Secure SDN Traffic based on Machine Learning Classifier

Nowadays, the majority of human activities are carried out utilizing a variety of services or applications that rely on the local and Internet connectivity services provided by private or public networks. With the developments in Machine Learning and Software Defined Networking, traffic classification has become an essential study subject.  As a consequence of the segregation of control and data planes, Software Defined Networks have some security flaws. To cope with malicious code in SDN, certain operational security techniques have been devised. In this paper, a machine learning model, supervised, was utilized to identify normal and malicious traffic flows. While, normal traffic were generated using Internet traffic generator, malicious traffic were accomplish by Scapy and Python. The main network features of the OpenFlow flow table such as Packets count, bytes counts, packet rates, byte rate for forward and revers flows, were extracted. The combination of good ML classifier and dataset produced the greatest accuracy rate over 99% in DDoS attack detection, according to the results. Further to the main aim, the presented approach could be utilized to classify different traffic flows with the purpose of balance and priorities the important traffic

Developing Best Practices for Securing VoIP Communication for a non-profit Organization

Voice over Internet Protocol (VoIP) is the most widely used service around the world. The proficiency of it utilizing the web has increased awesome ubiquity in the current years. With this notoriety, there is expanding worry about the wellbeing of the system. The robbery or loss of the information being exchanged is great concern. For example, a basic problem for researchers who are developing safeguards for VoIP systems is the level of threats and other issues experienced by the non-profit organizations while implementing VoIP communication. This problem originated when non-profits received pressure from their donors not to implement VoIP communication because it will record important and valuable information of their bank account, including their bank balance, and consequently, exposing them to the public. Other dangers include safeguarding secrecy, respectability, and accessibility of the system, known as CIA. dangers. To battle these dangers, some security conventions and calculations have been produced. For example, the H.235 has been investigated, their calculations updated, and it is currently regarded as the most recent and effective system for security of the VoIP system. Another method for battling issues and concerns, and one that is the most proficient due to bigger budgets than non-profits, is VoIP being utilized in new structures and the IT work force. Fortunately, the expanding interest of VoIP has guaranteed and emphasized the requirement for more research to build up the effective security structures and countermeasures of CIA threats. This investigation examines the methods by which such security issues concerning VoIP can be set out to give an appropriate, secure and effective method for correspondence and data trade. In this postulation, the analyst will profoundly examine the relief of VoIP security issues

Secure communication channel architecture for Software Defined Mobile Networks

Abstract A Software-Defined Mobile Network (SDMN) architecture is proposed to enhance the performance, flexibility, and scalability of today’s telecommunication networks. However, SDMN features such as centralized controlling, network programmability, and virtualization introduce new security challenges to telecommunication networks. In this article, we present security challenges related to SDMN communication channels (i.e., control and data channel) and propose a novel secure communication channel architecture based on Host Identity Protocol (HIP). IPsec tunneling and security gateways are widely utilized in present-day mobile networks to secure backhaul communication channels. However, the utilization of legacy IPsec mechanisms in SDMNs is challenging due to limitations such as distributed control, lack of visibility, and limited scalability. The proposed architecture also utilizes IPsec tunnels to secure the SDMN communication channels by eliminating these limitations. The proposed architecture is implemented in a testbed and we analyzed its security features. The performance penalty of security due to the proposed security mechanisms is measured on both control and data channels