Guardians of the Digital Realm: Strategies for Defense in Modern Cybersecurity

In the ever-evolving landscape of cybersecurity, understanding both human vulnerabilities and technical defenses is crucial for protecting digital infrastructure. This blog explores two fundamental concepts Ethical Hacking and Social Engineering that reflect opposing sides of the cybersecurity spectrum: one being a proactive safeguard, the other a deceptive threat. Ethical hacking involves legally probing systems to uncover and fix weaknesses before malicious hackers can exploit them, while social engineering manipulates human behavior to bypass security barriers entirely. To support these themes, two academic journal reviews are discussed: one delves into Access Control strategies in cloud-native architectures, and the other analyzes Risk Management through structured decision-making methods. Together, these topics paint a comprehensive picture of modern security practices and their challenges in today's interconnected world.

Ethical Hacking is the authorized practice of deliberately probing computer systems, networks, or applications to identify and fix security vulnerabilities before malicious hackers can exploit them.

Section 1: Ethical Hacking – Breaking in to Build Stronger Walls

Ethical Hacking is the authorized practice of deliberately probing computer systems, networks, or applications to identify and fix security vulnerabilities before malicious hackers can exploit them. It is a key component of modern cybersecurity strategies and is typically performed by trained professionals known as ethical hackers or white hat hackers. Ethical hacking can involve internal or external penetrations testing as well as web application testing.

• External testing involves testing for vulnerabilities as an outsider trying to get into an organization or system. This type of testing looks for issues with firewalls potentially being misconfigured, problems with third-party applications, or weaknesses in email servers.
• Internal testing looks for possible issues within an organization, often related to human error and employees' use of the system. Human error is the most common cybersecurity threat to organizations and businesses, this can be due to weak passwords, vulnerability to phishing and social engineering scams, and failure to update systems and devices. Ethical hackers doing internal testing will look for ways to bait employees and search for potential security vulnerabilities.
• Web application testing is a type of ethical hacking that looks for problems with websites and applications. This can ferret out potential bugs or security breaches with applications and websites before they are deployed or go live.

Unlike malicious hackers, ethical hackers follow legal and contractual boundaries. Ethical hacking involves reporting these potential issues back to the organization offering solutions for fixing the problems and plugging possible leaks and weak spots. On the other hand, malicious hacking is used for illegitimate and illegal purposes, often to commit a crime. A malicious hacker will gain unauthorized access to a system, computer, network, or application, and use this access to steal credentials, sensitive information, crash systems, insert malware, or otherwise wreak havoc, always working for financial or personal gain. Ethical Hackers often have certifications such as CompTIA PenTest+, Certified Ethical Hacker (CEH), or Offensive Security Certified Professional (OSCP), which validate their knowledge of attack techniques and ethical standards. Ethical Hacking have some key goals to maintain the organizations infrastructure:

• Identify security flaws before criminals do.
• Test how well a system withstands real-world cyberattacks.
• Strengthen organization defense mechanisms.
• Ensure compliance with industry regulations (e.g, HIPPA, PCI-DSS).

By simulating real-world attacks, ethical hackers ensure that systems are secure, data remains protected, and risks are minimized. This proactive approach plays a crucial role in strengthening cybersecurity and preventing potential breaches. Some examples of the day-by-day and techniques used by ethical hackers would be:

• Vulnerability Assessment: A comprehensive scan of a network, system, or application to identify weakness that hackers could exploit using automated tools such as Nessus, OpenVas, or Qualys to scan for known vulnerabilities, outdated software or misconfigurations.
• Social Engineering: It involves ethical hackers manipulating employees into revealing confidential information or performing actions that compromise the organization's security. Ethical hackers tests the organization’s human factor by simulating phishing, pretexting, baiting, or tailgating attacks.
• Ransomware Simulation: It involves ethical hackers simulating a ransomware attack to test an organization’s preparedness for such threats. They may introduce a controlled ransomware strain into the network without causing actual damage, to see if the organization can detect and mitigate the ransomware attack.
• Password Cracking: Ethical hackers could use password-cracking tools like John the Ripper, Hashcat, or Hydra to test the strength of passwords within an organization. They may attempt to crack weak or reused passwords to demonstrate the risks of poor passwords policies.

Social Engineering is a psychological manipulation technique used to deceive individuals into revealing confidential or personal information.

Section 2: Social Engineering – When the Weakest Link is Human

Social Engineering is a psychological manipulation technique used to deceive individuals into revealing confidential or personal information. Instead of directly attacking a system through code or software, attackers exploit human behavior, such as trust, fear, curiosity, or urgency. Social engineering is often considered one of the most dangerous forms of attack because it bypasses even the most advanced technical defenses by targeting the human factor. Some examples of the most common types of social engineering attacks are:

• Phishing: Fake emails or websites designed to steal credential or data.
• Pretexting: Creating a false scenario to extract information (e.g., pretending to be tech support)
• Baiting: Offering something attractive (like a free USB drive) loaded with malware.
• Tailgating: Following someone into a secure area without authorization.
• Scareware: Malware used to frighten users into acting. This deceptive malware uses alarming warnings that report fake malware infections or claim one of your accounts has been compromised to push the user to buy fake software or divulgate private information like credentials.

The lines between social engineering and phishing are blurred because they usually go hand in hand in a sophisticated attack. Social engineering usually involves masquerading as a legitimate employee (e.g., CEO, CFO, CISO, CIO) or tricking an employee into thinking that the attacker is a legitimate customer to get the employee to provide the attacker with sensitive information or change account features. Regardless of the attacker’s goals, there are some clear signs that the communication being made is an attempt of a social engineering attack. One primary component in social engineering is playing on a targeted person fears and emotions. The attacker doesn't want the targeted person digesting and contemplating the request, so social engineering involves using fear and a sense of urgency. A few common traits in all social engineering attacks are:

• Sense of Urgency or Pressure: Attackers create a false sense of emergency to get victims to act quickly without thinking.
• Impersonation of Authority or Trust: The attacker pretends to be someone trusted; a boss, IT administrator, police officer, or even a well-known company.
• Preying on Emotions: Social engineers may manipulate emotions like fear, curiosity, greed or sympathy to gain credentials or money from the victim.
• Use of Spoofed or Fake Contact Information: Attackers can use fake caller IDs, spoofed emails, or websites that look nearly identical to real ones that may lead to a phishing site or malicious download.

Social engineering attacks are difficult to prevent because they rely on human psychology rather than technological ways. The attack surface also is significant, because in a larger organization it takes just one employee’s mistake to compromise the integrity of the entire enterprise network. However, there exist some steps that security experts recommend to mitigate the risks and success of social engineering scams, these steps include:

• Security Awareness Training: Many users don’t know how to identify social engineering attacks, security awareness training combined with data security policies can help employees understand how to protect their sensitive data and how to detect and respond to social engineering attacks in progress.
• Access Control Policies: Secure access control policies and technologies including multi-factor authentication, adaptive authentication and zero trust security approach can limit cybercriminals’ access to sensitive information and assets on the corporate network.
• Cybersecurity technologies: Spam filters and secure email gateways can prevent some phishing attacks from reaching employees in the first place. Firewalls and antivirus software can mitigate the extent of any damage done by attackers who gain access to the network. Keeping operating systems updated with the latest patches can also close some vulnerabilities that attackers exploit through social engineering.

While ethical hacking and social engineering highlight the practical frontlines of cybersecurity, academic research continues to explore more specialized areas that support secure system design and decision-making. To deepen our understanding of these foundational pillars, here are two insightful journal papers, one focusing on Access Control in cloud-native environments, and the other on Risk Management using structured decision-making models. These studies expand our view beyond tactics and threats, offering strategic frameworks that enhance long-term security planning.

Paper Reviews

Access Control Design Practice and Solutions in Cloud-Native Architecture: A Systematic Mapping Study

By Shahidur Rahaman, Sadia Nasrin Tisha, Eunjee Song, and Tomas Cerny

This paper is a thorough and well-structured systematic mapping study that provides a strong foundation for understanding access control mechanisms in cloud-native systems. The authors have done commendable work collecting and synthesizing information from a wide range of scholarly sources. Their methodical inclusion and exclusion criteria, alongside their categorization of access control strategies, authentication/authorization patterns, and tools, reflect a high level of academic rigor. I believe the research is sufficiently comprehensive, with a clear explanation of its objectives and detailed answers to their research questions. As a reader, I found their use of figures, tables, and diagrams helpful in understanding the breadth and scope of the study.

That said, while the paper excels at classifying existing approaches, some areas could have been enhanced with more in-depth technical analysis or real-world case studies. For instance, while the authors identify popular mechanisms like Role-Based Access Control (RBAC), JSON Web Tokens (JWT), and mTLS, they don’t delve deeply into implementation challenges or performance comparisons across cloud providers. Including metrics on the effectiveness or performance trade-offs of each access control model in real deployment environments would strengthen their argumentation and practical relevance.

I appreciated the authors’ discussion of the challenges and gaps in current practices, such as lack of standardization, difficulties in applying granular access controls, and the complexities of securing multi-tenant architectures. The future research directions suggested zero-trust security, context-aware access, and AI-powered decision-making resonated with modern industry trends and hint at useful areas for future exploration. A follow-up article could significantly benefit the field by presenting empirical studies or experimental frameworks that test the proposed patterns and mechanisms in actual microservices environments.

Overall, I agree with the article's conclusions and found that it reinforced my understanding of the complexities in cloud-native security design. It didn't drastically change my opinions but did deepen them by offering a clearer structure of the current landscape and highlighting gaps that I hadn't previously considered. It stands as a valuable resource for both researchers and practitioners aiming to build secure, scalable, and robust microservices-based systems.

Information Security Management: ANP Based Approach for Risk Analysis and Decision Making

By H. Brožová, L. Šup, J. Rydval1, M. Sadok, P. Bednar

This paper presents a strong and methodologically detailed approach to managing information security risks using the Analytic Network Process (ANP) in combination with semantic networks. I believe the authors have done sufficient research, offering a clear explanation of the theoretical underpinnings of the ANP model and its relevance to information systems security. The integration of multiple perspectives (from end users, network administrators, and security experts) adds practical weight to their argument, and the case study involving a forestry company makes the work more relatable and grounded in the real world.

That said, the paper would benefit from a deeper dive into comparative analysis. While ANP is presented as a superior method, the authors could have enhanced the argument by comparing its effectiveness directly with other decision-making or risk evaluation frameworks, such as AHP or fuzzy logic models, in similar scenarios. Additionally, more visual examples of how semantic networks are practically designed and processed within ANP software (e.g., SuperDecision) would have improved accessibility for readers unfamiliar with these tools.

A valuable follow-up article might include a broader empirical study across multiple industries, showcasing how ANP performs in different IT environments with varying security complexities. It could also expand on stakeholder collaboration and the challenges of achieving consistent judgments during pairwise comparisons, perhaps exploring automation or AI-enhanced decision aids. This would make the model more applicable to dynamic, modern threat landscapes where decision-making needs to be rapid and precise.

Overall, I agree with the article’s central argument: that ANP is a powerful tool for understanding the interdependencies of information security risks. It didn’t change my views on risk management, but it certainly deepened my appreciation for structured, multi-criteria approaches that account for both quantitative and qualitative perspectives. The focus on stakeholder-specific insight adds value, showing that effective security decisions are not just technical, they're organizational.

Conclusion

Cybersecurity isn't just about firewalls and code, it’s about understanding how systems fail, whether through software vulnerabilities or human error. Ethical hacking provides a proactive shield, exposing flaws before attackers can exploit them. Meanwhile, social engineering reminds us that no system is safe if its users are untrained or unaware. Together with structured access control and robust risk management frameworks, these concepts form a multidimensional approach to cybersecurity. As threats evolve, so must our strategies blending psychology, technology, and decision-making to defend the digital frontier.

References

1. A. Basta, N. Basta, and M. B. P. Cisa Cissp, Computer security and penetration testing. Cengage Learning, 2013.
2. H. Brožová, L. Šup, J. Rydval, M. Sadok, and P. Bednar, “Information Security Management: ANP based approach for risk analysis and decision making,” Agris On-line Papers in Economics and Informatics, vol. VIII, no. 1, pp. 13–23, Mar. 2016, doi: 10.7160/aol.2016.080102.
3. M. Chapple, J. M. Stewart, and D. Gibson, ISC2 CISSP Certified Information Systems Security Professional Official Study Guide. Sybex, 2024.
4. M. S. Rahaman, S. N. Tisha, E. Song, and T. Cerny, “Access Control design practice and Solutions in Cloud-Native Architecture: A Systematic Mapping study,” Sensors, vol. 23, no. 7, p. 3413, Mar. 2023, doi: 10.3390/s23073413.