THREAT INTELLIGENCE CONFERENCE


Threat Intelligence Conference is one of the leading research topics in the international research conference domain. Threat Intelligence is a conference track under the Law Conference which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of Law.

internationalconference.net provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of (Law).

Threat Intelligence is not just a call for academic papers on the topic; it can also include a conference, event, symposium, scientific meeting, academic, or workshop.

You are welcome to SUBMIT your research paper or manuscript to Threat Intelligence Conference Track will be held at .

Threat Intelligence is also a leading research topic on Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, Elsevier, Scopus, Web of Science.

FINISHED

I. INTERNATIONAL LAW CONFERENCE

MARCH 19 - 20, 2019
ISTANBUL, TURKEY

FINISHED

II. INTERNATIONAL LAW CONFERENCE

JUNE 26 - 27, 2019
PARIS, FRANCE

FINISHED

III. INTERNATIONAL LAW CONFERENCE

AUGUST 21 - 22, 2019
LONDON, UNITED KINGDOM

FINISHED

IV. INTERNATIONAL LAW CONFERENCE

OCTOBER 08 - 09, 2019
NEW YORK, UNITED STATES

FINISHED

V. INTERNATIONAL LAW CONFERENCE

DECEMBER 12 - 13, 2019
ROME, ITALY

FINISHED

VI. INTERNATIONAL LAW CONFERENCE

FEBRUARY 13 - 14, 2020
LONDON, UNITED KINGDOM

FINISHED

VII. INTERNATIONAL LAW CONFERENCE

APRIL 15 - 16, 2020
BARCELONA, SPAIN

FINISHED

VIII. INTERNATIONAL LAW CONFERENCE

MAY 11 - 12, 2020
ISTANBUL, TURKEY

FINISHED

IX. INTERNATIONAL LAW CONFERENCE

JUNE 05 - 06, 2020
SAN FRANCISCO, UNITED STATES

FINISHED

X. INTERNATIONAL LAW CONFERENCE

JULY 20 - 21, 2020
PARIS, FRANCE

FINISHED

XI. INTERNATIONAL LAW CONFERENCE

AUGUST 10 - 11, 2020
NEW YORK, UNITED STATES

FINISHED

XII. INTERNATIONAL LAW CONFERENCE

SEPTEMBER 10 - 11, 2020
TOKYO, JAPAN

FINISHED

XIII. INTERNATIONAL LAW CONFERENCE

SEPTEMBER 16 - 17, 2020
ZÜRICH, SWITZERLAND

FINISHED

XIV. INTERNATIONAL LAW CONFERENCE

OCTOBER 21 - 22, 2020
BARCELONA, SPAIN

FINISHED

XV. INTERNATIONAL LAW CONFERENCE

NOVEMBER 02 - 03, 2020
SAN FRANCISCO, UNITED STATES

FINISHED

XVI. INTERNATIONAL LAW CONFERENCE

NOVEMBER 12 - 13, 2020
ISTANBUL, TURKEY

FINISHED

XVII. INTERNATIONAL LAW CONFERENCE

NOVEMBER 19 - 20, 2020
SINGAPORE, SINGAPORE

FINISHED

XVIII. INTERNATIONAL LAW CONFERENCE

DECEMBER 15 - 16, 2020
BANGKOK, THAILAND

FINISHED

XIX. INTERNATIONAL LAW CONFERENCE

DECEMBER 28 - 29, 2020
PARIS, FRANCE

FINISHED

XX. INTERNATIONAL LAW CONFERENCE

FEBRUARY 13 - 14, 2021
LONDON, UNITED KINGDOM

FINISHED

XXI. INTERNATIONAL LAW CONFERENCE

APRIL 15 - 16, 2021
BARCELONA, SPAIN

FINISHED

XXII. INTERNATIONAL LAW CONFERENCE

MAY 11 - 12, 2021
ISTANBUL, TURKEY

FINISHED

XXIII. INTERNATIONAL LAW CONFERENCE

JUNE 05 - 06, 2021
SAN FRANCISCO, UNITED STATES

FINISHED

XXIV. INTERNATIONAL LAW CONFERENCE

JULY 20 - 21, 2021
PARIS, FRANCE

FINISHED

XXV. INTERNATIONAL LAW CONFERENCE

AUGUST 10 - 11, 2021
NEW YORK, UNITED STATES

FINISHED

XXVI. INTERNATIONAL LAW CONFERENCE

SEPTEMBER 10 - 11, 2021
TOKYO, JAPAN

FINISHED

XXVII. INTERNATIONAL LAW CONFERENCE

SEPTEMBER 16 - 17, 2021
ZÜRICH, SWITZERLAND

FINISHED

XXVIII. INTERNATIONAL LAW CONFERENCE

OCTOBER 21 - 22, 2021
BARCELONA, SPAIN

FINISHED

XXIX. INTERNATIONAL LAW CONFERENCE

NOVEMBER 02 - 03, 2021
SAN FRANCISCO, UNITED STATES

FINISHED

XXX. INTERNATIONAL LAW CONFERENCE

NOVEMBER 12 - 13, 2021
ISTANBUL, TURKEY

FINISHED

XXXI. INTERNATIONAL LAW CONFERENCE

NOVEMBER 19 - 20, 2021
SINGAPORE, SINGAPORE

FINISHED

XXXII. INTERNATIONAL LAW CONFERENCE

DECEMBER 15 - 16, 2021
BANGKOK, THAILAND

FINISHED

XXXIII. INTERNATIONAL LAW CONFERENCE

DECEMBER 28 - 29, 2021
PARIS, FRANCE

Law Conference Call For Papers are listed below:

Previously Published Papers on "Threat Intelligence Conference"

  • Factors Affecting Employee Decision Making in an AI Environment
    Authors: Yogesh C. Sharma, A. Seetharaman, Keywords: Employee decision making, artificial intelligence, environment, human trust, technology innovation, psychological safety. DOI:10.5281/zenodo. Abstract: The decision-making process in humans is a complicated system influenced by a variety of intrinsic and extrinsic factors. Human decisions have a ripple effect on subsequent decisions. In this study, the scope of human decision making is limited to employees. In an organisation, a person makes a variety of decisions from the time they are hired to the time they retire. The goal of this research is to identify various elements that influence decision making. In addition, the environment in which a decision is made is a significant aspect of the decision-making process. Employees in today's workplace use artificial intelligence (AI) systems for automation and decision augmentation. The impact of AI systems on the decision-making process is examined in this study. This research is designed based on a systematic literature review. Based on gaps in the literature, limitations and the scope of future research have been identified. Based on these findings, a research framework has been designed to identify various factors affecting employee decision making. Employee decision making is influenced by technological advancement, data-driven culture, human trust, decision automation-augmentation and workplace motivation. Hybrid human-AI systems require development of new skill sets and organisational design. Employee psychological safety and supportive leadership influences overall job satisfaction.
  • Terrorism as a Threat to International Peace: A Study on 9/11 Terrorism
    Authors: Aftab, Keywords: Domains, global disorder, internal disorder, international peace, terrorism, threat. DOI:10.5281/zenodo. Abstract: This paper is a theory-oriented study that seeks to generalize the process through which terrorism leads to the disruption of international peace. For this, it scrutinizes 9/11 terrorism based on five analytical domains of threat—security disorder, political tensions, economic adversity, socio-ideological intolerance, and the fear and cost of counterterrorism—each of which is explored in light of specific indicators. By applying qualitative correlation method, the paper finds that terrorism immediately entails five distinct kinds of negative impacts that lead to both internal disorders caused by state weakness and global disorder caused by international tensions, which in consequence, causes international peace to be disrupted. Thus, in following inductive process, the findings of this paper help to make a general inference that terrorism is a threat to international peace. 
  • Military Use of Artificial Intelligence under International Humanitarian Law: Insights from Canada
    Authors: Mahshid Talebian Kiakalayeh, Keywords: Artificial intelligence, military use, International Humanitarian Law, the Canadian perspective. DOI:10.5281/zenodo. Abstract: As artificial intelligence (AI) technologies can be used by both civilians and soldiers; it is vital to consider the consequences emanating from AI military as well as civilian use. Indeed, many of the same technologies can have a dual-use. This paper will explore the military uses of AI and assess their compliance with international legal norms. AI developments not only have changed the capacity of the military to conduct complex operations but have also increased legal concerns. The existence of a potential legal vacuum in legal principles on the military use of AI indicates the necessity of more study on compliance with International Humanitarian Law (IHL), the branch of international law which governs the conduct of hostilities. While capabilities of new means of military AI continue to advance at incredible rates, this body of law is seeking to limit the methods of warfare protecting civilian persons who are not participating in an armed conflict. Implementing AI in the military realm would result in potential issues including ethical and legal challenges. For instance, when intelligence can perform any warfare task without any human involvement, a range of humanitarian debates will be raised as to whether this technology might distinguish between military and civilian targets or not. This is mainly because AI in fully military systems would not seem to carry legal and ethical judgment which can interfere with IHL principles. The paper will take, as a case study, Canada’s compliance with IHL in the area of AI and the related legal issues that are likely to arise as this country continues to develop military uses of AI.
  • Conceptualizing Thoughtful Intelligence for Sustainable Decision Making
    Authors: Musarrat Jabeen, Keywords: Thoughtful intelligence, Sustainable decision making, Thoughtful decision support system. DOI:10.5281/zenodo. Abstract: Thoughtful intelligence offers a sustainable position to enhance the influence of decision-makers. Thoughtful Intelligence implies the understanding to realize the impact of one’s thoughts, words and actions on the survival, dignity and development of the individuals, groups and nations. Thoughtful intelligence has received minimal consideration in the area of Decision Support Systems, with an end goal to evaluate the quantity of knowledge and its viability. This pattern degraded the imbibed contribution of thoughtful intelligence required for sustainable decision making. Given the concern, this paper concentrates on the question: How to present a model of Thoughtful Decision Support System (TDSS)? The aim of this paper is to appreciate the concepts of thoughtful intelligence and insinuate a Decision Support System based on thoughtful intelligence. Thoughtful intelligence includes three dynamic competencies: i) Realization about long term impacts of decisions that are made in a specific time and space, ii) A great sense of taking actions, iii) Intense interconnectivity with people and nature and; seven associate competencies, of Righteousness, Purposefulness, Understanding, Contemplation, Sincerity, Mindfulness, and Nurturing. The study utilizes two methods: Focused group discussion to count prevailing Decision Support Systems; 70% results of focus group discussions found six decision support systems and the positive inexistence of thoughtful intelligence among decision support systems regarding sustainable decision making. Delphi focused on defining thoughtful intelligence to model (TDSS). 65% results helped to conceptualize (definition and description) of thoughtful intelligence. TDSS is offered here as an addition in the decision making literature. The clients are top leaders.
  • Personal Factors and Career Adaptability in a Call Centre Work Environment: The Mediating Effects of Professional Efficacy
    Authors: Nisha Harry, Keywords: Call centre, professional efficacy, career adaptability, emotional intelligence. DOI:10.5281/zenodo. Abstract: The study discussed in this article sought to assess whether a sense of professional efficacy mediates the relationship between personal factors and career adaptability. A quantitative cross-sectional survey approach was followed. A non–probability sample of (N = 409) of which predominantly early career and permanently employed black females in call centres in Africa participated in this study. In order to assess personal factors, the participants completed sense of meaningfulness and emotional intelligence measures. Measures of professional efficacy and career adaptability were also completed. The results of the mediational analysis revealed that professional efficacy significantly mediates the meaningfulness (sense of coherence) and career adaptability relationship, but not the emotional intelligence–career adaptability relationship. Call centre agents with professional efficacy are likely to be more work engaged as a result of their sense of meaningfulness and emotional intelligence.
  • Predicting the Success of Bank Telemarketing Using Artificial Neural Network
    Authors: Mokrane Selma, Keywords: Bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network. DOI:10.5281/zenodo. Abstract: The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.
  • A Weighted Group EI Incorporating Role Information for More Representative Group EI Measurement
    Authors: Siyu Wang, Anthony Ward, Keywords: Emotional intelligence, EI, Group EI, multi-method research, teamwork. DOI:10.5281/zenodo.3462111 Abstract: Emotional intelligence (EI) is a well-established personal characteristic. It has been viewed as a critical factor which can influence an individual's academic achievement, ability to work and potential to succeed. When working in a group, EI is fundamentally connected to the group members' interaction and ability to work as a team. The ability of a group member to intelligently perceive and understand own emotions (Intrapersonal EI), to intelligently perceive and understand other members' emotions (Interpersonal EI), and to intelligently perceive and understand emotions between different groups (Cross-boundary EI) can be considered as Group emotional intelligence (Group EI). In this research, a more representative Group EI measurement approach, which incorporates the information of the composition of a group and an individual’s role in that group, is proposed. To demonstrate the claim of being more representative Group EI measurement approach, this study adopts a multi-method research design, involving a combination of both qualitative and quantitative techniques to establish a metric of Group EI. From the results, it can be concluded that by introducing the weight coefficient of each group member on group work into the measurement of Group EI, Group EI will be more representative and more capable of understanding what happens during teamwork than previous approaches.
  • Technology, Organizational and Environmental Determinants of Business Intelligence Systems Adoption in Croatian SME: A Case Study of Medium-Sized Enterprise
    Authors: Ana-Marija Stjepić, Luka Sušac, Dalia Suša Vugec, Keywords: Adoption, business intelligence, business intelligence systems, case study, TOE framework. DOI:10.5281/zenodo.3298898 Abstract: In the last few years, examples from scientific literature and business practices show that the adoption of technological innovations increases enterprises' performance. Recently, when it comes to the field of information technology innovation, business intelligence systems (BISs) have drawn a significant amount of attention of the scientific circles. BISs can be understood as a form of technological innovation which can bring certain benefits to the organizations that are adopting it. Therefore, the aim of this paper is twofold: (1) to define determinants of successful BISs adoption in small and medium enterprises and thus contribute to this neglected research area and (2) to present the current state of BISs adoption in small and medium-sized companies. In order to do so, determinants are defined and classified into three dimensions, according to the Technology – Organization – Environment (TOE) theoretical framework that describes the impact of each dimension on technological innovations adoption. Moreover, paper brings a case study presenting the adoption of BISs in practice within an organization from tertiary (service) industry sector. Based on the results of the study, guidelines for more efficient, faster and easier BISs adoption are presented.
  • Using Business Intelligence Capabilities to Improve the Quality of Decision-Making: A Case Study of Mellat Bank
    Authors: Jalal Haghighat Monfared, Zahra Akbari, Keywords: Business intelligence, business intelligence capability, decision making, decision quality. DOI:10.5281/zenodo.2571904 Abstract: Today, business executives need to have useful information to make better decisions. Banks have also been using information tools so that they can direct the decision-making process in order to achieve their desired goals by rapidly extracting information from sources with the help of business intelligence. The research seeks to investigate whether there is a relationship between the quality of decision making and the business intelligence capabilities of Mellat Bank. Each of the factors studied is divided into several components, and these and their relationships are measured by a questionnaire. The statistical population of this study consists of all managers and experts of Mellat Bank's General Departments (including 190 people) who use commercial intelligence reports. The sample size of this study was 123 randomly determined by statistical method. In this research, relevant statistical inference has been used for data analysis and hypothesis testing. In the first stage, using the Kolmogorov-Smirnov test, the normalization of the data was investigated and in the next stage, the construct validity of both variables and their resulting indexes were verified using confirmatory factor analysis. Finally, using the structural equation modeling and Pearson's correlation coefficient, the research hypotheses were tested. The results confirmed the existence of a positive relationship between decision quality and business intelligence capabilities in Mellat Bank. Among the various capabilities, including data quality, correlation with other systems, user access, flexibility and risk management support, the flexibility of the business intelligence system was the most correlated with the dependent variable of the present research. This shows that it is necessary for Mellat Bank to pay more attention to choose the required business intelligence systems with high flexibility in terms of the ability to submit custom formatted reports. Subsequently, the quality of data on business intelligence systems showed the strongest relationship with quality of decision making. Therefore, improving the quality of data, including the source of data internally or externally, the type of data in quantitative or qualitative terms, the credibility of the data and perceptions of who uses the business intelligence system, improves the quality of decision making in Mellat Bank.
  • SeCloudBPMN: A Lightweight Extension for BPMN Considering Security Threats in the Cloud
    Authors: Somayeh Sobati Moghadam, Keywords: BPMN, security threats, cloud computing, graphical representation. DOI:10.5281/zenodo.1474423 Abstract: Business processes are crucial for organizations and help businesses to evaluate and optimize their performance and processes against current and future-state business goals. Outsourcing business processes to the cloud becomes popular due to a wide varsity of benefits and cost-saving. However, cloud outsourcing raises enterprise data security concerns, which must be incorporated in Business Process Model and Notation (BPMN). This paper, presents SeCloudBPMN, a lightweight extension for BPMN which extends the BPMN to explicitly support the security threats in the cloud as an outsourcing environment. SeCloudBPMN helps business’s security experts to outsource business processes to the cloud considering different threats from inside and outside the cloud. In this way, appropriate security countermeasures could be considered to preserve data security in business processes outsourcing to the cloud.

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