Open Access Open Access  Restricted Access Subscription Access

Strategies to Avoid Illegal Data Access

Muhammad Mubeen, Muhammad Arslan, Giri Anandhi


For companies of all sizes, data security is a top priority. The chance of unauthorized data access increases as technology develops. To prevent unwanted access to their data, businesses must be proactive. This study examines technology solutions, personnel training, and policy enforcement as methods to prevent unauthorized data access. Data may be protected from illegal access using technological solutions like firewalls, intrusion detection systems, and encryption. Intrusion detection systems notify the administrator when suspicious behavior is found, while firewalls serve as a protective border between the internal network and the internet. Even if data is intercepted, encryption makes sure it is safe. Another effective method of avoiding unauthorized data access is employee education. Employees must be taught how to spot hazards like phishing emails and shady websites and react to them. Additionally, they should be taught the right way to utilize passwords and other security precautions. To secure data, organizations should create and implement policies. Policies should set out appropriate data and system use guidelines and provide repercussions for noncompliance. Policies should be evaluated regularly to ensure that they are current and useful. Businesses may prevent unwanted access to their data by installing technology solutions, training staff, and enforcing regulations. Organizations may reduce data breach risk and maintain regulatory compliance by taking these precautions. However, several cyber threats that corporations currently face are examined in this study. It outlines several threat categories, including ransomware, phishing, malware, and data breaches, and how they might affect enterprises. It also looks at methods businesses can employ to reduce the danger posed by these threats, including setting up firewalls and antivirus software, attending frequent security awareness training sessions, and implementing robust authentication systems.


Software, data, encrypt data, malware threat, SIEM, network traffic, multifactor authentication

Full Text:



Aparajit S, Shah R, Chopdekar R, Patil R. Data Protection: The Cloud Security Perspective. In 2022 IEEE 3rd International Conference for Emerging Technology (INCET). 2022 May 27; 1–5.

Ibrokhimov S, Hui KL, Al-Absi AA, Sain M. Multi-factor authentication in cyber physical system: A state of art survey. In 2019 IEEE 21st international conference on advanced communication technology (ICACT). 2019 Feb 17; 279–284.

Isaak J, Hanna MJ. User data privacy: Facebook, Cambridge Analytica, and privacy protection. Computer. 2018 Aug 14; 51(8): 56–9.

Lin F, Zhou Y, An X, You I, Choo KK. Fair resource allocation in an intrusion-detection system for edge computing: Ensuring the security of Internet of Things devices. IEEE Consum Electron Mag. 2018 Oct 5; 7(6): 45–50.

Abdulghani HA, Nijdam NA, Collen A, Konstantas D. A study on security and privacy guidelines, countermeasures, threats: IoT data at rest perspective. Symmetry. 2019 Jun 10; 11(6): 774.

El Ghamry M, Halim IT, Bahaa-Eldin AM. Secular: A decentralized blockchain-based data privacy-preserving model training platform. In 2021 IEEE International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC). 2021 May 26; 357–363.

Alkadi O, Moustafa N, Turnbull B, Choo KK. A deep blockchain framework-enabled collaborative intrusion detection for protecting IoT and cloud networks. IEEE Internet Things J. 2020 May 22; 8(12): 9463–72.

Nguyen DC, Pathirana PN, Ding M, Seneviratne A. Blockchain for secure EHRS sharing of mobile cloud-based e-health systems. IEEE Access. 2019 May 17; 7: 66792–806.

Daoud L, Huen H. Performance Study of Software-based Encrypting Data at Rest. Proceedings of 37th International Confer. 2022 Mar 18; 82: 122–30.

Sun P. Security and privacy protection in cloud computing: Discussions and challenges. J Netw Comput Appl. 2020 Jun 15; 160: 102642.

Mavroeidis V, Hohimer R, Casey T, Jesang A. Threat actor type inference and characterization within cyber threat intelligence. In 2021 IEEE 13th International Conference on Cyber Conflict (CyCon). 2021 May 25; 327–352.

Gao Y, Xiaoyong LI, Hao PE, Fang B, Yu P. Hincti: A cyber threat intelligence modeling and identification system based on heterogeneous information network. IEEE Trans Knowl Data Eng. 2020 Apr 20; 34(2): 708–722.

Williams R, Samtani S, Patton M, Chen H. Incremental hacker forum exploit collection and classification for proactive cyber threat intelligence: An exploratory study. In 2018 IEEE International Conference on Intelligence and Security Informatics (ISI). 2018 Nov 9; 94–99.

Abu MS, Selamat SR, Ariffin A, Yusof R. Cyber threat intelligence–issue and challenges. Indones J Electr Eng Comput Sci. 2018 Apr; 10(1): 371–9.

Jothi KR, Pandey N, Beriwal P, Amarajan A. An efficient SQL injection detection system using deep learning. In 2021 IEEE International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). 2021 Mar 17; 442–445.

Dong S, Abbas K, Jain R. A survey on distributed denial of service (DDoS) attacks in SDN and cloud computing environments. IEEE Access. 2019 Jun 12; 7: 80813–28.

Badsha S, Vakilinia I, Sengupta S. Privacy preserving cyber threat information sharing and learning for cyber defense. In 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC). 2019 Jan 7; 0708–0714.


  • There are currently no refbacks.

Copyright (c) 2023 Journal of Communication Engineering & Systems