Defense Perspective Research Articles

Initiation of forensic examinations by the defence counsel: topical issues of forensic support

The article is devoted to the consideration of topical issues of initiation of forensic examinations by the defence counsel, as well as forensic support of this activity. The relevance of the topic is due to the fact that the initiation of forensic examinations by the defence counsel is an important aspect of the criminal process which affects not only the formation of the evidence base for the prosecution, but also for the defence, which can establish the circumstances that justify or mitigate the responsibility of the defendant. The article focuses on the fact that the defence counsel may obtain an expert opinion in three ways at the stage of pre-trial investigation: 1) defence counsel’s independent request to an expert or an expert institution to conduct an expert examination; 2) defence counsel’s initiation of a forensic examination by an investigating judge; 3) defence counsel’s initiation of a forensic examination by an investigator, coroner, or prosecutor. It is noted that the organisational activities of a defence counsel who plans to initiate a forensic examination before an investigator, coroner, or prosecutor include three stages: preparatory, working, and final. The author analyses all three stages of organisational activities of a defence counsel who plans to initiate a forensic examination, both from the criminal procedural and forensic sides. The author emphasises that when filing a relevant motion, a defence counsel should always clearly understand what specific purpose is being pursued and what result is desirable from the defence perspective. The author comes to the conclusion that forensic support for the defence counsel’s initiation of forensic examinations to the investigator, coroner, prosecutor is provided in the process of: preparation, submission of a petition, and familiarisation with the results of the examination.

A DDoS Tracking Scheme Utilizing Adaptive Beam Search with Unmanned Aerial Vehicles in Smart Grid

As IoT technology advances, the smart grid (SG) has become crucial to industrial infrastructure. However, SG faces security challenges, particularly from distributed denial of service (DDoS) attacks, due to inadequate security mechanisms for IoT devices. Moreover, the extensive deployment of SG exposes communication links to attacks, potentially disrupting communications and power supply. Link flooding attacks (LFAs) targeting congested backbone links have increasingly become a focal point of DDoS attacks. To address LFAs, we propose integrating unmanned aerial vehicles (UAVs) into the Smart Grid (SG) to offer a three-dimensional defense perspective. This strategy includes enhancing the speed and accuracy of attack path tracking as well as alleviating communication congestion. Therefore, our new DDoS tracking scheme leverages UAV mobility and employs beam search with adaptive beam width to reconstruct attack paths and pinpoint attack sources. This scheme features a threshold iterative update mechanism that refines the threshold each round based on prior results, improving attack path reconstruction accuracy. An adaptive beam width method evaluates the number of abnormal nodes based on the current threshold, enabling precise tracking of multiple attack paths and enhancing scheme automation. Additionally, our path-checking and merging method optimizes path reconstruction by merging overlapping paths and excluding previously searched nodes, thus avoiding redundant searches and infinite loops. Simulation results on the Keysight Ixia platform demonstrate a 98.89% attack path coverage with a minimal error tracking rate of 2.05%. Furthermore, simulations on the NS-3 platform show that drone integration not only bolsters security but also significantly enhances network performance, with communication effectiveness improving by 88.05% and recovering to 82.70% of normal levels under attack conditions.

Markov game based on reinforcement learning solution against cyber–physical attacks in smart grid

The rapid expansion of information networks has amplified vulnerabilities in cyberspace, particularly within the power grid and communication layers of smart grid systems. Safeguarding smart grid security has become imperative for users concerned about both online and offline privacy. Detecting attacks in smart grids is crucial for ensuring the safety and continuity of the electrical network. This paper introduces a novel stealth attack-defense game that examines the impact of these invasions on the availability, confidentiality, and integrity of phasor measurement units. The proposed system considers both attack and defense perspectives. Attackers focus on key parameters to covertly infiltrate system layers while defending the smart grid system requires advanced knowledge of data flow and critical insights to establish robust protections. To address this cybersecurity challenge, we propose a game approach based on a partially observed Markov game with an improved Shapley Q-value and a multi-agent reinforcement learning framework, implemented in cooperative, communicative, and dynamic environments. The evaluation results demonstrate the robustness of the proposed approach against coordinated attacks in smart grid environments. Additionally, the results emphasize the significance of attack distribution as a crucial trace for identifying the attack source. Our approach shows promise for addressing various types of attacks against smart grid systems.

Analysis of Paths to Effectively Safeguarding Property Owners Rights in Property Service Disputes from a Defensive Perspective

This paper begins by analyzing the current status of property service disputes, examining the complex legal relationships, widespread and voluminous disputes, and intense group struggles, revealing the true state of property service disputes. The article then focuses on introducing the main types of damage to property owners rights in property service disputes to demonstrate the necessity of safeguarding property owners rights from a defensive perspective. Simultaneously, it presents the concept, types, qualifications for exercising the right of defense, and the statute of limitations, comprehensively analyzing the real challenges faced by property owners in property service disputes, including issues such as the lack of legal provisions, the absence of clear standards for defining property service quality, obstacles to property owners exercising the right of defense due to internal and external factors, and jurisdictional attributes causing inconsistent judgments in similar cases. Finally, the paper proposes measures to improve the system for property owners right of defense and the protection of legitimate rights and interests in property service disputes, including the rational allocation of burden of proof, enhancing legal provisions for standardized discretion, refining the evaluation mechanism for the property service industry, and leveraging the primary role of the property owners committee and the supervisory role of property owners.

Assessing Economic Resilience in NATO Countries: A Comprehensive Defence Perspective

Economic resilience, considered in this paper as the ability to withstand and recover from economic shocks and disruptions, has become a linchpin of ensuring national security and stability. As demonstrated by conflicts such as the one in Ukraine, where economic sanctions were deployed to diminish an adversary’s capacity to sustain its war efforts, it has become evident that military power alone is insufficient in today’s complex security landscape. A comprehensive approach to defence must incorporate economic considerations, as the economic well-being of a nation is intrinsically linked to its overall security. The main research objectives of this paper are to investigate the concept of economic resilience, from the perspective of the concept of comprehensive defence and the ways it is interconnected with other resilience domains, through the development of an economic resilience index outlining the relative economic resilience of the 29 European countries that are NATO members and to propose a methodology for identifying the main factors that influence the economic resilience from a comprehensive defence point of view.

Historical Analysis of Nepal’s International Relations from a Defence Perspective

Nepal has a track record of being one of the oldest as well as ever sovereign and independent nations of the world. Today, Nepal’s international relations is going through a critical and vulnerable phase. One of the main reasons for this may be that Nepal abruptly abandoned and stopped learning from the deeds of the founding heroes and has not been able to chart and steer an effective national policy strategy in its international relations. In the past, many of the rulers used to be kings and military generals and they had adopted hard power as their main instruments. Today, Nepal cannot think of hard power but rather soft power and smart power. At this point, it would be pertinent to reflect on Nepal’s past international relations policy strategy so it may help to understand the value and role of national security policy strategy as an integral part of successful international relations in the future. This paper has tried to examine the international relations of contemporary Nepal from a defense perspective based on historical references.

Measuring economic resilience for the CEE and Black Sea countries in the framework of comprehensive defense

The main research objective of this paper is to identify key factors influencing economic resilience from the perspective of comprehensive defence. This involves developing a composite economic resilience index (Ericda) that outlines the relative economic resilience of countries in Central and Eastern Europe and the Black Sea regions, within the comprehensive defence framework. The paper employs qualitative research methods, focusing on an analysis of specialist literature pertaining to economic resilience. Quantitative methods are also used for developing the Economic Resilience Index from the Comprehensive Approach to Defence (Ericda) perspective. This includes using data on selected resilience indicators in Central and the Eastern European and Black Sea region countries to generate rankings. The results of the study reveal strong positive correlations between the economic resilience index and various factors, such as logistics and infrastructure, economic complexity, foreign trade vulnerabilities and dependence, economic stability and development, governance effectiveness, military, and human capital. Additionally, a negative correlation was observed with the resilience index. The research findings suggest that to ensure effective comprehensive defence, isolated measures targeting individual pillars are inadequate. Economic resilience requires a collaborative approach, extending beyond the purview of the finance ministry and involving a broader range of stakeholders.

Generative Adversarial Networks: A Survey on Attack and Defense Perspective

Generative Adversarial Networks (GANs) are a remarkable creation with regard to deep generative models. Thanks to their ability to learn from complex data distributions, GANs have been credited with the capacity to generate plausible data examples, which have been widely applied to various data generation tasks over image, text, and audio. However, as with any powerful technology, GANs have a flip side: their capability to generate realistic data can be exploited for malicious purposes. Many recent studies have demonstrated the security and privacy (S&P) threats brought by GANs, especially the attacks on machine learning (ML) systems. Nevertheless, so far as we know, there is no existing survey that has systematically categorized and discussed the threats and strategies of these GAN-based attack methods. In this article, we provide a comprehensive survey of GAN-based attacks and countermeasures. We summarize and articulate: (1) what S&P threats of GANs expose to ML systems; (2) why GANs are useful for certain attacks; (3) what strategies can be used for GAN-based attacks; and (4) what countermeasures can be effective to GAN-based attacks. Finally, we provide several promising research directions combining the existing limitations of GAN-based studies and the prevailing trend in the associated research fields.

Some Remarks from the Defence Perspective

Some Remarks from the Defence Perspective

Conflict Analysis and Papuan Policies from a Social, Economic and National Defense Perspective

Objective: An analysis of the ongoing conflict and policies in Papua is essential to understand how to combat the current situation effectively. To understand the broader picture, it is necessary to delve into the conflict's background, including cultural differences, armed groups, political agendas, and other factors.
 
 Method: This study will qualitatively to achieve this aim, the conflict and policies will be analysed in two ways, namely macro and micro. The macro analysis will examine the background of the conflict and also look at the methods used by the Indonesian government since the 1969 Act of Free Choice.
 
 Result: Examining past, present, and future policies is also crucial in trying to resolve the conflict and is closely linked to the factors under analysis. The first step is to assess the impact of these factors on the conflict and policies, followed by the results and solutions.
 
 Conclusion: Finally, proposals for implementing these solutions must be developed and tested to demonstrate their effectiveness.

Optimum Location for Backup Land Uses From the Perspective of Passive Defense in Urmia City

Background and objective This study aim is to find the optimal location form backup land uses from the perspective of passive defense in Urmia City. This is an applied, descriptive, and analytical study. Method Data collection was done using documentary data, a field study, and a questionnaire. Participants were 10 experts in this subject, who were selected purposefully. The network analysis process (ANP) was used to analyze the data. A dynamic and comprehensive model was prepared to locate fuel centers, fire stations, and hospitals from the perspective of passive defense. Results The findings showed that Ali Gorge neighborhood and a part of the Hezaran neighborhood were suitable places for fire stations. Ali Gorge neighborhood was a completely suitable location for fuel stations. Moreover, the neighborhoods of Ali Gorge and Haft-Asiab were completely suitable locations for the construction of hospitals. Conclusion It can be concluded that Ali Gorge neighborhood has more suitable conditions than other neighborhoods for locating backup land uses. Therefore, special attention should be paid to this neighborhood by the city managers.

Discrete Adversarial Attack to Models of Code

The pervasive brittleness of deep neural networks has attracted significant attention in recent years. A particularly interesting finding is the existence of adversarial examples, imperceptibly perturbed natural inputs that induce erroneous predictions in state-of-the-art neural models. In this paper, we study a different type of adversarial examples specific to code models, called discrete adversarial examples , which are created through program transformations that preserve the semantics of original inputs.In particular, we propose a novel, general method that is highly effective in attacking a broad range of code models. From the defense perspective, our primary contribution is a theoretical foundation for the application of adversarial training — the most successful algorithm for training robust classifiers — to defending code models against discrete adversarial attack. Motivated by the theoretical results, we present a simple realization of adversarial training that substantially improves the robustness of code models against adversarial attacks in practice. We extensively evaluate both our attack and defense methods. Results show that our discrete attack is significantly more effective than state-of-the-art whether or not defense mechanisms are in place to aid models in resisting attacks. In addition, our realization of adversarial training improves the robustness of all evaluated models by the widest margin against state-of-the-art adversarial attacks as well as our own.

European Defence Planning: Concorde, Franco-British Politico-Military Relations and the Cold War, 1956–68

Cold War tensions between the superpowers marked the years 1956 to 1966, where the United States, Britain and France prioritised European defence against Soviet aggression. Despite being envisaged for civil aviation purposes, the Concorde aircraft was the Franco-British alternative to US proposals concerning the introduction of a supersonic bomber within the Inter-Allied Nuclear Force (IANF) to protect against Soviet attack during the Cold War technological race. This offers a unique case study for the examination of Franco-British bi-lateral partnership in the context of European defence. This article will concentrate on three main themes. The first investigates how Concorde was considered as a viable component for the IANF. Subsequently, the loci of US, British and French policy decisions will be explored with regards to constructing supersonic aircrafts. Lastly, the article considers how foreign policies influenced the shift from a military-use Concorde to a more commercial option. The historiography on Concorde focuses on its commercial impact, and how it affected the Franco-British partnership. Considering Concorde from the defence perspective allows us to analyse the divisions between the US and French grand design ideas – the IANF and Europe puissance – and how they provoked further friction in the Franco-British military relationship.

Privacy-enhanced generative adversarial network with adaptive noise allocation

Generative adversarial networks (GANs) have become hugely popular by virtue of their impressive ability to generate realistic samples. Although GANs alleviate the arduous data-collection problem, they are prone to memorize training samples as a result of their complex model structure. Thus, GANs may not provide sufficient privacy guarantees, and there is a considerable chance of inadvertently divulging data privacy. To alleviate this issue, we design a privacy-enhanced GAN based on differential privacy. We first integrate truncated concentrated differential privacy technique into GAN for mitigating privacy leakage with tighter privacy bound. Then, according to different privacy demands of users in real-world scenarios, we design two adaptive noise allocation strategies, which enable us to dynamically inject noise into gradients at each iteration. Different strategies provide us with an intuitive handle to adopt a suitable strategy and achieve an elegant compromise between privacy and utility in distinct scenarios. Furthermore, we offer rigorous illustrations from the perspective of privacy preservation and privacy defense to demonstrate that our algorithm can fulfill differential privacy guarantees. Extensive experiments on real-world datasets manifest that our algorithm can generate high-quality samples while achieving an excellent trade-off between model performance and privacy guarantees.

Evaluation of GAN-based Models for Phishing URL Classifiers

Phishing attacks by malicious URL/web links are common nowadays. The user data, such as login credentials and credit card numbers can be stolen by their careless clicking on these links. Moreover, this can lead to installation of malware on the target systems to freeze their activities, perform ransomware attack or reveal sensitive information. Recently, GAN-based models have been attractive for anti-phishing URLs. The general motivation is using Generator network (G) to generate fake URL strings and Discriminator network (D) to distinguish the real and the fake URL samples. This is operated in adversarial way between G and D so that the synthesized URL samples by G become more and more similar to the real ones. From the perspective of cybersecurity defense, GAN-based motivation can be exploited for D as a phishing URL detector or classifier. This means after training GAN on both malign and benign URL strings, a strong classifier/detector D can be achieved. From the perspective of cyberattack, the attackers would like to to create fake URLs that are as close to the real ones as possible to perform phishing attacks. This makes them easier to fool users and detectors. In the related proposals, GAN-based models are mainly exploited for anti-phishing URLs. There have been no evaluations specific for GAN-generated fake URLs. The attacker can make use of these URL strings for phishing attacks. In this work, we propose to use TLD (Top-level Domain) and SSIM (Structural Similarity Index Score) scores for evaluation the GAN-synthesized URL strings in terms of the structural similariy with the real ones. The more similar in the structure of the GAN-generated URLs are to the real ones, the more likely they are to fool the classifiers. Different GAN models from basic GAN to others GAN extensions of DCGAN, WGAN, SEQGAN are explored in this work. We show from the intensive experiments that D classifier of basic GAN and DCGAN surpasses other GAN models of WGAN and SegGAN. The effectiveness of the fake URL patterns generated from SeqGAN is the best compared to other GAN models in both structural similarity and the ability in deceiving the phishing URL classifiers of LSTM (Long Short Term Memory) and RF (Random Forest).

Optimal defense strategy for AC/DC hybrid power grid cascading failures based on game theory and deep reinforcement learning

This paper proposes a two-person multi-stage zero-sum game model considering the confrontation between cascading failures and control strategies in an AC/DC hybrid system to solve the blocking problem of DC systems caused by successive failures at the receiving end of an AC/DC system. A game model is established between an attacker (power grid failure) and a defender (dispatch side). From the attacker’s perspective, this study mainly investigates the problem of system line failures caused by AC or DC blockages. From the perspective of dispatch-side defense, the multiple-feed short-circuit ratio constraint method, output adjustment measures of the energy storage system, sensitivity control, and distance third-segment protection adjustment are used as strategies to reduce system losses. Using as many line return data as possible as samples, the deep Q-network (DQN), a deep reinforcement learning algorithm, is used to obtain the Nash equilibrium of the game model. The corresponding optimal dispatch and defense strategies are also obtained while obtaining the optimal sequence of tripping failures for AC/DC hybrid system cascading failures. Using the improved IEEE 39-node system as an example, the simulation results verify the appropriateness of the two-stage dynamic zero-sum game model to schedule online defense strategies and the effectiveness and superiority of the energy storage system participating in defense adjustment.

Security defense decision method based on potential differential game for complex networks

Most defense strategies in complex networks are developed from the defense perspective, overlooking the key attack-defense characteristics in cybersecurity. A defense decision algorithm is ineffective when dealing with dynamic attacking behaviors, and when based on attack-defense analysis, stochastic uniform network models are generally used to model the target network, while most networks are large and complex. Thus, the algorithms and their results do not well suit small-world, scale-free, and high-aggregation networks. In this study, considering the structural characteristics of complex networks and the attack-defense characteristics of cybersecurity, potential differential game theory is integrated with complex networks, and a global optimal defense decision algorithm is proposed according to the overall network defense objective. Based on the evolutionary analysis of network security states, a network attack-defense potential differential game model is constructed. Adversarial analysis is carried out on the overall attack-defense strategy, and a defense decision algorithm is designed based on a saddle point equilibrium strategy. Simulation tests are carried out on small-world and scale-free networks to evaluate the effectiveness of the proposed method by comparing its performance with that of random defense strategies and classic decision algorithms.

Research on Security Defense of Coupled Transportation and Cyber-Physical Power System Based on the Static Bayesian Game

The driving and charging behavior of an increasing number of electric vehicles (EVs) have strengthened the connection between transportation network (TN) and cyber-physical power system (CPPS). Cyber-attacks imposed on the coupled system will cause a big disturbance to the power network (PN), which will further affect the travel behavior of EVs in the TN. To improve the ability of the coupled system to resist attacks, this paper presents the framework of coupled transportation and cyber-physical power system with a defense mechanism. From a defense perspective, considering comprehensive load shedding loss of load buses, an active defense model driven by static Bayesian game theory is built at the information network (IN) level of CPPS, which provides a defense strategy selection method against attacks at a certain moment. Moreover, a charging guidance model for EVs based on dynamic vehicles travel simulation is developed to describe the impact of charging station (CS) outage induced by the unsuccessful defense, and to mitigate disturbance on the TN. Simulation experiments with a modified Sioux Falls traffic network and IEEE 30-bus power grid coupled system verify the effectiveness of the proposed method and model.

Effect Of Special Autonomy Fund And Local Original Revenue To The Percentage Of Poverty In Papua Province In Defense Perspective

Poverty in Papua Province is an important problem faced by the Indonesian government because it involves issues of national security and defense. This quantitative study aims to obtain information about the Special Autonomy Fund, Regional Original Income and its effect on the percentage level of poverty in Papua Province. This study involves data from the Special Autonomy Fund, PAD and the percentage of poverty in Papua Province from 2004 to 2021. The collected data were analyzed using SPSS multiple linear regression statistics. The results of this study inform that local revenue does not affect the percentage of poverty but the Special Autonomy Fund has an effect on the percentage of poverty in Papua Province. In a defense perspective, the poverty level in Papua Province needs special attention because it involves non-military threats that can lead to the threat of conflict and security. Following up on the findings of this study, the Papua Special Autonomy Fund program is reviewed to continue and it is necessary to prepare a Grand Design for the governance of the Papua Special Autonomy implementation. so that it can be right on target and avoid deviations.

The Relationship between Defending the State and National Character in Technological Development for the Millennial Generation During the COVID-19 Pandemic

Background: We know that the whole world is facing the same problem, namely the COVID-19 pandemic, including Indonesia. The Indonesian government has made every effort to reduce the pace of the COVID-19 pandemic by establishing policies and regulations such as implementing health protocols, and others. Covid-19 is a non-natural disaster that affects all aspects of life including the nation's character. The younger generation or those who are known as millennials as a determinant of the nation's character have an important role during the Covid-19 pandemic. The problem at this time is that millennials live in a modern and instant era that shapes them to be free, individualistic, and active in the field of technology. This has caused the millennial generation to start forgetting their love for the Motherland and Defending the Country. Methods: The method used in this research is descriptive qualitative and the human instrument is the researcher. A descriptive qualitative method in the form of analyzing and drawing conclusions using various sources of literature. Results: In times of peace and war, young intellectuals as the national guard in non-military defense have a crucial role as potential agents of change in shaping the character and character of the nation. The serious challenges faced by the younger generation must also be addressed by maintaining a balance between intellectual intelligence and emotional intelligence as well as spiritual intelligence. It is hoped that the balance of these three factors will manifest the behavior of young people who always uphold morals and ethics of honesty and nationality. This ability is a form of defending the country on a fine spectrum that needs to be carried out by young people in times of peace. From the perspective of national defense, it is precisely this role of defending the country in the soft spectrum that will determine the quality of the nation's defense and resilience in the future. The toughness and tenacity and ability of the nation to develop the potential of national strength to become a solid state defense force need to be built on the values of nationalism and defense of the country. From the perspective of national resilience, these three basic elements are prerequisites that must be fostered early, continuously, integrated and sustainable. Intellectual intelligence which is a great potential possessed by young people must be able to be developed in a balanced way with emotional intelligence, moral intelligence, and spiritual intelligence. During the Covid-19 pandemic, it turned out that the millennial generation showed high concern and made good contributions as a form of defending the country to maintain national resilience and support the Indonesian government in preventing and handling unexpected events such as Covid-19. Conclusion: The existence of social media as a form of technological progress can be used to hold fundraising events which will later be given to underprivileged communities affected by Covid-19 and medical personnel who lack PPE (personal protective equipment). With the urgency of Indonesia's current situation, the younger generation is required to care about using technology as best as possible in an effort to defend the country which is carried out to help the government and show love for the motherland, harmonious relations between the government and its people, and awareness of the obligations of the nation and state.