By: Gonipalli Bharath Vel Tech University, Chennai, India International Center for AI and Cyber Security Research and Innovations, Asia University, Taiwan, Gmail: gonipallibharath@gmail.com
Abstract:
Phishing schemes have become the dominant deceptive cyber threat which targets all types of entities from individuals to organizations and large enterprises. Cyber attackers deceive their targets to reveal access credentials and money-related information and private data. This paper presents an extensive classification system of phishing attacks which examines them through their attack vector patterns as well as their technical methods and the platforms they target. The article presents modern phishing technique developments and analyzes prevention techniques to increase overall cybersecurity protection. Individuals together with organizations must establish proactive defense strategies through exploitation of phishing attack classification knowledge and trend information to effectively fight these threats.
Introduction:
Victims fall prey to cyber attackers through phishing cyber-attacks when the attackers use human trust to obtain sensitive information. Phishing attacks became increasingly complex as digital transactions along with online communications expanded because attackers now possess more advanced methods. The following research investigates phishing attack methods together with forthcoming security patterns alongside defensive measures against phishing threats[1].
Taxonomy of Phishing Attacks:
Attack classification divides phishing into multiple frameworks between the attack methods and the attack platforms. The main organizational system uses attack vectors together with techniques and targeted platforms for classification purposes[2]. Cyber actors exploit several methods to launch attacks such as email phishing and spear phishing and whaling as well as vishing and smishing and social media phishing. Email phishing attacks make up the majority of phishing attempts because attackers pretend to be authentic sources to extract secret information from their targets. Spear phishing represents a customized attack method that uses information collection to focus on particular persons[3]. High-profile corporate leaders are the primary targets of the whaling tactic to achieve access to protected company information. Vishing and smishing utilize caller voice connections and mobile text messages to trick users and social media phishing specifically exploits Facebook and Twitter platforms for deceive purposes[4].
The different methods of phishing consist of deceptive phishing and malware-based phishing together with man-in-the-middle (MITM) phishing and clone phishing. Attacks that use deceptive phishing tactics pretend to be trusted organizations in order to trick victims into performing dangerous actions. Phishing attacks using malware as a tool seek to steal information or damage system infrastructure. MITM phishing disrupts communications between users and their actual platforms whereas clone phishing tricks users with slightly altered legitimate messages[5].
Several types of platforms become the primary targets of phishing attacks which consist of banking and financial services alongside e-commerce and cloud services in addition to corporate networks. Official financial institutions serve as the fraudulent target of banking phishing attacks[6]. The attack methods of e-commerce phishing use counterfeit payment gateways to obtain user login details[7]. Phishing attacks against cloud service providers and corporate networks both use false provider identities to obtain unauthorized access to systems along with targeted data acquisition for espionage or ransomware deployment purposes[8].
Emerging Trends in Phishing Attacks:
The methods used by phishers have progressed through multiple developments that include state-of-the-art technological advances and sophisticated techniques. The use of AI to generate artificial reports of phishing attacks represents a developing trend because these authentic-seeming deception messages confuse users. Deepfake phishing has become an emerging threat because cyber criminals use AI-generated voice and video to pretend as real people in order to trick victims into giving away sensitive information[9]. The phishing trend currently includes the use of QR codes known as quishing. Attackers spread dangerous QR codes which send users to fraudulent websites after scanning as well as starting the process of malware installation. Supply chain phishing refers to a rising threat in which cyber attackers exploit vendors and partners of businesses to penetrate secure systems by compromising their supply chains. Multiple stages of phishing attacks now exist because hackers establish trust over sequential interactions before conducting their ultimate assault which makes it harder to identify threats during the process[10].
Mitigation Strategies:
The prevention of phishing attacks needs three comprehensive security elements consisting of user education as well as technological safeguards and sector wide policies. Users need proper education and training as a fundamental element for fighting against phishing attacks effectively. Regular organization-initiated educational campaigns must create employee understanding of phishing schemes and protection methods for avoiding unpredictable links and receiving emails. The combination of multiple authentication types through MFA serves as an effective protection method which makes users prove their identity various times before entry access becomes possible therefore minimizing the possibility of stolen credentials. Anti-phishing tools in combination with email filtering systems lower the number of phishing attempts people receive. Phishing emails can be detected and blocked using advanced solutions built with artificial intelligence and machine learning capabilities through behavioral pattern analysis. The security measures of endpoint defense together with firewalls and intrusion detection systems and secure web gateways protect system environments from malware-based phishing attempts. Through zero-trust security organizations verify users and devices at every point during their attempts to access critical business information. Organizations need to create robust cybersecurity rules together with emergency action protocols that reduce the outcome damage when phishing attempts succeed. Organizations must maintain their software as well as security patch updates because this practice prevents attackers from exploiting system weaknesses.
Conclusion:
Phishing attacks stay as a critical cybersecurity risk which continues developing new methods to escape established security protocols. Better organizational and individual defenses develop through knowledge of phishing classification systems together with current phishing trends. User education and MFA implementation together with email filtering and endpoint security produce strong risk reduction outcomes. A combination of AI-based detection technologies together with a zero-trust security model establishes a further protective mechanism. Prolonged developments in cyber security threats demand ongoing awareness combined with constant awareness about possible threats. Secure organizations must adopt both security solutions at advanced levels together with the establishment of security-conscious company culture to protect sensitive data securely.
References:
- R. Alabdan, “Phishing Attacks Survey: Types, Vectors, and Technical Approaches,” Future Internet, vol. 12, no. 10, Art. no. 10, Oct. 2020, doi: 10.3390/fi12100168.
- Z. Alkhalil, C. Hewage, L. Nawaf, and I. Khan, “Phishing Attacks: A Recent Comprehensive Study and a New Anatomy,” Front. Comput. Sci., vol. 3, Mar. 2021, doi: 10.3389/fcomp.2021.563060.
- D. D. Caputo, S. L. Pfleeger, J. D. Freeman, and M. E. Johnson, “Going Spear Phishing: Exploring Embedded Training and Awareness,” IEEE Secur. Priv., vol. 12, no. 1, pp. 28–38, Jan. 2014, doi: 10.1109/MSP.2013.106.
- E. O. Yeboah-Boateng and P. M. Amanor, “Phishing, SMiShing & Vishing: An Assessment of Threats against Mobile Devices,” vol. 5, no. 4, 2014.
- M. Conti, N. Dragoni, and V. Lesyk, “A Survey of Man In The Middle Attacks,” IEEE Commun. Surv. Tutor., vol. 18, no. 3, pp. 2027–2051, 2016, doi: 10.1109/COMST.2016.2548426.
- R. Alabdan, “Phishing Attacks Survey: Types, Vectors, and Technical Approaches,” Future Internet, vol. 12, no. 10, Art. no. 10, Oct. 2020, doi: 10.3390/fi12100168.
- sangeetha. J. Pon, S. S. Ramya, Antony. V. Christal, and k Mythili, “Secured payment gateway for authorizing E-commerce websites and transactions using Machine Learning Algorithm,” in 2020 International Conference on Computer Communication and Informatics (ICCCI), Jan. 2020, pp. 1–5. doi: 10.1109/ICCCI48352.2020.9104140.
- “A survey on security challenges in cloud computing: issues, threats, and solutions | The Journal of Supercomputing.” Accessed: Feb. 26, 2025. [Online]. Available: https://link.springer.com/article/10.1007/s11227-020-03213-1
- J. Bateman, “Deepfakes and Synthetic Media in the Financial System: Assessing Threat Scenarios”.
- G. A. Amoah and H.-A. J.B., “QR Code Security: Mitigating the Issue of Quishing (QR Code Phishing),” Int. J. Comput. Appl., vol. 184, no. 33, pp. 34–39, Oct. 2022, doi: 10.5120/ijca2022922425.
- Gupta, B. B., Joshi, R. C., & Misra, M. (2009). Defending against distributed denial of service attacks: issues and challenges. Information Security Journal: A Global Perspective, 18(5), 224-247.
- Dahiya, A., & Gupta, B. B. (2021). A reputation score policy and Bayesian game theory based incentivized mechanism for DDoS attacks mitigation and cyber defense. Future Generation Computer Systems, 117, 193-204.
- Manasrah, A. M., Aldomi, A. A., & Gupta, B. B. (2019). An optimized service broker routing policy based on differential evolution algorithm in fog/cloud environment. Cluster Computing, 22, 1639-1653.
- Navaneeth J. (2024) A Beginners Guide to Using Machine Learning for Phishing Detection, Insights2Techifo, pp.1
Cite As
Bharath G. (2025) A Taxonomy of Phishing Attacks: Classification, Trends, and Mitigation Strategies, Insights2Techinfo, pp.1