Cybersecurity Measures for Logistics Industry

Sindiramutty, Siva Raja; Jhanjhi, Noor Zaman; Tan, Chong Eng; Khan, Navid Ali; Shah, Bhavin; Manchuri, Amaranadha Reddy

doi:10.4018/979-8-3693-3816-2.ch001

Advances in Information Security, Privacy, and Ethics

2024

DOI: 10.4018/979-8-3693-3816-2.ch001

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Cybersecurity Measures for Logistics Industry

Siva Raja Sindiramutty,

Noor Zaman Jhanjhi,

Chong Eng Tan

et al.

Abstract: The logistics sector plays a crucial role in the worldwide economy by facilitating the efficient and punctual transportation of commodities and services. Nevertheless, the growing reliance on technological and digital infrastructure has highlighted the significance of implementing resilient cybersecurity protocols within the logistics industry. The occurrence of cybersecurity threats within the logistics industry may result in notable ramifications such as financial losses, impairment of reputation, and distur… Show more

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Cited by 6 publications

References 89 publications

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Addressing Issues and Challenges Using AI in Pharmacy

Siraj,

Shoaib

et al. 2024

Advances in Medical Technologies and Clinical Practice

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The complications and difficulties relating to the application of AI in pharmacy events are systematically scrutinized in this chapter. AI technologies have momentous potential to aid in pharmacy and healthcare settings as they advance. However, numerous challenges must be overcome before AI may be successfully executed in pharmacies. Integration, data security and privacy, regulatory compliance, ethical issues, user acceptability and training, clinical efficacy, and validation are just a few of the major problems covered in this chapter. Every impediment is thoroughly inspected, offering valuable perceptions of the particulars related to the integration of AI in pharmaceutical settings. The chapter provides a nuanced standpoint that can guide strategic decision-making in the ever-changing geography of AI integration in apothecaries by bridging the gap between academic knowledge and practical factors.

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Addressing Issues and Challenges Using AI in Pharmacy

Siraj,

Shoaib

et al. 2024

Advances in Medical Technologies and Clinical Practice

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Generative AI in Network Security and Intrusion Detection

Sindiramutty,

Prabagaran,

Jhanjhi

et al. 2024

Advances in Information Security, Privacy, and Ethics

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Protecting virtual assets from cyber threats is essential as we live in a digitally advanced world. Providing a responsible emphasis on proper network security and intrusion detection is imperative. On the other hand, traditional strategies need a supportive tool to adapt to the transforming threat space. New generative AI techniques like generative adversarial networks (GANs) and variational autoencoders (VAEs) are the mainstream technologies required to meet the gap. This chapter deals with how these models can enhance network security by inspecting the network traffic for anomalies and malicious behaviors detected through unsupervised learning, which considers strange or emerging phenomena. This survey features innovations in fault detection, behavior control, deep packet inspection, traffic classification, and examples of real-world intrusions detected by GAN-based systems. Furthermore, the chapter focuses on the challenges of adversarial attacks on models that require the development of solid defense mechanisms, such as generative adversarial networks. Ethics becomes the following matter on our list of discussions, given that privacy transparency and accountability are to be observed when working with generative AI technologies in network security. Finally, the authors examine trends that determine how cyber-attacks are dealt with comprehensively.

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Future Trends and Challenges in Cybersecurity and Generative AI

Khan,

Jhanjhi,

Hamid

et al. 2024

Advances in Information Security, Privacy, and Ethics

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The chapter presents a comprehensive exploration of the changing dynamics at the intersection between the rapidly growing landscape of the interconnectivity of various devices—the internet of things—and the innovations piloted by advancements in generative artificial intelligence. In the following background-focused analysis, the significance of the enactment of new levels of security details in this fast-growing and virulently expansive landscape is emphasized, with generative AI ultimately serving as the highlight. The conversation consequently shifts to threats. This includes a detailed depiction of new cybersecurity threats rooted in advancements in AI, featuring AI malicious actors and incidents, such as the increasingly popular phenomenon of ransomware-as-a-service as mirror illustrations of the dynamic and multifaceted character of these threats. The class further proceeds to more in-depth detail about the most contemporary generative AI platforms such as generative adversarial networks, variational autoencoders, and reinforcement learning—all relevant in identifying emerging solutions to advance strategies in cybersecurity. The conversation simultaneously conducts an opportunity and threat analysis of the merger between these platforms and cybersecurity with regard to ethics, regulations, and overall adversarial touchpoints and tactics. The chapter concludes with a call for unity in discourse and action between the relevant industry, academia, and government stakeholders as a summary of the essential cross-disciplinary aspect that must drive the narrative in confronting and overcoming the threats to and from generative AI research. Having presented the narrative structure, this chapter has allowed a comprehensive coverage of the major issues and opportunities at the heart of the cybersecurity-generative AI combination. Additionally, it has provided a forum to call for collaborative and fortified efforts regarding the securing and defending of the uncertainties that the rapidly changing and more unpredictable digital landscape has in store for the world.

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Cybersecurity Measures for Logistics Industry

Cited by 6 publications

References 89 publications

Addressing Issues and Challenges Using AI in Pharmacy

Addressing Issues and Challenges Using AI in Pharmacy

Generative AI in Network Security and Intrusion Detection

Future Trends and Challenges in Cybersecurity and Generative AI

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