Efficient Detection of Attacks in SIP Based VoIP Networks Using Linear l1-SVM Classifier

The Session Initiation Protocol (SIP) is one of the most common protocols that are used for signaling function in Voice over IP (VoIP) networks. The SIP protocol is very popular because of its flexibility, simplicity, and easy implementation, so it is a target of many attacks. In this paper, we propose a new system to detect the Denial of Service (DoS) attacks (i.e. malformed message and invite flooding) and Spam over Internet Telephony (SPIT) attack in the SIP based VoIP networks using a linear Support Vector Machine with l1 regularization (i.e. l1-SVM) classifier. In our approach, we project the SIP messages into a very high dimensional space using string based n-gram features. Hence, a linear classifier is trained on the top of these features. Our experimental results show that the proposed system detects malformed message, invite flooding, and SPIT attacks with a high accuracy. In addition, the proposed system outperformed other systems significantly in the detection speed

Control and Protection of MMC-Based HVDC Systems: A Review

The voltage source converter (VSC) based HVDC (high voltage direct current system) offers the possibility to integrate other renewable energy sources (RES) into the electrical grid, and allows power flow reversal capability. These appealing features of VSC technology led to the further development of multi-terminal direct current (MTDC) systems. MTDC grids provide the possibility of interconnection between conventional power systems and other large-scale offshore sources like wind and solar systems. The modular multilevel converter (MMC) has become a popular technology in the development of the VSC-MTDC system due to its salient features such as modularity and scalability. Although, the employment of MMC converter in the MTDC system improves the overall system performance. However, there are some technical challenges related to its operation, control, modeling and protection that need to be addressed. This paper mainly provides a comprehensive review and investigation of the control and protection of the MMC-based MTDC system. In addition, the issues and challenges associated with the development of the MMC-MTDC system have been discussed in this paper. It majorly covers the control schemes that provide the AC system support and state-of-the-art relaying algorithm/ dc fault detection and location algorithms. Different types of dc fault detection and location algorithms presented in the literature have been reviewed, such as local measurement-based, communication-based, traveling wave-based and artificial intelligence-based. Characteristics of the protection techniques are compared and analyzed in terms of various scenarios such as implementation in CBs, system configuration, selectivity, and robustness. Finally, future challenges and issues regarding the development of the MTDC system have been discussed in detail

A muti-agent based framework for managing security policy

No abstract available

A new standard security policy language

Some of the significant factors that led to the introduction of a new standard security policy language (SSPL) as a tool to help security officers write security policies in a standard format are discussed. The need for automation systems that increased due to more attacks along with continuous change and increase in organizational policies to keep assets secured were some of these factors that to led to the creation of the SSPL. The language facilitated the task of the automation systems and increased the need for a policy tracking tool of defined policies within the organization along with their existing configurations. It included a formal policy statement, scale and domain, descriptive, and extensible languages. The proposed SSPL also covered the intended features from the security policy language. It represented policy as a serialized policy object, while each object encapsulated policy structure and configuration

Fog-Based CDN Framework for Minimizing Latency of Web Services Using Fog-Based HTTP Browser

Cloud computing has been a dominant computing paradigm for many years. It provides applications with computing, storage, and networking capabilities. Furthermore, it enhances the scalability and quality of service (QoS) of applications and offers the better utilization of resources. Recently, these advantages of cloud computing have deteriorated in quality. Cloud services have been affected in terms of latency and QoS due to the high streams of data produced by many Internet of Things (IoT) devices, smart machines, and other computing devices joining the network, which in turn affects network capabilities. Content delivery networks (CDNs) previously provided a partial solution for content retrieval, availability, and resource download time. CDNs rely on the geographic distribution of cloud servers to provide better content reachability. CDNs are perceived as a network layer near cloud data centers. Recently, CDNs began to perceive the same degradations of QoS due to the same factors. Fog computing fills the gap between cloud services and consumers by bringing cloud capabilities close to end devices. Fog computing is perceived as another network layer near end devices. The adoption of the CDN model in fog computing is a promising approach to providing better QoS and latency for cloud services. Therefore, a fog-based CDN framework capable of reducing the load time of web services was proposed in this paper. To evaluate our proposed framework and provide a complete set of tools for its use, a fog-based browser was developed. We showed that our proposed fog-based CDN framework improved the load time of web pages compared to the results attained through the use of the traditional CDN. Different experiments were conducted with a simple network topology against six websites with different content sizes along with a different number of fog nodes at different network distances. The results of these experiments show that with a fog-based CDN framework offloading autonomy, latency can be reduced by 85% and enhance the user experience of websites