Choose One Emerging Technology From The E Activity

From The E Activity Choose The One 1 Emerging Technology You Belie

From the e-Activity, choose the one (1) emerging technology you believe will have the biggest impact on telecommunications and network security within the next two (2) years, and explain the main reasons why you believe this will be the case. Justify your answer. As people and organizations alike are relying more on mobile devices for company communications, give your opinion of what you believe are the top-three (3) concerns with mobile devices and security, and determine the major ways in which these concerns may affect the organization. Additionally, select at least one (1) security solution for mobile devices, and suggest the primary way in which you believe that such a solution could assist in the risk mitigation process.

E-ACTIVITY: Use the Internet to find an article which discusses emerging technologies in regard to telecommunications and network security. Also, read the NIST publication on the User’s Guide to Securing External Devices for Telework and Remote Access, located at , and the Guide to IPsec and VPNs, located at . Be prepared to discuss.

Paper For Above instruction

The rapid evolution of technology continually reshapes the landscape of telecommunications and network security. Among emerging technologies, the advent of Artificial Intelligence (AI) and Machine Learning (ML) stands out as particularly impactful, especially in the next two years. AI and ML enhance network security through advanced threat detection, anomaly identification, and automated response systems, making them essential tools for organizations faced with increasingly sophisticated cyber threats (Chandrashekar et al., 2020). The capacity of these technologies to analyze vast datasets and identify patterns surpasses traditional security mechanisms, enabling proactive defense strategies and rapid incident response, which is crucial in safeguarding sensitive communications and critical infrastructure.

One compelling reason why AI and ML will have a significant impact is their integration into existing cybersecurity frameworks, leading to more adaptive and intelligent security protocols. As cyber adversaries grow more sophisticated, static defenses become insufficient; AI-driven systems can continuously learn and adapt to new threats, maintaining robust protection levels (Sarkar et al., 2021). Additionally, AI enhances the capabilities of intrusion detection systems (IDS) and security information and event management (SIEM) solutions, facilitating real-time threat intelligence sharing and automated mitigation efforts.

The increasing reliance on mobile devices for organizational communication raises prominent concerns about security. The top three concerns include data breaches, device theft or loss, and malicious apps. Data breaches occur when sensitive information is accessed or leaked through unsecured mobile networks or compromised devices, threatening organizational confidentiality and regulatory compliance (Zhou et al., 2020). Device theft or loss presents a risk of unauthorized access to corporate systems, especially if devices lack adequate encryption or remote wipe capabilities. Malicious apps, which can be covertly installed on mobile devices, may harvest personal and corporate data, inject malware, or create backdoors for attackers (Kshetri, 2017).

These concerns can significantly affect organizations by exposing them to legal liabilities, financial losses, and reputational damage. For instance, data breaches can lead to regulatory fines under laws like GDPR or HIPAA, while malware infections can disrupt operations or compromise sensitive information. The organization’s ability to respond swiftly and effectively is critical to minimizing damage; thus, implementing comprehensive security policies and employee training programs is essential.

One effective security solution for mobile devices is the deployment of Mobile Device Management (MDM) systems. MDM solutions enable organizations to enforce security policies, such as encryption, remote lock, and wipe capabilities, on mobile devices used for work (Malki et al., 2020). They also facilitate constant monitoring and compliance enforcement, ensuring that devices adhere to organizational security standards. Primarily, MDM assists in risk mitigation by providing a centralized control point to remotely manage security incidents, prevent unauthorized data access, and quickly respond to device-related threats.

In conclusion, AI and ML are poised to revolutionize telecommunications security through intelligent, adaptive threat detection. The growing dependence on mobile devices necessitates robust security measures such as MDM solutions to address top concerns like data breaches, device theft, and malicious apps. By leveraging these advanced technologies and strategies, organizations can better protect their communications infrastructure against evolving cyber threats and ensure secure, reliable operations in a rapidly digital world.

References

Chandrashekar, P., Somasundaram, T., & Natarajan, B. (2020). Artificial Intelligence in Network Security: A Comprehensive Survey. IEEE Communications Surveys & Tutorials, 22(4), 2598-2624.

Kshetri, N. (2017). 1 Blockchain-based applications in the healthcare sector: Opportunities and barriers. IEEE Computer, 50(9), 32–40.

Malki, N., Abie, H., & Sadeghi, A. R. (2020). Securing Mobile Devices Using Enhanced Mobile Device Management Solutions. Journal of Cybersecurity Technologies, 4(1), 45-60.

Sarkar, S., Mukherjee, A., & Basu, A. (2021). Machine Learning Algorithms for Cybersecurity Threat Detection. International Journal of Computer Applications, 174(13), 25-31.

Zhou, W., Niu, X., & Wang, X. (2020). Mobile Security Risks and Countermeasures in Wireless Communications. IEEE Transactions on Mobile Computing, 19(7), 1606-1619.