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

Poseidon: Mitigating Interest Flooding DDoS Attacks in Named Data Networking

Content-Centric Networking (CCN) is an emerging networking paradigm being considered as a possible replacement for the current IP-based host-centric Internet infrastructure. In CCN, named content becomes a first-class entity. CCN focuses on content distribution, which dominates current Internet traffic and is arguably not well served by IP. Named-Data Networking (NDN) is an example of CCN. NDN is also an active research project under the NSF Future Internet Architectures (FIA) program. FIA emphasizes security and privacy from the outset and by design. To be a viable Internet architecture, NDN must be resilient against current and emerging threats. This paper focuses on distributed denial-of-service (DDoS) attacks; in particular we address interest flooding, an attack that exploits key architectural features of NDN. We show that an adversary with limited resources can implement such attack, having a significant impact on network performance. We then introduce Poseidon: a framework for detecting and mitigating interest flooding attacks. Finally, we report on results of extensive simulations assessing proposed countermeasure.Comment: The IEEE Conference on Local Computer Networks (LCN 2013

Flooding attacks to internet threat monitors (ITM): Modeling and counter measures using botnet and honeypots

The Internet Threat Monitoring (ITM),is a globally scoped Internet monitoring system whose goal is to measure, detect, characterize, and track threats such as distribute denial of service(DDoS) attacks and worms. To block the monitoring system in the internet the attackers are targeted the ITM system. In this paper we address flooding attack against ITM system in which the attacker attempt to exhaust the network and ITM's resources, such as network bandwidth, computing power, or operating system data structures by sending the malicious traffic. We propose an information-theoretic frame work that models the flooding attacks using Botnet on ITM. Based on this model we generalize the flooding attacks and propose an effective attack detection using Honeypots

Capability Analysis of Attacks in Wireless Sensor Network

Security is key concern area in WSN as the nature of such networks makes them susceptible to various types of attacks. Driven by this, a lot of research work has been done to classify the attacks and their prevention schemes. In this paper, some well-known attacks are compared based on their severity in WSN. The behavior of black hole, gray hole and flooding attack is simulated and analyzed using ns2. The capability analysis is done on the parameters such aspacket delivery ratio, throughput, drop rate, success rate and density of packet drop, packet forward, packet sent and packet received. The analysiscompares the intensity of the attacks against each other. The simulated result shows a maximum density of packet drop in black hole attack and a minimum density of packet received in flooding attack