TCP-SYN Flooding Attack in Wireless Networks

This paper concerns the TCP (Transmission Control Protocol) vulnerabilities which gives space for a DoS (Denial of Service) attacks called TCP-SYN flooding which is well-known to the community for several years. The paper shows this attack in wireless as well as wired networks using perl synflood script, Wireshark network analyzer server, Windows 2008 server, and OPNET simulation environment. Using these tools an effects of this attack are shown. Finally, some effective practical mitigation techniques against SYN flooding attack for Linux and Windows systems are explained

Real-time cross-layer design for large-scale flood detection and attack trace-back mechanism in IEEE 802.11 wireless mesh networks

IEEE 802.11 WMN is an emerging next generation low-cost multi-hop wireless broadband provisioning technology. It has the capability of integrating wired and wireless networks such as LANs, IEEE 802.11 WLANs, IEEE 802.16 WMANs, and sensor networks. This kind of integration: large-scale coverage, decentralised and multi-hop architecture, multi-radios, multi-channel assignments, ad hoc connectivity support the maximum freedom of users to join or leave the network from anywhere and at anytime has made the situation far more complex. As a result broadband resources are exposed to various kinds of security attacks, particularly DoS attacks

Analysis of the SYN Flood DoS Attack

The paper analyzes systems vulnerability targeted by TCP (Transmission Control Protocol) segments when SYN flag is ON, which gives space for a DoS (Denial of Service) attack called SYN flooding attack or more often referred as a SYN flood attack. The effects of this type of attack are analyzed and presented in OPNET simulation environment. Furthermore, the paper presents two anomaly detection algorithms as an effective mechanism against this type of attack. Finally, practical approaches against SYN flood attack for Linux and Windows environment are shown

Preventing DDoS using Bloom Filter: A Survey

Distributed Denial-of-Service (DDoS) is a menace for service provider and prominent issue in network security. Defeating or defending the DDoS is a prime challenge. DDoS make a service unavailable for a certain time. This phenomenon harms the service providers, and hence, loss of business revenue. Therefore, DDoS is a grand challenge to defeat. There are numerous mechanism to defend DDoS, however, this paper surveys the deployment of Bloom Filter in defending a DDoS attack. The Bloom Filter is a probabilistic data structure for membership query that returns either true or false. Bloom Filter uses tiny memory to store information of large data. Therefore, packet information is stored in Bloom Filter to defend and defeat DDoS. This paper presents a survey on DDoS defending technique using Bloom Filter.Comment: 9 pages, 1 figure. This article is accepted for publication in EAI Endorsed Transactions on Scalable Information System

Defense Against Distributed Denial of Service Attacks in Computer Networks

Tohoku University亀山充隆課

DDoS-Capable IoT Malwares: comparative analysis and Mirai Investigation

The Internet of Things (IoT) revolution has not only carried the astonishing promise to interconnect a whole generation of traditionally “dumb” devices, but also brought to the Internet the menace of billions of badly protected and easily hackable objects. Not surprisingly, this sudden flooding of fresh and insecure devices fueled older threats, such as Distributed Denial of Service (DDoS) attacks. In this paper, we first propose an updated and comprehensive taxonomy of DDoS attacks, together with a number of examples on how this classification maps to real-world attacks. Then, we outline the current situation of DDoS-enabled malwares in IoT networks, highlighting how recent data support our concerns about the growing in popularity of these malwares. Finally, we give a detailed analysis of the general framework and the operating principles of Mirai, the most disruptive DDoS-capable IoT malware seen so far

Efficient trapdoor-based client puzzle system against DoS attacks

Denial of service (DoS) and distributed denial of service (DDoS) are serious threats to computer networks. DoS and DDoS attacks aim to shut down a target server by depleting its resources and rendering it incapable of offering stable and integrated service to legitimate clients. Preventing DoS and DDoS attacks is a difficult task. A promising countermeasure against DoS attacks is the Client Puzzle method, which nevertheless faces a number of challenges, such as the complexity of puzzle construction and solution verification. Our research focuses on exploring novel puzzle constructions to satisfy the high demands of DoS defence in practice. In this thesis, we first identify the underlying weaknesses of existing client puzzles. To mitigate these vulnerabilities, we recommend the necessary requirements for good client puzzles. Based on this, we propose a new model for puzzle distribution, called the Trapdoor-based Client Puzzle System (TCPS). Two specific schemes are presented to construct puzzles within TCPS. We depict these two schemes, where each trapdoor algorithm is applied respectively. Both schemes have two distinct features: the computational overheads are low, and the difficulty level of puzzles is measurable. Moreover, both puzzle schemes are provably secure under traditional hard problems in mathematics. Our contribution to client puzzle defence against DoS attacks can be summarised as follows: * Identify the shortcomings of existing client puzzles. * Recommend the requirements of good client puzzles. * Formally define the Trapdoor-based Client Puzzle System, along with strict security conditions. * Propose a client puzzle scheme whose security is based on the RSA Assumption. Effectiveness and security are analysed and proven. * Propose a second client puzzle scheme whose security is based on the Discrete Logarithm Problem (DLP). Similarly, effectiveness and security are also analysed. * Provide a possible configuration for system parameters. * Discuss further possible attacks and their solutions. As our research is carried out in DoS attack scenarios, we also introduce this technical background before our achievements are presented

Flow-oriented anomaly-based detection of denial of service attacks with flow-control-assisted mitigation

Flooding-based distributed denial-of-service (DDoS) attacks present a serious and major threat to the targeted enterprises and hosts. Current protection technologies are still largely inadequate in mitigating such attacks, especially if they are large-scale. In this doctoral dissertation, the Computer Network Management and Control System (CNMCS) is proposed and investigated; it consists of the Flow-based Network Intrusion Detection System (FNIDS), the Flow-based Congestion Control (FCC) System, and the Server Bandwidth Management System (SBMS). These components form a composite defense system intended to protect against DDoS flooding attacks. The system as a whole adopts a flow-oriented and anomaly-based approach to the detection of these attacks, as well as a control-theoretic approach to adjust the flow rate of every link to sustain the high priority flow-rates at their desired level. The results showed that the misclassification rates of FNIDS are low, less than 0.1%, for the investigated DDOS attacks, while the fine-grained service differentiation and resource isolation provided within the FCC comprise a novel and powerful built-in protection mechanism that helps mitigate DDoS attacks