"The Role of 5G/6G Cellular Network Technologies in Achieving the goals of Sustainable Development"
In order to achieve the global goals of sustainable development, it is necessary to use all available high-tech tools, which to one degree or another will bring the world community closer to the realization of the most ambitious ideas for global well-being. The ICT industry's contribution to achieving sustainable development goals should be noted separately. Cellular networks are one of the key drivers of the development of the ICT industry. They are developing at a very rapid pace and this is evidenced by several studies and the results of the analysis of the subscriber base. The latest generation of mobile radio communication networks today are 5G networks. However, the benefits of 5G are not limited to the ICT sector. The technology represents an open innovation platform that serves a multitude of sustainable use cases – from smart farms to smart factories – by improving automation, increasing productivity, increasing energy efficiency, conserving resources and enhancing resilience to climate change. 5G can also contribute to the decarbonization of the world's largest carbon-emitting sectors, namely energy, manufacturing and transport, by improving data sharing, optimizing systems and increasing operational efficiency, thereby accelerating global efforts to reduce carbon emissions. It can be argued that 5G and future 6G cellular network technologies have significant potential to promote sustainable development. Their high throughput, low latency and high scalability make them key tools for various initiatives to improve the quality of life and preserve the environment. With the help of 5G/6G technologies, it is possible to ensure the efficient use of resources, develop the "Internet of Things" and "smart" systems, increase the availability of education and health services, promote the development of remote work and mobility, and also increase the competitiveness of the economy. Therefore, the role of 5G/6G cellular network technologies in sustainable development cannot be overestimated. Their implementation and use open up new opportunities for creating more efficient, intelligent and ecologically clean cities and countries.
"ML-based quality assessment of PRNG for cryptographic applications"
This study proposes the use of machine learning methods (in particular, hybrid and convolutional neural networks) to improve both accuracy and speed of assessing the quality of the PRNGs even with a limited amount of input data. This provides new opportunities for the use of generators in real-world conditions, where access to large amounts of data may be limited, and guarantees a high level of reliability and security of information systems. The results obtained will be useful for cryptography, LTE/5G/6G cellular networks, UAV-based technologies as well as critical information infrastructure protection.
"The Evolving Role of International Law in Cyberspace"
As cyberspace becomes increasingly central to global interactions, international law faces new and complex challenges. This intervention will explore how existing legal frameworks are being applied to state actions in the digital realm and the emerging norms specific to cyberspace. Special attention will be given to issues such as digital sovereignty, the impact of cyber operations on state sovereignty, and the tension between security concerns and the protection of human rights online. By examining recent developments and key case studies, this presentation will highlight the urgent need for a more cohesive and adaptive international legal framework. The goal is to foster a deeper understanding of how international law can evolve to effectively govern cyberspace, ensuring it remains a secure, open, and stable domain.
"Blackbox Android Malware Detection Using Machine Learning and Evasion Attacks Techniques"
Over the past ten years, researchers have extensively explored the vulnerability of Android malware detectors to adversarial examples through the development of evasion attacks. Nevertheless, the feasibility of these attacks in real-world use case scenarios is debatable. Most of the existing published papers are based on the assumptions that the attackers know the details of the target classifiers used for malware detection. Nevertheless, in reality, malicious actors have limited access to the target classifiers. This proposed talk presents a problem-space adversarial attack designed to effectively evade blackbox Android malware detectors in real-world use case scenarios. The proposed approach constructs a collection of problem-space transformations derived from benign donors that share opcode-level similarity with malware applications through the consideration of an n-gram-based approach. These transformations are then used to present malware instances as legitimate entities through an iterative and incremental manipulation strategy. The proposed presentation will describe a manipulation model that is based on a query-efficient optimization algorithm, which can identify and implement the required sequences of transformations into the malware applications. The model has already been evaluated relative to more than 1,000 malware applications. This demonstrates the effectiveness of the reported approach relative to the generation of real-world adversarial examples in both software and hardware-related scenarios. The experiments that we conducted demonstrate that the proposed model may effectively trick various malware detectors into believing that malware entities are legitimate. More precisely, the proposed model generates evasion rates of 90%–95% relative to data sets like DREBIN, Sec-SVM, ADE-MA, MaMaDroid, and Opcode-SVM. The average number of required computational operations belongs to the range [1..7]. Additionally, it is relevant to note that the proposed adversarial attack preserves its stealthiness against the virus detection core of three popular commercial antivirus softwares. The obtained evasion rate is 87%, which further proves the proposed model’s relevance for real-world use case scenarios.
"Internet Fragmentation as a new challenge for the Unified, Security and Stability of Internet"
The positive process of rapid development of the Internet and Internet technologies is accompanied by certain risks that pose a threat to the unity and security of the global Internet network, its stability and sustainable growth.
"Hidden Dangers: Exploring Rare IoT Attacks"
The Internet of Things (IoT) has transformed connectivity by embedding smart devices into various environments, yet it also presents unique security challenges. Among these, rare IoT attacks targeting hardware vulnerabilities are particularly concerning. This abstract delves into such attacks, focusing on the exploitation of hardware components within IoT systems. IoT devices are frequently targeted through various hardware vulnerabilities, including debugging attacks, where attackers exploit debugging interfaces left enabled on IoT devices, allowing them to extract sensitive information or alter device functionality. These interfaces,
often intended for development purposes, can be misused if not properly secured. One-time programmable (OTP) chips, designed to prevent reprogramming after initial setup, can be bypassed by attackers, potentially altering device behaviour or extracting sensitive data. Bypassing read protection (RDP) levels is another tactic, where attackers employ sophisticated techniques to gain access to critical firmware and data, circumventing protections meant to prevent unauthorised access. Similarly, code read protection (CRP) attacks exploit vulnerabilities to disable or bypass
CRP, allowing attackers to extract and analyse the firmware.
Additional hardware attacks include fault injection attacks, which involve deliberately introducing faults into a device's operation, often by manipulating voltage or clock signals, to cause unintended behaviour or extract sensitive information. Physical layer attacks target the physical transmission medium of IoT devices, potentially intercepting or altering data as it is transmitted. Tamper resistance bypass involves physically manipulating devices to bypass
tamper-resistant features, gaining unauthorised access to the device's internals. Clock glitch attacks introduce glitches in the clock signal, disrupting normal device operations and potentially bypassing security checks. Power analysis attacks monitor the power consumption of a device to extract cryptographic keys or other sensitive information. Electromagnetic attacks use electromagnetic emissions from a device to infer sensitive information or disrupt device operations. Finally, hardware reverse engineering involves analyzing a device's hardware to understand its design and functionality, potentially revealing vulnerabilities that can be exploited. Although rare, hardware exploitation attacks on IoT systems pose significant threats due to their potential to cause widespread disruption and damage. Mitigating these vulnerabilities
necessitates a multi-layered security approach, encompassing robust hardware design and continuous monitoring for anomalies. As IoT technology continues to evolve, understanding and addressing these rare but severe attack vectors is crucial for maintaining secure and reliable IoT ecosystems.
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