{"id":{"repo_id":"csusb","oai_identifier":"oai:scholarworks.lib.csusb.edu:etd-1397"},"canonical_url":"https://search.dev.ndltd.org/etd/csusb/oai:scholarworks.lib.csusb.edu:etd-1397","repository":{"repo_id":"csusb","name":"CSUniversity San Bernardino","base_url":"https://scholarworks.lib.csusb.edu/do/oai/"},"display":{"title":"PACKET FILTER APPROACH TO DETECT DENIAL OF SERVICE ATTACKS","abstract":"<p>Denial of service attacks (DoS) are a common threat to many online services. These attacks aim to overcome the availability of an online service with massive traffic from multiple sources. By spoofing legitimate users, an attacker floods a target system with a high quantity of packets or connections to crash its network resources, bandwidth, equipment, or servers. Packet filtering methods are the most known way to prevent these attacks via identifying and blocking the spoofed attack from reaching its target. In this project, the extent of the DoS attacks problem and attempts to prevent it are explored. The attacks categories and existing countermeasures based on preventing, detecting, and responding are reviewed. Henceforward, a neural network learning algorithms and statistical analysis are utilized into the designing of our proposed packet filtering system.</p>","abstract_html":"&lt;p&gt;Denial of service attacks (DoS) are a common threat to many online services. These attacks aim to overcome the availability of an online service with massive traffic from multiple sources. By spoofing legitimate users, an attacker floods a target system with a high quantity of packets or connections to crash its network resources, bandwidth, equipment, or servers. Packet filtering methods are the most known way to prevent these attacks via identifying and blocking the spoofed attack from reaching its target. In this project, the extent of the DoS attacks problem and attempts to prevent it are explored. The attacks categories and existing countermeasures based on preventing, detecting, and responding are reviewed. Henceforward, a neural network learning algorithms and statistical analysis are utilized into the designing of our proposed packet filtering system.&lt;/p&gt;","abstract_has_math":false,"creators":["Muharish, Essa Yahya M"],"institution":null,"degree_name":"Master of Science in Computer Science","degree_level":"Project","degree_discipline":"School of Computer Science and Engineering","degree_department":null,"school":null,"contributors":["Wu, Zhengping"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-06-01T07:00:00Z","date_published":"2016-06-01T07:00:00Z","updated_at":"2026-07-24T01:53:00Z","subjects":["Denial-of-service (DoS). Internet Control Message Protocol (ICMP). User Datagram Protocol (UDP). Open Systems Interconnection Layers Attacks (OSI). Self-Organize-Map (SOM). Multilayer perceptron (MLP).","Information Security","OS and Networks","Systems Architecture","Theory and Algorithms"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarworks.lib.csusb.edu/etd/342","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Wu, Zhengping"]},{"key":"dc:creator","label":"Author","values":["Muharish, Essa Yahya M"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2016-05-19T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["School of Computer Science and Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Project"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Computer Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Denial-of-service (DoS). Internet Control Message Protocol (ICMP). User Datagram Protocol (UDP). Open Systems Interconnection Layers Attacks (OSI). Self-Organize-Map (SOM). Multilayer perceptron (MLP).","Information Security","OS and Networks","Systems Architecture","Theory and Algorithms"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarworks.lib.csusb.edu/etd/342"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>Denial of service attacks (DoS) are a common threat to many online services. These attacks aim to overcome the availability of an online service with massive traffic from multiple sources. By spoofing legitimate users, an attacker floods a target system with a high quantity of packets or connections to crash its network resources, bandwidth, equipment, or servers. Packet filtering methods are the most known way to prevent these attacks via identifying and blocking the spoofed attack from reaching its target. In this project, the extent of the DoS attacks problem and attempts to prevent it are explored. The attacks categories and existing countermeasures based on preventing, detecting, and responding are reviewed. Henceforward, a neural network learning algorithms and statistical analysis are utilized into the designing of our proposed packet filtering system.</p>"]},{"key":"dc:title","label":"Title","values":["PACKET FILTER APPROACH TO DETECT DENIAL OF SERVICE ATTACKS"]}]}],"canonical_facts":{"dc:contributor":["Wu, Zhengping"],"dc:creator":["Muharish, Essa Yahya M"],"dc:date.available":["2016-05-19T07:00:00Z"],"dc:description.abstract":["<p>Denial of service attacks (DoS) are a common threat to many online services. These attacks aim to overcome the availability of an online service with massive traffic from multiple sources. By spoofing legitimate users, an attacker floods a target system with a high quantity of packets or connections to crash its network resources, bandwidth, equipment, or servers. Packet filtering methods are the most known way to prevent these attacks via identifying and blocking the spoofed attack from reaching its target. In this project, the extent of the DoS attacks problem and attempts to prevent it are explored. The attacks categories and existing countermeasures based on preventing, detecting, and responding are reviewed. Henceforward, a neural network learning algorithms and statistical analysis are utilized into the designing of our proposed packet filtering system.</p>"],"dc:identifier":["https://scholarworks.lib.csusb.edu/etd/342"],"dc:subject":["Denial-of-service (DoS). Internet Control Message Protocol (ICMP). User Datagram Protocol (UDP). Open Systems Interconnection Layers Attacks (OSI). Self-Organize-Map (SOM). Multilayer perceptron (MLP).","Information Security","OS and Networks","Systems Architecture","Theory and Algorithms"],"dc:title":["PACKET FILTER APPROACH TO DETECT DENIAL OF SERVICE ATTACKS"],"thesis:degree_discipline":["School of Computer Science and Engineering"],"thesis:degree_level":["Project"],"thesis:degree_name":["Master of Science in Computer Science"]},"updated_at":"2026-07-24T01:53:00Z"}