Veritatem Cognoscere: The DEI Threat to National Security

The concept of “intelligence” represents an important subject for researchers, developed over time in many categories, such as business intelligence, competitive intelligence, and national security intelligence. Even so, those meanings basically refer to the same capacity for processing data, information, and knowledge, their differences coming from their area of expertise. Given this, national security intelligence is associated with state institutions, while business intelligence and competitive intelligence are associated with private companies. National security intelligence represents the capacity of the leaders of a country to process the significant data, information, and knowledge for that country's security from all possible perspectives. To achieve this performance, each country has its own intelligence structures that must collect data and information, analyze and transform them into valuable knowledge for the decision-makers. The methods and means used by these intelligence structures for conducting specific activities are mainly secret and classified. This paper represents a literature review regarding the possible links and connections between national security intelligence, business intelligence, and competitive intelligence, aiming to discover the possible similarities between these concepts. We used the bibliometric analysis conducted with the specialized software VOSViewer to achieve this goal. This analysis was focused on the co-occurrence procedure using words and expressions from article titles, abstracts, and keywords. The databases used for this paper were retrieved from the Web of Science core collection, using the following expressions for searching: ”business intelligence – competitive intelligence,” ”business intelligence - national security,” and ”competitive intelligence - national security.” The results showed that no publications approach the differences between business, competitive, and national security intelligence.

Transnational threats including organised crime and terrorism pose serious physical and national security concerns, and have significant economic and social costs. Despite these widely recognised harms, there is limited literature on using strategic intelligence resources to understand and assess transnational threats to enable action to reduce them. Whilst there is growing consensus that national security and national law enforcement intelligence challenges are moving closer together – especially in relation to transnational threats – there is very little theory or practitioner guidance. This article presents an applied national law enforcement case study; the provision of strategic intelligence assessments to senior decision-makers of the Australian Federal Police intended to improve decision-making. During this case study, practitioners drew on national security intelligence approaches and analytical techniques to produce strategic assessments of transnational threats. The case study addressed challenges raised in the literature as obstacles to effective strategic intelligence, including ambiguity relating to the role of intelligence in the criminal environment, a broad range of divergent threat types and the need to demonstrate value of strategic intelligence for decision-makers. This has broader applicability in different jurisdictions and on different topics due to the focus on consultation, engagement and collaboration alongside traditional intelligence processes. Given the lack of literature in the field, it makes a contribution to understanding and developing best practice in strategic intelligence as applicable to national policing and security.

On November 23, 2021, Mr. Artur Wilczynski, Associate Deputy Chief at Communications Security Establishment (CSE), presented on Equity, Diversity, and Inclusion in National Security Intelligence at the 2021 CASIS Vancouver West Coast Security Conference. This presentation was followed by a question and answer period and a breakout room session with questions from the audience and CASIS Vancouver executives. The key points discussed included how a lack of diversity in intelligence can negatively contribute to Canada’s national security, how diversity broadens the effectiveness of organizations, and how Canadian national security institutions must be in service to all Canadians.

Due to the increasing amount of information in web-based environment, analysts nowadays need information extracted from different sources. Extracting this information to guide decision making in a national security perspective remains a challenging task. The major issue arises due to a large amount of irrelevant information or complexity of unstructured data which makes information extraction and classification a very tedious task while analyzing the textual content for finding various aspects of entities or groups. In this paper, we describe our efforts towards introducing a context-based information extraction using National Security Information Sources (NSIS) which employs different types of knowledge inspired by natural activities of living things. In order to improve classification performance by utilizing relevant information from the sources related to national security and to make better decision, we assume that entities and relationships from these sources can be used to contextualize information from the records. This paper presents a new method for nature-inspired classification after extracting various features from dataset created using social posts and records. Then, analysis of classes of information to concepts available on knowledge sources is carried out to ensure quality of information based on the user needs. The simulation results demonstrated the ability of the proposed method inspired by cultural algorithm to extract group-centric information and improve classification performance using proposed Social Info Finder (SIF). This paper highlights the challenges and application of proposed SIF method to improve information extraction and performance of text classification focusing on national security and related threats.

This chapter examines the offensive strategies employed by the United States and the Soviet Union in fighting the Cold War. It begins with a discussion of US covert operations and its revised national security strategy, focusing on Operation Solarium, the search for a post-Solarium national security policy, and subversion and intelligence gathering. It then considers the Berlin Crises, noting that Berlin was at the heart of the Cold War, the heart of the German question, and on several occasions became the focus of tension between the two blocs in Europe. The airlift of 1948–9 to preserve the Western position in the city, which was an island in East Germany, had become a potent Cold War symbol. The chapter concludes with an analysis of the Offshore Islands Crises and the Cuban Missile Crisis.

Now-a-days, the primary focus of the search techniques in the first generation of the Web is accessing relevant documents from the Web. Though it satisfies user requirements, but it is insufficient as the user sometimes wishes to access actionable information involving complex relationships between two given entities. Finding such complex relationships (also known as semantic associations) is especially useful in applications such as National Security, Pharmacy and Business Intelligence etc. Therefore the next frontier is discovering relevant semantic associations between two entities present in large semantic metadata repositories. Given two entities, there exist a huge number of semantic associations between two entities. Hence ranking of these associations is required in order to find more relevant associations. For this Aleman Meza et al. proposed a method involving six metrics viz. context, subsumption, rarity, popularity, association length and trust. To compute the overall rank of the associations this method computes context, subsumption, rarity and popularity values for each component of the association and for all the associations. However it is obvious that, many components appears repeatedly in many associations therefore it is not necessary to compute context, subsumption, rarity and popularity values of the components every time for each association rather the previously computed values may be used while computing the overall rank of the associations. This paper proposes a method to reuse the previously computed values using a hash data structure thus reduce the execution time. To demonstrate the effectiveness of the proposed method, experiments were conducted on SWETO ontology. Results show that the proposed method is more efficient than the other existing methods.

This chapter examines the offensive strategies employed by the United States and the Soviet Union in fighting the Cold War. It begins with a discussion of US covert operations and its revised national security strategy, focusing on Operation Solarium, the search for a post-Solarium national security policy, and subversion and intelligence gathering. It then considers the Berlin crises, noting that Berlin was at the heart of the Cold War, the heart of the German question, and on several occasions became the focus of tension between the two blocs in Europe. The airlift of 1948–9 to preserve the Western position in the city, which was an island in East Germany, had become a potent Cold War symbol. The chapter concludes with an analysis of the Offshore Islands crises and the Cuban missile crisis.

Social media is the most responsive method in modern times for communication through the Internet platform. Social media has evolved and continued to shape how we communicate to share our opinions and feelings. It has brought in a consistent real-time communication pattern that has never been in existence before now. Young and older people, organizations, government institutions, professional bodies, etc., have dedicated social media presence through which they interact with other users. Social media also serves as a strong network engine that links users irrespective of their geographical locations. This new communication platform will be available in the future with a significant role in global communication enhancement. Hence, there is an urgent need to study usage patterns in social media platforms to proffer automated systems that intelligence agencies can utilize as a service for national security incidents prevention. This research study proposes an automated machine learning model that can enhance quick intervention to national security incidents through social media data mining.

The authors propose that valuation of information metrics developed near the end of the intelligence cycle are appropriate supplemental metrics for national security intelligence. Existing information and decision theoretic frameworks are often either inapplicable in the context of national security intelligence or they capture affects from inputs aside from just the information or intelligence. Applied information theory looks at the syntactic transmission of information rather than assigning it a quantitative value. Information economics determines the market value of information, which is also inapplicable in a national security intelligence context. Decision analysis can use the value of information to show the expected value of perfect information (EVPI) and the expected value of imperfect information (EVII) and although this method can be used with utility theory and not just monetary objectives, it has been shown that decision makers within the intelligence community (IC) have difficulty agreeing upon how to value objectives within analysis. Additionally, it is difficult to determine how decision makers use intelligence in the decision-making process, which makes existing decision theoretic methods problematic, and might include inputs from variables besides just the intelligence.

The authors propose that valuation of information metrics developed near the end of the intelligence cycle are appropriate supplemental metrics for national security intelligence. Existing information and decision theoretic frameworks are often either inapplicable in the context of national security intelligence or they capture affects from inputs aside from just the information or intelligence. Applied information theory looks at the syntactic transmission of information rather than assigning it a quantitative value. Information economics determines the market value of information, which is also inapplicable in a national security intelligence context. Decision analysis can use the value of information to show the expected value of perfect information (EVPI) and the expected value of imperfect information (EVII) and although this method can be used with utility theory and not just monetary objectives, it has been shown that decision makers within the intelligence community (IC) have difficulty agreeing upon how to value objectives within analysis. Additionally, it is difficult to determine how decision makers use intelligence in the decision-making process, which makes existing decision theoretic methods problematic, and might include inputs from variables besides just the intelligence.

National security intelligence (NSI) activity is considered through a normative (ethical) lens and the application of a normative theory to NSI collection, analysis, and dissemination undertaken. The currently favored normative theory is the Just Intelligence Theory (JIT), derived from the Just War Theory, applicable to waging war. Whereas JIT has provided a useful starting point to normative theorizing about NSI activity as well as several specific insights, it has several significant deficiencies as a general overarching normative theory of NSI activity and, therefore, should be abandoned by qua general theory. For instance, NSI activity is largely epistemic (or knowledge-focused) activity, whereas waging war is kinetic activity, and this has important ethical consequences, such as that the principle of last resort applicable to waging war is not applicable to NSI activity. Moreover, other principles, such as the principle of discrimination, are applicable in a radically different manner.

Mass and Elite Attitudes About Wiretapping in Canada: Implications for Democratic Theory and Politics

This book explores the use of artificial intelligence by intelligence services around the world and its critical role in intelligence analysis, defense, and national security. Intelligence services play a crucial role in national security, and the adoption of artificial intelligence technologies has had a significant impact on their operations. It also examines the various applications of artificial intelligence in intelligence services, the implications, challenges and ethical considerations associated with its use. The book emphasizes the need for continued research and development in the field of artificial intelligence to ensure that intelligence services. and overall national defense and security can effectively adapt to emerging threats.

This article examines the issues of economic stability, sustainable development, and security intelligence challenges in Kaduna State from 2022 to 2024, with a specific focus on the Zaria Local Government area. The study utilised conflict theory as its theoretical framework and employed purposive and stratified sampling methods. A combination of questionnaires and in-depth interviews was conducted. A total of eighty-six respondents from various Nigerian security intelligence agencies, including the CID, NIA, SSS, and DMI, were selected. Key findings include the role of security intelligence in mitigating security threats in Kaduna State; however, poor coordination was identified as the primary barrier to the practical application of security intelligence in the state. Additional obstacles highlighted were a lack of resources, corruption, and inadequate training. The study suggests providing socially sufficient social amenities and developmental initiatives to help individuals avoid vulnerable situations that could lead to conflict and insecurity. It emphasises the need for Federal, State, and Local governments to prioritise specific programs and projects aimed at job creation and fostering entrepreneurship among the youth. National security agencies and relevant stakeholders should improve their capabilities for intelligence gathering, sharing, detection, and investigation. Furthermore, National Orientation Agencies, relevant organisations, and NGOs should consistently promote awareness and educate the population on the importance of peaceful coexistence, respect, tolerance, and diversity. Lastly, ongoing training and capacity development for all national security personnel should focus on security intelligence and the strategies employed by contemporary organised criminal activities.

This paper designs a cross-platform data interaction and information fusion mechanism for national security-oriented public security intelligence. The data interaction mechanism enables automatic cross-platform data invocation and cross-platform contract invocation. Subsequently, the encrypted communication protocol and security constraint algorithm for public security intelligence data are designed. Then the information fusion method based on information grid is designed. Simulation experiments show that the data interaction and information fusion mechanism proposed in this paper can accurately realize the adaptive scheduling of public security intelligence cross-platform, with a high information recall rate and a good checking accuracy rate. It improves the level of cross-platform data interaction and sharing of public security intelligence and intelligent management capability.