3,699 research outputs found

    A hybrid and cross-protocol architecture with semantics and syntax awareness to improve intrusion detection efficiency in Voice over IP environments

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    Includes abstract.Includes bibliographical references (leaves 134-140).Voice and data have been traditionally carried on different types of networks based on different technologies, namely, circuit switching and packet switching respectively. Convergence in networks enables carrying voice, video, and other data on the same packet-switched infrastructure, and provides various services related to these kinds of data in a unified way. Voice over Internet Protocol (VoIP) stands out as the standard that benefits from convergence by carrying voice calls over the packet-switched infrastructure of the Internet. Although sharing the same physical infrastructure with data networks makes convergence attractive in terms of cost and management, it also makes VoIP environments inherit all the security weaknesses of Internet Protocol (IP). In addition, VoIP networks come with their own set of security concerns. Voice traffic on converged networks is packet-switched and vulnerable to interception with the same techniques used to sniff other traffic on a Local Area Network (LAN) or Wide Area Network (WAN). Denial of Service attacks (DoS) are among the most critical threats to VoIP due to the disruption of service and loss of revenue they cause. VoIP systems are supposed to provide the same level of security provided by traditional Public Switched Telephone Networks (PSTNs), although more functionality and intelligence are distributed to the endpoints, and more protocols are involved to provide better service. A new design taking into consideration all the above factors with better techniques in Intrusion Detection are therefore needed. This thesis describes the design and implementation of a host-based Intrusion Detection System (IDS) that targets VoIP environments. Our intrusion detection system combines two types of modules for better detection capabilities, namely, a specification-based and a signaturebased module. Our specification-based module takes the specifications of VoIP applications and protocols as the detection baseline. Any deviation from the protocol’s proper behavior described by its specifications is considered anomaly. The Communicating Extended Finite State Machines model (CEFSMs) is used to trace the behavior of the protocols involved in VoIP, and to help exchange detection results among protocols in a stateful and cross-protocol manner. The signature-based module is built in part upon State Transition Analysis Techniques which are used to model and detect computer penetrations. Both detection modules allow for protocol-syntax and protocol-semantics awareness. Our intrusion detection uses the aforementioned techniques to cover the threats propagated via low-level protocols such as IP, ICMP, UDP, and TCP

    Multi-Layer Cyber-Physical Security and Resilience for Smart Grid

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    The smart grid is a large-scale complex system that integrates communication technologies with the physical layer operation of the energy systems. Security and resilience mechanisms by design are important to provide guarantee operations for the system. This chapter provides a layered perspective of the smart grid security and discusses game and decision theory as a tool to model the interactions among system components and the interaction between attackers and the system. We discuss game-theoretic applications and challenges in the design of cross-layer robust and resilient controller, secure network routing protocol at the data communication and networking layers, and the challenges of the information security at the management layer of the grid. The chapter will discuss the future directions of using game-theoretic tools in addressing multi-layer security issues in the smart grid.Comment: 16 page

    Novel Approach for IP-PBX Denial of Service Intrusion Detection Using Support Vector Machine Algorithm.

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    Recent trends have revealed that SIP based IP-PBX DoS attacks contribute to most overall IP-PBX attacks which is resulting in loss of revenues and quality of service in telecommunication providers. IP-PBX face challenges in detecting and mitigating malicious traffic. In this research, Support Vector Machine (SVM) machine learning detection & prevention algorithm were developed to detect this type of attacks Two other techniques were benchmarked decision tree and Naïve Bayes. The training phase of the machine learning algorithm used proposed real-time training datasets benchmarked with two training datasets from CICIDS and NSL-KDD. Proposed real-time training dataset for SVM algorithm achieved highest detection rate of 99.13% while decision tree and Naïve Bayes has 93.28% & 86.41% of attack detection rate, respectively. For CICIDS dataset, SVM algorithm achieved highest detection rate of 76.47% while decision tree and Naïve Bayes has 63.71% & 41.58% of detection rate, respectively. Using NSL-KDD training dataset, SVM achieved 65.17%, while decision tree and Naïve Bayes has 51.96% & 38.26% of detection rate, respectively.The time taken by the algorithms to classify the attack is very important. SVM gives less time (2.9 minutes) for detecting attacks while decision tree and naïve Bayes gives 13.6 minutes 26.2 minutes, respectively. Proposed SVM algorithm achieved the lowest false negative value of (87 messages) while decision table and Naïve Bayes achieved false negative messages of 672 and 1359, respectively

    Security-centric analysis and performance investigation of IEEE 802.16 WiMAX

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    Ubiquitous robust communications for emergency response using multi-operator heterogeneous networks

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    A number of disasters in various places of the planet have caused an extensive loss of lives, severe damages to properties and the environment, as well as a tremendous shock to the survivors. For relief and mitigation operations, emergency responders are immediately dispatched to the disaster areas. Ubiquitous and robust communications during the emergency response operations are of paramount importance. Nevertheless, various reports have highlighted that after many devastating events, the current technologies used, failed to support the mission critical communications, resulting in further loss of lives. Inefficiencies of the current communications used for emergency response include lack of technology inter-operability between different jurisdictions, and high vulnerability due to their centralized infrastructure. In this article, we propose a flexible network architecture that provides a common networking platform for heterogeneous multi-operator networks, for interoperation in case of emergencies. A wireless mesh network is the main part of the proposed architecture and this provides a back-up network in case of emergencies. We first describe the shortcomings and limitations of the current technologies, and then we address issues related to the applications and functionalities a future emergency response network should support. Furthermore, we describe the necessary requirements for a flexible, secure, robust, and QoS-aware emergency response multi-operator architecture, and then we suggest several schemes that can be adopted by our proposed architecture to meet those requirements. In addition, we suggest several methods for the re-tasking of communication means owned by independent individuals to provide support during emergencies. In order to investigate the feasibility of multimedia transmission over a wireless mesh network, we measured the performance of a video streaming application in a real wireless metropolitan multi-radio mesh network, showing that the mesh network can meet the requirements for high quality video transmissions
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