryption. We verified by experiments that the proposed protocol can be deployed in existing a MACsec-enabled Ethernet network.

Biostimulant Properties of Seaweed Extracts in Plants: Implications towards Sustainable Crop Production.

The use of seaweed-based bioproducts has been gaining momentum in crop production systems owing to their unique bioactive components and effects. They have phytostimulatory properties that result in increased plant growth and yield parameters in several important crop plants. They have phytoelicitor activity as their components evoke defense responses in plants that contribute to resistance to several pests, diseases, and abiotic stresses including drought, salinity, and cold. This is often linked to the upregulation of important defense-related genes and pathways in the plant system, priming the plant defenses against future attacks. They also evoke phytohormonal responses due to their specific components and interaction with plant growth regulation. Treatment by seaweed extracts and products also causes significant changes in the microbiome components of soil and plant in support of sustainable plant growth. Seaweed extracts contain a plethora of substances which are mostly organic, but trace levels of inorganic nutrient elements are also present. Fractionation of seaweed extracts into their components and their respective bioassays, however, has not yielded favorable growth effects. Only the whole seaweed extracts have been consistently proven to be very effective, which highlights the role of multiple components and their complex interactive effects on plant growth processes. Since seaweed extracts are highly organic, they are ideally suited for organic farming and environmentally sensitive crop production. They are also very compatible with other crop inputs, paving the way for an integrated management approach geared towards sustainability. The current review discusses the growth and functional effects evoked by seaweed extracts and their modes and mechanisms of action in crop plants which are responsible for elicitor and phytostimulatory activities. The review further analyses the potential value of seaweed extracts in integrated crop management systems towards sustainable crop production.

Anticipated Attack Slows Responses in a Cued Virtual Attack Emotional Sternberg Task.

Threatening stimuli have varying effects, including reaction time (RT) increase in working memory tasks. This could reflect disruption of working memory or, alternatively, a reversible state of freezing. In the current series of experiments, reversible slowing due to anticipated threat was studied using the cued Virtual Attack Emotional Sternberg Task (cVAEST). In this task visually neutral cues indicate whether a future virtual attack could or could not occur during the maintenance period of a Sternberg task. Three studies (N = 47, 40, and 40, respectively) were performed by healthy adult participants online. The primary hypothesis was that the cVAEST would evoke anticipatory slowing. Further, the studies aimed to explore details of this novel task, in particular the interval between the cue and probe stimuli and the memory set size. In all studies it was found that threat anticipation slowed RTs on the working memory task. Further, Study 1 (memory set size 3) showed a decrease in RT when the attack occurred over all Cue Stimulus Intervals (CSIs). In Study 2 a minimal memory set of one item was used, under which circumstances RTs following attacks were only faster shortly after cue presentation (CSI 200 and 500 ms), when RTs were high for both threat and safe cues. Study 3 replicated results of Study 2 with more fine-grained time intervals. The results confirm that anticipation of attack stimuli can reversibly slow responses on an independent working memory task. The cVAEST may provide a useful method to study such threat-induced response slowing.

Terrorism in China and the Emerging Needs for Counter- Terrorism Medicine Following a Decade of Deaths and Injuries.

China is ranked 42nd on the Global Terrorism Index (2019), a scoring system of terrorist activities. While China has a relatively low terrorism risk, events globally have wide-ranging repercussions for future attacks, putting first responders and emergency health workers at risk. This study aims to provide the epidemiological context for the past decade detailing the unique injury types responders are likely to encounter and to develop training programs utilizing these data. The Global Terrorism Database (GTD) was searched for all attacks in China between the years 2008-2018. Attacks met inclusion criteria if they fulfilled the terrorism-related criteria as set by the GTD's Codebook. Ambiguous events, as defined by the GTD's Codebook, were excluded. English language grey literature was searched to ensure no events meeting these criteria were missed. A focused search of online English language newspaper articles was also performed for any terrorist events between 2008-2018. One-hundred and eight terrorist events occurred in the study time period. Of the 108 incidents, forty-seven (43.5%) involved Explosives/Bombs/Dynamite (E/B/D) only, with an average fatality count of 2.9 and injury count of 7.5 per event. Twenty-seven (25.0%) used bladed or blunt weapons in melees with an average fatality count of 9.7 and an injury count of 8.8 per event. Five (4.6%) involved incendiary weapons with an average fatality count of 2.4 and an injury count of 7.2 per event. Two used only chemical weapons (1.8%) with no recorded deaths and an injury count of 27.0 per event. Two events had unknown weapon types (1.8%) with one recorded death and no injury count. One event used a firearm (0.9%) and led to one death and no injuries. One event used a vehicle (0.9%), which also led to one death and no recorded injuries. Twenty-three attacks used a mix of weapons (21.2%) with an average fatality count of 17.1 and an injury count of 12.0 per event. One-hundred and eight terrorist attacks were recorded between 2008-2018 on Chinese soil using well-understood modalities. This resulted in a total of 809 recorded fatalities with 956 non-fatal injuries. The most commonly chosen methodology was E/B/D, followed by melees and the use of bladed weapons. Three events individually recorded a combined casualty toll of over 100 people.

How do inoculation messages work? A two-study mixed-method investigation into inoculation mechanisms

ABSTRACT The central principle of inoculation theory is that when individuals are presented with a weakened form of a persuasive attack against an existing attitude, they become inoculated against future attacks to that attitude. To address a gap in the literature regarding inoculation mechanisms, we used focus groups (Study 1) to allow participants to describe resistance processes following inoculation. Guided by processing pathways that mirror those in established persuasion frameworks, participants described some of the variables that influence, occur during, and result from, their processing of inoculation material. We applied these findings by presenting a separate group of participants (Study 2) with a healthy nutrition inoculation message and studying their processing responses on the basis of variables identified in Study 1 and through related research. Analyses revealed that participants varied in their elaborative processing of the message and that elaboration was positively associated with desirable resistance processes (e.g. post-inoculation planning, talk, and information searching). By advancing our understanding of the ways through which inoculation messages prepare individuals for attitudinal attacks, these findings provide important future research directions and may inform effective inoculation message design.

The Illusory Standard of Imminence in the International Law of Self-Defense: The Killing of Qassim Soleimani

The crisis year 2020 began with the dramatic Reaper drone attack by the U.S. on the cars carrying Iranian General Qassim Soleimani. As the hash tag “World War III” trended on Twitter, scholars, government officials, and lawmakers took up the question of whether the attack was lawful. Most pointed to the international law of self-defense and said if the facts were as the Trump administration alleged, the killings were lawful. Many cited a purported rule permitting armed force against imminent threats or dangers. U.S. Secretary of State Mike Pompeo said Soleimani was plotting just such future attacks on U. S. interests. The only problem is that there is no right to attack in such circumstances. The United Nations Charter, which regulates the inter-state use of force, does not use the term “imminent” or any variation on it. The Charter prohibits all use of force by member states in their international relations, unless the UN Security Council provides authorization or “an armed attack occurs”. This article challenges the long tradition of reading a right to attack when alleging imminent threats or dangers. The analysis will meet resistance, given the long acceptance that imminence is part of Charter Article 51. The law, however, is plain. Imminence forms no part of Article 51, and the negative consequences of believing that it does can be seen graphically throughout a year of unprecedented developments from the coronavirus pandemic to wide exposure of structural racism, to climate change and insurrection. All of these crises are linked to the killing of Soleimani and disregard of fundamental legal norms, none more important than the prohibition of armed force.

More than a mob: Parler as preparatory media for the U.S. Capitol storming

On 6 January 2021, a violent mob attacked the United States Capitol. Yet while mob suggests a chaotic and fragmented crowd, networked media had already been working to provide it with “just enough” cohesion, transforming it into a more dangerous political body. This article conceptualizes this preparatory media by examining the “free speech” social media network Parler, drawing on a corpus of ∼350,000 posts from the days leading up to and including the attack. This material empirically demonstrates how media worked to forge connections between disparate camps, to incite participants toward violent activity, and to legitimize this attack as moral or even spiritual. Preparatory media frames events, establishes targets, and sets agendas, providing a degree of order and working against disaggregation online. This temporary stabilization contributes to a more mobilized and organized public body. Rather than prosocial or emancipatory, the Capitol storming demonstrates the far darker potential of this work. Understanding this role of media and intervening within these logics provides one component for preventing future attacks.

A Randomized, Multicentric, Open Label, Interventional Study to Evaluate the Efficacy and Tolerability of Four Types of Amrutanjan Pain Balms for Pain Relief in Patients with Primary Type of Headache and Body Pain Disorders

Introduction: Body pain disorders like knee pain, low back pain and primary headache disorders impose burdens that include substantial personal suffering, impaired quality of life, and financial cost. Repeated attacks, and often fear of future attacks, affects the family life, social life, and employment. Objectives: To evaluate the Safety, Efficacy and tolerability of four types of Amrutanjan Pain Balm preparations for rapid pain relief in patients with primary type of headache and body pain disorders. Materials & Methods: This study is a randomized, multicentric, open label, interventional study conducted at a secondary care centre in Vellore. A total of 150 patients were screened and 144 patients were enrolled who were diagnosed with either body pain disorders like knee pain, low back pain or primary type of headache disorders like migraine, tension type headache and other primary head ache disorders. All the study participants were randomized to four arms of 36 each such that each arm comprised of 12 patients with knee pain, 12 patients with low back pain and 12 patients with primary headache disorder to receive four different formulations of Amrutanjan pain balms. Efficacy was evaluated by assessing pain reduction after treatment at various time points and duration of action. Visual analogue scale questionnaires were used post study to obtain feedback on overall status of improvement. Results: Patients enrolled with headache had 75 % tension-type, 17% migraine and 8% Cluster headache; those with knee joint Pain had osteoarthritis (80%) and reactive arthritis (20%) whereas patients with low back pain had lumbar strain and lumbar spondylosis. The onset of action was 55 seconds for patients with headache disorders, while it ranged between 95 to 115 seconds for joint pain and low back pain respectively. Highly significant improvement in the VAS score, was observed after 5, 10 and 30 minutes of test product application. Conclusion: All the four types of topical Amrutanjan balms were found to be effective and safe for the treatment of primary headache and body pain disorders.

Acute Pancreatitis

Acute pancreatitis is one of the most common reasons for gastroenterology-related hospitalization in the United States. With significant morbidity and subsequent mortality related to both the acute presentation and subsequent sequelae, prompt diagnosis and appropriate management are critical, especially in the first 24 hours of illness. It is also important to accurately recognize complications, such as pancreatic fluid collections and vascular events, and identify a definitive cause so that a strategy to prevent future attacks can be implemented.

Self-adaptive and secure mechanism for IoT based multimedia services: a survey

With the advent of internet of things (IoT) and IoT multimedia services in real-time applications, including smart healthcare, smart home, and smart connected transportation, IoT multimedia systems have significantly enhanced the lifestyle. However, the increased number of connected heterogeneous IoT multimedia devices have resulted in several vulnerabilities and cyberattacks. The existing multimedia in IoT multimedia security solutions are insufficient for detecting such complex attacks and require a self-adaptive security mechanism that can monitor the changing environment and detect, mitigate, plan, and prevent future prospective attacks in real time. In this study, we conduct a study of several self-adaptive security approaches for IoT multimedia and analyze them based on critical, security metrics to determine their level of support and the achieved satisfaction for IoT multimedia services. The evaluation results show significant insights, challenges, and concerns in the existing approaches, which can provide vital information for the development of future IoT multimedia security research. We propose a self-adaptive security model for IoT multimedia and discuss a case utilizing a mobile e-health system, where we use an adaptation model (using monitor-analyze-plan-execute over a shared knowledge adaptation loop) to determine the adaptation requirement based on the confidence level of several security factors. The adaptation requirement depicts that adaptation is required for stabilizing the security factors in a continuous context-changing sustainable e-health IoT multimedia environment.

Explicit polynomial regression models of wind characteristics and structural effects on a long‐span bridge utilizing onsite monitoring data

From 2010 to 2016, wind speed time history and synchronous acceleration responses along Xihoumen Bridge (XB) girder were recorded by a health-monitoring system. Based on this dataset, wind speed, wind direction, angle of attack (AoA), turbulence intensity, and turbulence length scale are studied based on 10-min time intervals. The environmental wind characteristics and synchronous structural effects are decoupled by the control variable method. The probabilistic dependence between wind parameters and structural responses is explored by explicit polynomial regression equations. With wind environment parameters as input, the acceleration responses of the bridge could be rapidly predicted with a certain confidence interval using decoupling and regression modeling (DRM). The proposed DRM can reproduce the buffeting acceleration responses when the bridge is subject to future potential strong typhoon attacks. The key factors affecting the buffeting responses of XB are analyzed and discussed. Generally, the buffeting acceleration responses of XB are significantly affected by wind speed and turbulence intensity rather than by turbulence length scale, which agrees well with previous observations.

Explainable artificial intelligence (XAI) interactively working with humans as a junior cyber analyst

There are many applications where artificial intelligence (AI) can add a benefit, but this benefit may not be fully realized, if the human cannot understand and interact with the output as required by their context. Allowing AI to explain its decisions can potentially mitigate this issue. To develop effective explainable AI methods to support this need, we need to understand both what the human needs for decision-making, as well as what information the AI has and can make available. This paper presents an example case of capturing those requirements. We explore how an operational planner (senior human analyst) for a cyber protection team could use a junior analyst virtual agent to scour, analyze, and present the data available on vulnerabilities and incidents on both the target systems as well as similar systems. We explore the interactions required to understand these outputs and to integrate additional knowledge held by the human. This is an exemplar case for integrating XAI into the real-world bi-directional workflow: the senior analyst needs to be able to understand the junior analysts results, particularly the assumptions and implications, in order to create a plan and brief it up the command chain. He or she may have further questions, or analysis needs to achieve this understanding. The application is the junior analyst agent and senior human analysts working together to create this understanding of threats, vulnerabilities, incidents, likely future attacks, and counteractions on the mission relevant cyber terrain that their unit has been assigned a mission on.

History, Present 2021 and Future of Cyber Attacks

Cyber-attacks are the attacks that target organizations and individuals either as a tool for other activities like identity theft, stalking, etc. or with a computer as a crime object like phishing, hacking, and spamming. Cyber-attacks are rapidly increasing and making cyber security a major concern currently. When launched successfully, cyber-attacks can cause massive damage to individuals and businesses. Hence, immediate response is mandatory to contain the situation in case cyber-attacks occur. In this paper, we will discuss the history, present and future of cyber-attacks and measures for organizations to prevent those attacks in future. The ever-elusive strategies and suspicious nature of criminals should also be identified. We have outlined some of the practices to prevent those attacks while recommending incidence response measures and updates in enterprises.

Predicting Factors of Cognitive Behavioral Therapy Process and Outcome for Panic Disorder: An Overview of Mechanisms of Change

Panic disorder is an anxiety disorder characterized by panic attacks which includes abrupt, intense, unexpected and recurrent fear and worry about possible future attacks. The disorder requires an effective treatment and cognitive behavioral therapy (CBT) for panic disorder has been proven to be beneficial in various studies. However, despite the effects, studies also demonstrate that people receiving treatment do not always improve to the same extent and that symptoms may relapse after treatment. Therefore, it is important to investigate factors that may promote better treatment outcomes in the long term. In this regard, it was aimed to review the cognitive behavior therapy process applied for panic disorder and examine factors predicting the outcome. Firstly, definition of panic disorder and its importance, then the assumptions and methods of CBT for panic disorder were described. Following that, in accordance with the main aim of the review, predictors of therapy process and outcome were examined. Predictors were divided into factors present before treatment and factors associated with therapy process. Those present before treatment are characteristics of the disorder, comorbid diagnosis and social environment conditions. Factors associated with therapy process included expectations from therapy, adherence, therapeutic alliance and cognitive and behavioral change mechanisms in CBT for PD. Change mechanisms encompassed catastrophizing misinterpretations, anxiety sensitivity, panic self-efficacy, temporal change and safety behaviors, which had been demonstrated to predict decreases in panic symptoms. Lastly, substantial points of the literature review were emphasized, and some suggestions were offered in the discussion section.

HomeTec Software for Security Aspects of Smart Home Devices Based on IoT

As useful as it gets to connect devices to the internet to make life easier and more comfortable, it also opens the gates to various cyber threats. The connection of Smart Home devices to the internet makes them vulnerable to malicious hackers that infiltrate the system. Hackers can penetrate these systems and have full control over devices. This can lead to denial of service, data leakage, invasion of privacy, etc. Thus security is a major aspect of Smart home devices. However, many companies manufacturing these Smart Home devices have little to no security protocols in their devices. In the process of making the IoT devices cheaper, various cost-cutting is done on the security protocols in IoT devices. In some way, many manufactures of the devices don’t even consider this as a factor to build upon. This leaves the devices vulnerable to attacks. Various authorities have worked upon to standardize the security aspects for the IoT and listed out guidelines for manufactures to follow, but many fail to abide by them. This paper introduces and talks about the various threats, various Security threats to Smart Home devices. It takes a deep dive into the solutions for the discussed threats. It also discusses their prevention. Lastly, it discusses various preventive measures and good practices to be incorporated to protect devices from any future attacks.

A Review of Rule Learning-Based Intrusion Detection Systems and Their Prospects in Smart Grids

Intrusion detection systems (IDS) are commonly categorized into misuse based, anomaly based and specification based IDS. Both misuse based IDS and anomaly based IDS are extensively researched in academia and industry. However, as critical infrastructures including smart grids (SG) may often face sophisticated unknown attacks in the near future, misuse based attack detection techniques will mostly miss their targets. Despite the fact that anomaly based IDS can detect novel attacks, they are not often deployed in industry, mainly owing to high false positive rate and lack of interpretability of trained models. With misuse based IDS’ inability to detect unknown attacks and requirement for frequently manually crafting and updating signatures and with anomaly based IDS’ bad reputation for high false alarm rate, specification based IDS can be regarded as the most suitable detection engine for cyber-physical systems (CPS) including SG. We argue that specification based IDS especially using rule learning could prove to be the most promising IDS for SG. Intrusion detection rules are learned through rule learning techniques and periodically automatically updated to accommodate dynamic system behaviors in SG. Fortunately, rule learning based IDS can not only detect previously unknown attacks but also achieve higher interpretability, due to symbolic representation of learned rules. It can thus be considered more “trustworthy” from human perspective and further assist human in the loop security operation. The present work provides a systematic and deep analysis of rule learning techniques and their suitability for IDS in SG. Besides, it concludes the most important criteria for learning intrusion detection rules and assessing their quality. This work serves not only as a guide to a number of important rule learning techniques but also as the first survey on their applications in IDS, which indicates their potential opportunities in SG security.