دانلود کتاب پیامدهای حملات سایبری بر کلان‌داده‌ها و چگونگی کاهش خطر

It has become more important for companies in a variety of industries to be able to gather and analyze massive volumes of data. Big data analytics may provide several advantages to businesses, including enhanced understanding, improved judg-ment, and more streamlined processes [1]. Big data has become a prime target for hackers who want to get into networks and steal sensitive information because of its widespread use, raising major cybersecurity risks [2]. In several decades, computers and the Internet have become more fundamental in modern society. This has dramati-cally increased attacks on essential services, including the financial sector, the power grid, government offices, and hospitals [3]. The Internet presents various dangers, including but not limited to targeted attacks, viruses, spam, abuse of system rights, leakage of classified information, exposed vulnerabilities due to lack of mainte-nance, user indiscretions, and website defacements [4]. The data shows an alarming increase in assaults on these systems and a clear pattern of evolution like these attacks. Although other forms of cybercrime, such as distributed denial of service (DDoS), advanced persistent threat (APT), ransomware, and social engineering attacks, have long been popular, the prevalence of adware, phishing attacks, and Trojans has recently increased. Virvilis reports that there has been an exponential rise in the frequency, severity, and complexity of cyber threats and attacks since 2014 [5]. In the contemporary digitalization era, big data has emerged as a very impor-tant asset for both public and private entities. However, this phenomenon has also garnered the attention of nefarious individuals who want to exploit inherent weak-nesses within these systems. Cyberattacks targeting large-scale datasets might yield significant ramifications, including breaches of data, infringements upon privacy, financial detriments, misappropriation of intellectual property, data manipulation, and vulnerabilities inside crucial infrastructure [6]. To address these threats, it is imperative to implement heightened cybersecurity protocols, provide comprehen-sive staff training, enforce strict access control measures, develop robust disaster recovery plans, ensure adherence to regulatory requirements, and foster effective teamwork. Data breaches are a substantial outcome resulting from cyberattacks targeting large-scale datasets [7]. Gaining unauthorized access to confidential data can result in identity theft, financial detriment, and harm to one’s reputation. The economic ramifications of cyberattacks are substantial since organizations face finan-cial repercussions from the costs associated with addressing breaches, legal expenses, and penalties imposed by regulatory bodies. Company operational disruptions may lead to financial losses and a decline in market trust [8]. Cyberattacks on large data have significant implications, including infringing intellectual property rights. The misappropriation of trade secrets, proprietary algo-rithms, and the unauthorized reproduction of products may enable corporate espi-onage and undermine competitive advantage [9]. Data manipulation is a significant problem due to the potential for hostile actors to disseminate disinformation or false narratives, which may adversely affect public perception, decision-making processes, and electoral outcomes. The potential ramifications of this phenomenon extend to the domains of social trust and stability. The issue of cyberattacks targeting big data raises considerable apprehension over the vulnerability of critical infrastructure. Public safety and security may be compromised when key services, such as elec-tricity grids, transportation networks, and healthcare, are disrupted [10]. To address the potential vulnerabilities associated with assaults on large-scale datasets, organi-zations need to adopt and enforce advanced cybersecurity protocols. This encom-passes sophisticated threat detection systems that use machine learning and artificial intelligence algorithms to promptly detect and address new threats. Regular soft-ware upgrades and effective patch management are important in order to address and minimize vulnerabilities. The use of data encryption is crucial for safeguarding data both while it is stored and when it is being sent [11].