Improved Secure Address Resolution Protocol

In this paper, an improved secure address resolution protocol is presented where ARP spoofing attack is prevented. The proposed methodology is a centralised methodology for preventing ARP spoofing attack. In the proposed model there is a central server on a network or subnet which prevents ARP spoofing attack.Comment: 10 pages, 15 figures, paper selected in fifth international conference of communications security and information assurance 201

Computer Network Routing Challenges Associated to Tackle Resolution Protocol

Computer networks are very important in today�s scenario. They have changed the way we do business and the way we live. There are several protocols that help us to establish these networks. The most widely used network protocol is ARP (Address Resolution Protocol) which is used to find the physical address of the node when its internet address is known. In this paper we have discussed the weaknesses of this protocol and have proposed various methods of active detection and prevention of ARP poisoning(spoofing) based Man-in- the-Middle(MitM) attacks on switched Ethernet LAN�s, Denial-of-service (DoS), session hijacking etc. We have implemented tools and defense mechanisms such as central server on a network or subnets, encryption of data traffic etc. that help us to reduce these spoofing attacks

A Survey of Different Dos Attacks on Wireless Network

Wireless technologies like Wireless LAN (WLAN) 802.11 picking up ubiquity in all associations, undertakings and colleges because of its profitability, cost sparing when contrasted with wired system and usability by enabling the system clients to move physically while keeping up an association with the wireless system. Wireless systems are main stream among the Laptop client group today in light of the portability and usability. Individuals working through remote association must know about the surroundings because of the different sorts of assaults made by the interlopers. Remote systems are extremely defenseless against (Denial of Service) DoS attacks. DoS attacks are an endeavor to make a machine or system asset inaccessible to its clients. It can happen in numerous layers of OSI demonstrate and can happen in different frame Network clients can ensure their frameworks with Wi-Fi Protected Access (WPA) security conventions and Wired Equivalent Privacy (WEP), however DoS attack still can't be averted utilizing these conventions. These attacks bring about debasement of the system quality or finish loss of accessibility of the system inside the association. This survey paper makes a review on various kinds of DoS attacks and their countermeasures on the framework systems which depend on the Access Points (AP). The fundamental assaults called Deauthentication and Disassociation Flooding. DoS assaults are considered there avoidance/discovery arrangements. Keywords- Access Points, DoS, Wireless Security, 802.11, Disassociation, Deauthentication, Flooding attack

A survey of intrusion detection techniques in Cloud

Cloud computing provides scalable, virtualized on-demand services to the end users with greater flexibility and lesser infrastructural investment. These services are provided over the Internet using known networking protocols, standards and formats under the supervision of different managements. Existing bugs and vulnerabilities in underlying technologies and legacy protocols tend to open doors for intrusion. This paper, surveys different intrusions affecting availability, confidentiality and integrity of Cloud resources and services. It examines proposals incorporating Intrusion Detection Systems (IDS) in Cloud and discusses various types and techniques of IDS and Intrusion Prevention Systems (IPS), and recommends IDS/IPS positioning in Cloud architecture to achieve desired security in the next generation networks

Physical-model-checking to detect switching-related attacks in power systems

Recent public disclosures on attacks targeting the power industry showed that savvy attackers are now capable of occulting themselves from conventional rule-based network intrusion detection systems (IDS), bringing about serious threats. In order to leverage the work of rule-based IDS, this paper presents an artificially intelligent physical-model-checking intrusion detection framework capable of detecting tampered-with control commands from control centers of power grids. Unlike the work presented in the literature, the work in this paper utilizes artificial intelligence (AI) to learn the load flow characteristics of the power system and benefits from the fast responses of the AI to decode and understand contents of network packets. The output of the AI is processed through an expert system to verify that incoming control commands do not violate the physical system operational constraints and do not put the power system in an insecure state. The proposed content-aware IDS is tested in simulation on a 14-bus IEEE benchmark system. Experimental verification on a small power system, with an IEC 61850 network architecture is also carried out. The results showed the accuracy of the proposed framework in successfully detecting malicious and/or erroneous control commands

AEGIS: Validating Execution Behavior of Controller Applications in Software-Defined Networks

The software-defined network (SDN) controller provides an application programming interface (API) for network applications and controller modules. Malicious applications and network attackers can misuse these APIs to cause outbreaks on the controller. The controller is the heart of the SDN and should be secured from such API misuse scenarios and network attacks. Most of the prior research in security for SDN controllers focuses on a defense mechanism for a particular attack scenario that requires changes in the controller code. This research proposes dynamic access control and a policy engine-based approach for protecting the SDN controller from network attacks and application bugs, thus defending against the misuse of the controller APIs. The proposed AEGIS protects controller APIs and defines a set of access, semantic, syntactic and communication policy rules and a permission set for accessing controller APIs. It utilizes the traditional API hooking technique to control API usage. We generated various attack scenarios that included application bugs and network attacks on the Floodlight SDN controller and showed that applying AEGIS secured the Floodlight controller APIs and hence protected them from network attacks and application bugs. Finally, we discuss performance comparison tests of the new AEGIS controller implementation for memory usage, API execution time and boot-up time and conclude that AEGIS effectively protects the SDN controller for trustworthy operations

ARP cache poisoning mitigation and forensics investigation

Address Resolution Protocol (ARP) cache spoofing or poisoning is an OSI layer 2 attack that exploits the statelessness vulnerability of the protocol to make network hosts susceptible to issues such as Man in the Middle attack, host impersonation, Denial of Service (DoS) and session hijacking. In this paper, a quantitative research approach is used to propose forensic tools for capturing evidences and mitigating ARP cache poisoning. The baseline approach is adopted to validate the proposed tools. The evidences captured before attack are compared against evidences captured when the network is under attack in order to ascertain the validity of the proposed tools in capturing ARP cache spoofing evidences. To mitigate the ARP poisoning attack, the security features DHCP Snooping and Dynamic ARP Inspection (DAI) are enabled and configured on a Cisco switch. The experimentation results showed the effectiveness of the proposed mitigation technique

Federated Agentless Detection of Endpoints Using Behavioral and Characteristic Modeling

During the past two decades computer networks and security have evolved that, even though we use the same TCP/IP stack, network traffic behaviors and security needs have significantly changed. To secure modern computer networks, complete and accurate data must be gathered in a structured manner pertaining to the network and endpoint behavior. Security operations teams struggle to keep up with the ever-increasing number of devices and network attacks daily. Often the security aspect of networks gets managed reactively instead of providing proactive protection. Data collected at the backbone are becoming inadequate during security incidents. Incident response teams require data that is reliably attributed to each individual endpoint over time. With the current state of dissociated data collected from networks using different tools it is challenging to correlate the necessary data to find origin and propagation of attacks within the network. Critical indicators of compromise may go undetected due to the drawbacks of current data collection systems leaving endpoints vulnerable to attacks. Proliferation of distributed organizations demand distributed federated security solutions. Without robust data collection systems that are capable of transcending architectural and computational challenges, it is becoming increasingly difficult to provide endpoint protection at scale. This research focuses on reliable agentless endpoint detection and traffic attribution in federated networks using behavioral and characteristic modeling for incident response