Visible to the public Biblio

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2023-06-22
Kivalov, Serhii, Strelkovskaya, Irina.  2022.  Detection and prediction of DDoS cyber attacks using spline functions. 2022 IEEE 16th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET). :710–713.
The issues of development and legal regulation of cybersecurity in Ukraine are considered. The expediency of further improvement of the regulatory framework, its implementation and development of cybersecurity systems is substantiated. Further development of the theoretical base of cyber defense using spline functions is proposed. The characteristics of network traffic are considered from the point of view of detecting DDoS cyber attacks (SYN-Flood, ICMP-Flood, UDP-Flood) and predicting DDoS cyber-attacks using spline functions. The spline extrapolation method makes it possible to predict DDoS cyber attacks with great accuracy.
2022-04-20
Jun, Shen, Cuibo, Yu.  2013.  The Study on the Self-Similarity and Simulation of CPS Traffic. 2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing. :215–219.
CPS traffic characteristics is one of key techniques of Cyber-Physical Systems (CPS). A deep research of CPS network traffic characteristics can help to better plan and design CPS networks. A brief overview of the key concepts of CPS is firstly presented. Then CPS application scenarios are analyzed in details and classified. The characteristics of CPS traffic is analyzed theoretically for different CPS application scenarios. At last, the characteristics of CPS traffic is verified using NS-2 simulation.
2022-02-07
Abbood, Zainab Ali, Atilla, Doğu Çağdaş, Aydin, Çağatay, Mahmoud, Mahmoud Shuker.  2021.  A Survey on Intrusion Detection System in Ad Hoc Networks Based on Machine Learning. 2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI). :1–8.
This advanced research survey aims to perform intrusion detection and routing in ad hoc networks in wireless MANET networks using machine learning techniques. The MANETs are composed of several ad-hoc nodes that are randomly or deterministically distributed for communication and acquisition and to forward the data to the gateway for enhanced communication securely. MANETs are used in many applications such as in health care for communication; in utilities such as industries to monitor equipment and detect any malfunction during regular production activity. In general, MANETs take measurements of the desired application and send this information to a gateway, whereby the user can interpret the information to achieve the desired purpose. The main importance of MANETs in intrusion detection is that they can be trained to detect intrusion and real-time attacks in the CIC-IDS 2019 dataset. MANETs routing protocols are designed to establish routes between the source and destination nodes. What these routing protocols do is that they decompose the network into more manageable pieces and provide ways of sharing information among its neighbors first and then throughout the whole network. The landscape of exciting libraries and techniques is constantly evolving, and so are the possibilities and options for experiments. Implementing the framework in python helps in reducing syntactic complexity, increases performance compared to implementations in scripting languages, and provides memory safety.
2022-01-25
Uddin Nadim, Taef, Foysal.  2021.  Towards Autonomic Entropy Based Approach for DDoS Attack Detection and Mitigation Using Software Defined Networking. 2021 International Conference on Automation, Control and Mechatronics for Industry 4.0 (ACMI). :1—5.
Software defined networking (SDN) architecture frame- work eases the work of the network administrators by separating the data plane from the control plane. This provides a programmable interface for applications development related to security and management. The centralized logical controller provides more control over the total network, which has complete network visibility. These SDN advantages expose the network to vulnerabilities and the impact of the attacks is much severe when compared to traditional networks, where the network devices have protection from the attacks and limits the occurrence of attacks. In this paper, we proposed an entropy based algorithm in SDN to detect as well as stopping distributed denial of service (DDoS) attacks on the servers or clouds or hosts. Firstly, there explored various attacks that can be launched on SDN at different layers. Basically DDoS is one kind of denial of service attack in which an attacker uses multiple distributed sources for attacking a particular server. Every network in a system has an entropy and an increase in the randomness of probability causes entropy to decrease. In comparison with previous entropy based approaches this approach has higher performance in distinguishing legal and illegal traffics and blocking illegal traffic paths. Linux OS and Mininet Simulator along with POX controller are used to validate the proposed approach. By conducting pervasive simulation along with theoretical analysis this method can definitely detect and stop DDoS attacks automatically.
2015-05-05
Fernandez Arguedas, V., Pallotta, G., Vespe, M..  2014.  Automatic generation of geographical networks for maritime traffic surveillance. Information Fusion (FUSION), 2014 17th International Conference on. :1-8.

In this paper, an algorithm is proposed to automatically produce hierarchical graph-based representations of maritime shipping lanes extrapolated from historical vessel positioning data. Each shipping lane is generated based on the detection of the vessel behavioural changes and represented in a compact synthetic route composed of the network nodes and route segments. The outcome of the knowledge discovery process is a geographical maritime network that can be used in Maritime Situational Awareness (MSA) applications such as track reconstruction from missing information, situation/destination prediction, and detection of anomalous behaviour. Experimental results are presented, testing the algorithm in a specific scenario of interest, the Dover Strait.