@article {10.3844/jcssp.2023.20.56,
article_type = {journal},
title = {Cyber Security Threats and Countermeasures using Machine and Deep Learning Approaches: A Survey},
author = {M, Manjula and Venkatesh, and R., Venugopal K.},
volume = {19},
number = {1},
year = {2023},
month = {Jan},
pages = {20-56},
doi = {10.3844/jcssp.2023.20.56},
url = {https://thescipub.com/abstract/jcssp.2023.20.56},
abstract = {Recent advancements in e-business, e-healthcare, e-governance, and online digital transactions have brought valuable benefits. Unfortunately, it raises severe cyber-attacks. Cyberattacks disrupt normal operations, try to retrieve confidential information and defense secrets, and subvert the nation’s defense systems and Internet-connected devices. Cyber security solutions are required to detect, analyze, defend against threats and protect sensitive data from unauthorized access. This study gives a detailed survey of different cybersecurity attacks, like Denial-of-service attacks, Botnet Evasion Attacks, Malware invasions, Spam and phishing invasion, Spoofing, Domain Generation algorithms, Probing attacks, R2L, and U2R attacks. This research review emphasizes Machine Learning and Deep Learning-based approaches to Cybersecurity problems. This study’s key highlights are the research challenges, cybersecurity issues, cyber security domains, and tools for the Intrusion detection system. Data sets play a vital role in cybersecurity research; hence, Private and Publically available datasets are reviewed in this study. Various performance matrices are discussed in this survey which can be used to evaluate the effectiveness of cybersecurity solutions.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}