A defense against address spoofing using active networks

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (p. 45-46).by Van C. Van.M.Eng

A Defense Framework Against Denial-of-Service in Computer Networks

Denial-of-Service (DoS) is a computer security problem that poses a serious challenge totrustworthiness of services deployed over computer networks. The aim of DoS attacks isto make services unavailable to legitimate users, and current network architectures alloweasy-to-launch, hard-to-stop DoS attacks. Particularly challenging are the service-level DoSattacks, whereby the victim service is flooded with legitimate-like requests, and the jammingattack, in which wireless communication is blocked by malicious radio interference. Theseattacks are overwhelming even for massively-resourced services, and effective and efficientdefenses are highly needed. This work contributes a novel defense framework, which I call dodging, against service-level DoS and wireless jamming. Dodging has two components: (1) the careful assignment ofservers to clients to achieve accurate and quick identification of service-level DoS attackersand (2) the continuous and unpredictable-to-attackers reconfiguration of the client-serverassignment and the radio-channel mapping to withstand service-level and jamming DoSattacks. Dodging creates hard-to-evade baits, or traps, and dilutes the attack "fire power".The traps identify the attackers when they violate the mapping function and even when theyattack while correctly following the mapping function. Moreover, dodging keeps attackers"in the dark", trying to follow the unpredictably changing mapping. They may hit a fewtimes but lose "precious" time before they are identified and stopped. Three dodging-based DoS defense algorithms are developed in this work. They are moreresource-efficient than state-of-the-art DoS detection and mitigation techniques. Honeybees combines channel hopping and error-correcting codes to achieve bandwidth-efficientand energy-efficient mitigation of jamming in multi-radio networks. In roaming honeypots, dodging enables the camouflaging of honeypots, or trap machines, as real servers,making it hard for attackers to locate and avoid the traps. Furthermore, shuffling requestsover servers opens up windows of opportunity, during which legitimate requests are serviced.Live baiting, efficiently identifies service-level DoS attackers by employing results fromthe group-testing theory, discovering defective members in a population using the minimumnumber of tests. The cost and benefit of the dodging algorithms are analyzed theoretically,in simulation, and using prototype experiments

Securing the Edges of IoT Networks: a Scalable SIP DDoS Defense Framework with VNF, SDN, and Blockchain

An unintended consequence of the global deployment of IoT devices is that they provide a fertile breeding ground for IoT botnets. An adversary can take advantage of an IoT botnet to launch DDoS attacks against telecommunication services. Due to the magnitude of such an attack, legacy security systems are not able to provide adequate protection. The impact ranges from loss of revenue for businesses to endangering public safety. This risk has prompted academia, government, and industry to reevaluate the existing de- fence model. The current model relies on point solutions and the assumption that adversaries and their attacks are readily identifiable. But adversaries have challenged this assumption, building a botnet from thousands of hijacked IoT devices to launch DDoS attacks. With bot- net DDoS attacks there are no clear boundary where the attacks originate and what defensive measures to use. The research question is: in what ways programmable networks could defend against Session Initiation Protocol (SIP) Distributed Denial-of-Service (DDoS) flooding attacks from IoT botnets? My significant and original contribution to the knowledge is a scalable and collaborative defence framework that secures the edges of IoT networks with Virtual Network Function (VNF), Software-Defined Networking (SDN), and Blockchain technology to prevent, detect, and mitigate SIP DDoS flooding attacks from IoT botnets. Successful experiments were performed using VNF, SDN, and Blockchain. Three kinds of SIP attacks (scan, brute force, and DDoS) were launched against a VNF running on a virtual switch and each was successfully detected and mitigated. The SDN controller gathers threat intelligence from the switch where the attacks originate and installs them as packet filtering rules on all switches in the organisation. With the switches synchronised, the same botnet outbreak is prevented from attacking other parts of the organisation. A distributed application scales this framework further by writing the threat intelligence to a smart contract on the Ethereum Blockchain so that it is available for external organisations. The receiving organisation retrieves the threat intelligence from the smart contract and installs them as packet filtering rules on their switches. In this collaborative framework, attack detection/mitigation efforts by one organisation can be leveraged as attack prevention efforts by other organisations in the community

Security design analysis

EThOS - Electronic Theses Online ServiceGBUnited Kingdo