VoIP applications are emerging today as an important component in business and communication industry. In this paper, we address the intrusion detection and prevention in VoIP networks and describe how a conceptual solution based on the Bayes inference approach can be used to reinforce the existent security mechanisms. Our approach is based on network monitoring and analyzing of the VoIP-specific traffic. We give a detailed example on attack detection using the SIP signaling protocol.
A novel approach for security issues in VoIP networks in Virtualization with IVR
VoIP（Voice over Internet Protocol）是近十年来发展起来的一项技术。它提供了音频，视频流的设施，在网络上成功实施。但是，它提供了网络上的文本传输功能。由于它的成本效益的解决方案的实施，它可以被开发为一个有声望的组织的员工之间的相互沟通。所提出的想法已经在VoIP技术的音频流领域实现。在音频流中，VoIP服务器在双方通信期间可能存在安全漏洞。在所提出的模型中，首先，VoIP系统已经实现了IVR（交互式语音响应）作为一个案例研究，并与作为VoIP服务提供商的星号服务器提供的安全参数的实施。星号服务器已经配置了不同的安全参数，如VPN服务器，防火墙iptable规则，入侵检测和入侵防御系统。每个参数都将由VoIP服务器的系统管理员以及MySQL数据库进行监控。系统管理员将通过连接到星号服务器的邮件服务器获得与服务器上的攻击相关的每个更新。所提出的系统的主要优点是VoIP服务器单独配置为VoIP服务器，IVR提供商，具有IDS和IPS的邮件服务器，VPN服务器，在虚拟化环境中的单个星号服务器中与数据库服务器连接。VoIP系统是在大学系统内部的局域网中实现的
Mobile Ad-hoc Network (MANET) is a distributed, decentralized network of wireless portable nodes connecting directly without any fixed communication base station or centralized administration. Nodes in MANET move continuously in random directions and follow an arbitrary manner, which presents numerous challenges to these networks and make them more susceptible to different security threats. Due to this decentralized nature of their overall architecture, combined with the limitation of hardware resources, those infrastructure-less networks are more susceptible to different security attacks such…
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）；University of Chinese Academy of Sciences（中国科学院大学）；University of Macau（澳门大学）；University of New Brunswick（新不伦瑞克大学）
As Internet of Things devices become prevalent, using intrusion detection to protect IoT from malicious intrusions is of vital importance. However, the data scarcity of IoT hinders the effectiveness of traditional intrusion detection methods. To tackle this issue, in this paper, we propose the Adaptive Bi-Recommendation and Self-Improving Network (ABRSI) based on unsupervised heterogeneous domain adaptation (HDA). The ABRSI transfers enrich intrusion knowledge from a data-rich network intrusion source domain to facilitate effective intrusion detection for data-scarce IoT target domains. The AB…
Network connectivity exposes the network infrastructure and assets to vulnerabilities that attackers can exploit. Protecting network assets against attacks requires the application of security countermeasures. Nevertheless, employing countermeasures incurs costs, such as monetary costs, along with time and energy to prepare and deploy the countermeasures. Thus, an Intrusion Response System (IRS) shall consider security and QoS costs when dynamically selecting the countermeasures to address the detected attacks. This has motivated us to formulate a joint Security-vs-QoS optimization problem to …
Interest in poisoning attacks and backdoors recently resurfaced for Deep Learning (DL) applications. Several successful defense mechanisms have been recently proposed for Convolutional Neural Networks (CNNs), for example in the context of autonomous driving. We show that visualization approaches can aid in identifying a backdoor independent of the used classifier. Surprisingly, we find that common defense mechanisms fail utterly to remove backdoors in DL for Intrusion Detection Systems (IDSs). Finally, we devise pruning-based approaches to remove backdoors for Decision Trees (DTs) and Random F…
IEEE 802.1 Time-sensitive Networking~(TSN) standards are envisioned to replace legacy network protocols in critical domains to ensure reliable and deterministic communication over off-the-shelf Ethernet equipment. However, they lack security countermeasures and can even impose new attack vectors that may lead to hazardous consequences. This paper presents the first open-source security monitoring and intrusion detection mechanism, TSNZeek, for IEEE 802.1 TSN protocols. We extend an existing monitoring tool, Zeek, with a new packet parsing grammar to process TSN data traffic and a rule-based at…
Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is …
College of Technological Innovation, Zayed University（扎耶德大学技术创新学院）；University of Ottawa（渥太华大学）
Volunteer computing uses Internet-connected devices (laptops, PCs, smart devices, etc.), in which their owners volunteer them as storage and computing power resources, has become an essential mechanism for resource management in numerous applications. The growth of the volume and variety of data traffic in the Internet leads to concerns on the robustness of cyberphysical systems especially for critical infrastructures. Therefore, the implementation of an efficient Intrusion Detection System for gathering such sensory data has gained vital importance. In this paper, we present a comparative stu…
With a plethora of new connections, features, and services introduced, the 5th generation (5G) wireless technology reflects the development of mobile communication networks and is here to stay for the next decade. The multitude of services and technologies that 5G incorporates have made modern communication networks very complex and sophisticated in nature. This complexity along with the incorporation of Machine Learning (ML) and Artificial Intelligence (AI) provides the opportunity for the attackers to launch intelligent attacks against the network and network devices. These attacks often tra…
Due to the rising number of sophisticated customer functionalities, electronic control units (ECUs) are increasingly integrated into modern automotive systems. However, the high connectivity between the in-vehicle and the external networks paves the way for hackers who could exploit in-vehicle network protocols' vulnerabilities. Among these protocols, the Controller Area Network (CAN), known as the most widely used in-vehicle networking technology, lacks encryption and authentication mechanisms, making the communications delivered by distributed ECUs insecure. Inspired by the outstanding perfo…
SecureDyn-FL: A Robust Privacy-Preserving Federated Learning Framework for Intrusion Detection in IoT Networks
Sir Syed CASE Institute of Technology（Sir Syed CASE 理工学院）；Habib University（哈比布大学）；Yeunganam University（延世南大学）；University of Nottingham Ningbo China（诺丁汉大学宁波分校）；Korea University（高丽大学）
A model for multi-attack classification to improve intrusion detection performance using deep learning approaches
University College of Engineering(A), Osmania University（奥斯马尼亚大学（A）工程学院）；Vasavi College of Engineering（瓦萨维工程学院）；Bhavans Vivekananda College（巴万斯维韦卡南达学院）；KG Reddy College of Engineering & Technology（KG雷迪工程与技术学院）
The increase of cyber attacks in both the numbers and varieties in recent years demands to build a more sophisticated network intrusion detection system (NIDS). These NIDS perform better when they can monitor all the traffic traversing through the network like when being deployed on a Software-Defined Network (SDN). Because of the inability to detect zero-day attacks, signature-based NIDS which were traditionally used for detecting malicious traffic are beginning to get replaced by anomaly-based NIDS built on neural networks. However, recently it has been shown that such NIDS have their own dr…
Toward Autonomous and Efficient Cybersecurity: A Multi-Objective AutoML-based Intrusion Detection System
Faculty of Business and Information Technology, Ontario Tech University（业务与信息科技学院，安大略技术大学）；Department of Electrical and Computer Engineering, Western University（电气与计算机工程系，西部大学）
