Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/8607
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMalkawi, Malek-
dc.contributor.authorOzyer, Tansel-
dc.contributor.authorAlhajj, Reda-
dc.date.accessioned2022-07-30T16:41:54Z-
dc.date.available2022-07-30T16:41:54Z-
dc.date.issued2021-
dc.identifier.citationMalkawi, M., Özyer, T., & Alhajj, R. (2021, November). Automation of active reconnaissance phase: an automated API-based port and vulnerability scanner. In Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 622-629).en_US
dc.identifier.isbn9781450391283-
dc.identifier.issn2473-9928-
dc.identifier.issn2473-991X-
dc.identifier.urihttps://doi.org/10.1145/3487351.3492720-
dc.descriptionMalkawi, Malek/0000-0002-6588-9184en_US
dc.description.abstractThe unprecedented growth in technology has increased the importance of the required information security that is still hard to be reached. Recently, network and web application attacks have occurred frequently, causing confidential data to be stolen by the available vulnerabilities in the systems and the most prominent is in the form of open ports. This causes the CIA (Confidentiality Integrity and Availability) Triad Model to break. Penetration testing is one of the key techniques used in real life to accurately detect the possible threats and potential attacks against the system, and the first step for hackers to conduct attacks is information collection. In this paper, we present a useful schema for the active information-gathering phase that can be used during penetration testing and by system administrators. It will be the first feature of a security engine going to be implemented. The work involves an automated API-based IP and port scanner, service-version enumerator, and vulnerability detection system. This scheme is based on the Network Mapper (Nmap) to collect the information with high accuracy depending on the provided rules in our schema. Besides, the work has been implemented as a RESTful-API server, aiming at easy integration for real-life cases and allowing administrators to scan and secure their networks more quickly and easily. The effectiveness and efficiency of this technique has been proved by the various test cases applied considering different scenarios from the real world. The average time of scanning a server and detecting the vulnerabilities is 2.2 minutes. Regardless of the number of vulnerabilities, the increase in time for each open port is just about 12 seconds.en_US
dc.language.isoenen_US
dc.publisherAssoc Computing Machineryen_US
dc.relation.ispartofIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) -- NOV 08-11, 2021 -- ELECTR NETWORKen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectVulnerability Assessmenten_US
dc.subjectInformation Securityen_US
dc.subjectCyber Reconnaissanceen_US
dc.subjectPort Scanneren_US
dc.subjectNmapen_US
dc.subjectApien_US
dc.subjectSecurity Vulnerabilitiesen_US
dc.subjectPenetration Testingen_US
dc.titleAutomation of Active Reconnaissance Phase: an Automated Api-Based Port and Vulnerability Scanneren_US
dc.typeConference Objecten_US
dc.relation.ispartofseriesProceedings of the IEEE-ACM International Conference on Advances in Social Networks Analysis and Mining-
dc.departmentTOBB University of Economics and Technologyen_US
dc.identifier.startpage622en_US
dc.identifier.endpage629en_US
dc.authoridMalkawi, Malek/0000-0002-6588-9184-
dc.identifier.wosWOS:001196170500095-
dc.identifier.scopus2-s2.0-85124417139-
dc.institutionauthorÖzyer, Tansel-
dc.identifier.doi10.1145/3487351.3492720-
dc.authorwosidMalkawi, Malek/IYJ-0040-2023-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityN/A-
dc.identifier.wosqualityN/A-
dc.description.woscitationindexConference Proceedings Citation Index - Science - Conference Proceedings Citation Index - Social Science &amp- Humanities-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeConference Object-
item.grantfulltextnone-
crisitem.author.dept02.1. Department of Artificial Intelligence Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

1
checked on Mar 29, 2025

WEB OF SCIENCETM
Citations

1
checked on Mar 15, 2025

Page view(s)

62
checked on Mar 31, 2025

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.