Journal articles: 'DDoS-Protection'

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Reynolds, Roy. "It's time to rethink DDoS protection." Network Security 2020, no. 1 (January 2020): 6–8. http://dx.doi.org/10.1016/s1353-4858(20)30007-6.

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Shah, Harshil, Priyansh Shah, and Swapna Naik. "DDOS Protection by Dividing and Limiting." International Journal of Computer Applications 155, no. 11 (December 15, 2016): 12–14. http://dx.doi.org/10.5120/ijca2016912251.

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Evglevskaya, N. V., A. Yu Zuev, A. O. Karasenko, and O. S. Lauta. "Comparative analysis of the effectiveness of existing methods of networks security from DDoS attacks." Radio industry (Russia) 30, no. 3 (September 8, 2020): 67–74. http://dx.doi.org/10.21778/2413-9599-2020-30-3-67-74.

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At present, issues related to information security are highly relevant. DoS and DDoS attacks are carried out by cybercriminals quite often, because cyberattacks can bring almost any system to failure, leaving no legally significant evidence. At the same time, the failure of the attacked subsystem can be an intermediate stage towards the target system. The most vulnerable to DDoS attacks are online stores, online payment systems, news resources and companies, whose activities depend on the frequency of user access to the resource. The main methods of protection against cyberattacks and DDoS attacks, in particular, are currently antivirus programs and firewalls. The article presents a description of some types of DDoS attacks as well as the results of a comparative analysis of several existing methods of networks security from DDoS attacks, which will simplify the choice of the optimal solution to ensure reliable protection of a telecommunication facility. Considering all the advantages and disadvantages, the method of organizing a network protection system against DDoS attacks based on the technology of artificial neural networks is the most suitable solution for ensuring the information security of networks of various purpose.

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Mahmood, Hassan, Danish Mahmood, Qaisar Shaheen, Rizwan Akhtar, and Wang Changda. "S-DPS: An SDN-Based DDoS Protection System for Smart Grids." Security and Communication Networks 2021 (March 20, 2021): 1–19. http://dx.doi.org/10.1155/2021/6629098.

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Information Communication Technology (ICT) environment in traditional power grids makes detection and mitigation of DDoS attacks more challenging. Existing security technologies, besides their efficiency, are not adequate to cater to DDoS security in Smart Grids (SGs) due to highly distributed and dynamic network environments. Recently, emerging Software Defined Networking- (SDN-) based approaches are proposed by researchers for SG’s DDoS protection; however, they are only able to protect against flooding attacks and are dependent on static thresholds. The proposed approach, i.e., Software Defined Networking-based DDoS Protection System (S-DPS), is efficiently addressing these issues by employing light-weight Tsallis entropy-based defense mechanisms using SDN environment. It provides early detection mechanism with mitigation of anomaly in real time. The approach offers the best deployment location of defense mechanism due to the centralized control of network. Moreover, the employment of a dynamic threshold mechanism is making detection process adaptive to the changing network conditions. S-DPS has demonstrated its effectiveness and efficiency in terms of Detection Rate (DR) and minimal CPU/RAM utilization, considering DDoS protection focusing smurf attacks, socket stress attacks, and SYN flood attacks.

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Selvakani, S., K. Vasumathi, T. Vijayalakshmi, and A. Kavitha. "Attack in SDN Based Distributed Denial of Service." Asian Journal of Engineering and Applied Technology 10, no. 1 (May 5, 2021): 38–44. http://dx.doi.org/10.51983/ajeat-2021.10.1.2802.

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DOS assaults are executed with the aid of using assault tools, worms and botnets the usage of exclusive packet-transmission techniques and diverse types of assault packets to conquer protection structures. These issues cause protection structures requiring diverse detection techniques to be able to discover assaults. Moreover, DOS assaults can blend their traffics for the duration of flash crowds. By doing this, the complicated protection machine cannot locate the assault site visitors in time. In this challenge a conduct primarily based totally detection the usage of Crowd Correlation Analysis which can discriminate DOS assault site visitors from site visitors generated with the aid of using actual customers. In the Euclidean area to specific as a diagonal matrix proposed can grasp the potential of community machine towards every assault manner and the protection functionality of community machine. Cyber-assault consisting of DDOS assault continues to be the maximum effective assault that disrupts the real customers from having access to the crucial offerings. In software layer-primarily based totally DDOS assault, attacker makes use of different gadget in preference to the usage of his very own IP cope with to flood the focused machine and disrupts the offerings SDN (software program described networks) for value performance and community Application layer allotted denial of provider (DDOS) assaults have turn out to be a extreme hazard to the safety of net servers. These assaults avoid maximum intrusion prevention structures with the aid of using sending several HTTP requests flexibility, however DDOS is one of the maximum released assault on SDN layer. DDOS assault on this kind of surroundings results in machine failure DDoS is one of the maximum released assault on SDN layer. DDOS assault on this kind of surroundings results in machine failure monetary loss, facts theft, and overall performance degradation massive survey has been made to locate and save you DDOS primarily based totally assault in software layer and SDN primarily based totally surroundings. We suggest an powerful protection machine, named Sky Shield, which leverages the caricature facts shape to fast locate and mitigate software layer DDOS assaults. Novel calculation of the divergence among sketches, which alleviates the effect of community dynamics and improves the detection accuracy.

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Rebecchi, Filippo, Julien Boite, Pierre-Alexis Nardin, Mathieu Bouet, and Vania Conan. "DDoS protection with stateful software-defined networking." International Journal of Network Management 29, no. 1 (August 9, 2018): e2042. http://dx.doi.org/10.1002/nem.2042.

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Khalaf, Bashar Ahmad, Salama A. Mostafa, Aida Mustapha, Mazin Abed Mohammed, Moamin A. Mahmoud, Bander Ali Saleh Al-Rimy, Shukor Abd Razak, Mohamed Elhoseny, and Adam Marks. "An Adaptive Protection of Flooding Attacks Model for Complex Network Environments." Security and Communication Networks 2021 (April 22, 2021): 1–17. http://dx.doi.org/10.1155/2021/5542919.

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Currently, online organizational resources and assets are potential targets of several types of attack, the most common being flooding attacks. We consider the Distributed Denial of Service (DDoS) as the most dangerous type of flooding attack that could target those resources. The DDoS attack consumes network available resources such as bandwidth, processing power, and memory, thereby limiting or withholding accessibility to users. The Flash Crowd (FC) is quite similar to the DDoS attack whereby many legitimate users concurrently access a particular service, the number of which results in the denial of service. Researchers have proposed many different models to eliminate the risk of DDoS attacks, but only few efforts have been made to differentiate it from FC flooding as FC flooding also causes the denial of service and usually misleads the detection of the DDoS attacks. In this paper, an adaptive agent-based model, known as an Adaptive Protection of Flooding Attacks (APFA) model, is proposed to protect the Network Application Layer (NAL) against DDoS flooding attacks and FC flooding traffics. The APFA model, with the aid of an adaptive analyst agent, distinguishes between DDoS and FC abnormal traffics. It then separates DDoS botnet from Demons and Zombies to apply suitable attack handling methodology. There are three parameters on which the agent relies, normal traffic intensity, traffic attack behavior, and IP address history log, to decide on the operation of two traffic filters. We test and evaluate the APFA model via a simulation system using CIDDS as a standard dataset. The model successfully adapts to the simulated attack scenarios’ changes and determines 303,024 request conditions for the tested 135,583 IP addresses. It achieves an accuracy of 0.9964, a precision of 0.9962, and a sensitivity of 0.9996, and outperforms three tested similar models. In addition, the APFA model contributes to identifying and handling the actual trigger of DDoS attack and differentiates it from FC flooding, which is rarely implemented in one model.

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Saleh, Mohammed A., and Azizah Abdul Manaf. "A Novel Protective Framework for Defeating HTTP-Based Denial of Service and Distributed Denial of Service Attacks." Scientific World Journal 2015 (2015): 1–19. http://dx.doi.org/10.1155/2015/238230.

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The growth of web technology has brought convenience to our life, since it has become the most important communication channel. However, now this merit is threatened by complicated network-based attacks, such as denial of service (DoS) and distributed denial of service (DDoS) attacks. Despite many researchers’ efforts, no optimal solution that addresses all sorts of HTTP DoS/DDoS attacks is on offer. Therefore, this research aims to fix this gap by designing an alternative solution called a flexible, collaborative, multilayer, DDoS prevention framework (FCMDPF). The innovative design of the FCMDPF framework handles all aspects of HTTP-based DoS/DDoS attacks through the following three subsequent framework’s schemes (layers). Firstly, an outer blocking (OB) scheme blocks attacking IP source if it is listed on the black list table. Secondly, the service traceback oriented architecture (STBOA) scheme is to validate whether the incoming request is launched by a human or by an automated tool. Then, it traces back the true attacking IP source. Thirdly, the flexible advanced entropy based (FAEB) scheme is to eliminate high rate DDoS (HR-DDoS) and flash crowd (FC) attacks. Compared to the previous researches, our framework’s design provides an efficient protection for web applications against all sorts of DoS/DDoS attacks.

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Le, Duc, Minh Dao, and Quyen Nguyen. "Comparison of machine learning algorithms for DDoS attack detection in SDN." Information and Control Systems, no. 3 (June 15, 2020): 59–70. http://dx.doi.org/10.31799/1684-8853-2020-3-59-70.

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Introduction: Distributed denial-of-service (DDoS) has become a common attack type in cyber security. Apart from the conventional DDoS attacks, software-defined networks also face some other typical DDoS attacks, such as flow-table attack or controller attack. One of the most recent solutions to detect a DDoS attack is using machine learning algorithms to classify the traffic. Purpose: Analysis of applying machine learning algorithms in order to prevent DDoS attacks in software-defined network. Results: A comparison of six algorithms (random forest, decision tree, naive Bayes, support vector machine, multilayer perceptron, k-nearest neighbors) with accuracy and process time as the criteria has shown that a decision tree and naïve Bayes are the most suitable algorithms for DDoS attack detection. As compared to other algorithms, they have higher accuracy, faster processing time and lower resource consumption. The main features that identify malicious traffic compared to normal one are the number of bytes in a flow, time flow, Ethernet source address, and Ethernet destination address. A flow-table attack can be detected easier than a bandwidth attack, as all the six algorithms can predict this type with a high accuracy. Practical relevance: Important features which play a supporting role in correct data classification facilitate the development of a DDoS protection system with a smaller dataset, focusing only on the necessary data. The algorithms more suitable for machine learning can help us to detect DDoS attacks in software-defined networks more accurately.

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Jili, Tianwen, and Nanfeng Xiao. "DDoS Detection and Protection Based on Cloud Computing Platform." Journal of Physics: Conference Series 1621 (August 2020): 012005. http://dx.doi.org/10.1088/1742-6596/1621/1/012005.

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Qudah, Zakaria Al, Basheer Al Duwairi, and Osama Al Khaleel. "DDoS protection as a service: hiding behind the giants." International Journal of Computational Science and Engineering 9, no. 4 (2014): 292. http://dx.doi.org/10.1504/ijcse.2014.060711.

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Bdair Alghuraibawi, Adnan Hasan, Rosni Abdullah, Selvakumar Manickam, and Zaid Abdi Alkareem Alyasseri. "Detection of ICMPv6-based DDoS attacks using anomaly based intrusion detection system: A comprehensive review." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (December 1, 2021): 5216. http://dx.doi.org/10.11591/ijece.v11i6.pp5216-5228.

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Security network systems have been an increasingly important discipline since the implementation of preliminary stages of Internet Protocol version 6 (IPv6) for exploiting by attackers. IPv6 has an improved protocol in terms of security as it brought new functionalities, procedures, i.e., Internet Control Message Protocol version 6 (ICMPv6). The ICMPv6 protocol is considered to be very important and represents the backbone of the IPv6, which is also responsible to send and receive messages in IPv6. However, IPv6 Inherited many attacks from the previous internet protocol version 4 (IPv4) such as distributed denial of service (DDoS) attacks. DDoS is a thorny problem on the internet, being one of the most prominent attacks affecting a network result in tremendous economic damage to individuals as well as organizations. In this paper, an exhaustive evaluation and analysis are conducted anomaly detection DDoS attacks against ICMPv6 messages, in addition, explained anomaly detection types to ICMPv6 DDoS flooding attacks in IPv6 networks. Proposed using feature selection technique based on bio-inspired algorithms for selecting an optimal solution which selects subset to have a positive impact of the detection accuracy ICMPv6 DDoS attack. The review outlines the features and protection constraints of IPv6 intrusion detection systems focusing mainly on DDoS attacks.

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Et. al., Dr Shanti Rathore,. "Multipath Reliable Routing Using Cluster Based Communication." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (April 10, 2021): 3210–15. http://dx.doi.org/10.17762/turcomat.v12i2.2378.

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In this research we proposed the protection in ANT Optimized primarily based multipath congestion routing performance. Here the situation of DDoS is simulated and examines their impact in dynamic network. The multipath protocol like AOMDV is balance the all load by way of offering alternative path however not knowledgeable at each and every condition. The DDoS attacker is blocking off the whole viable direction in community by way of flooding large quantity of redundant packets in dynamic network. The attacker is that the intermediate node and this attacker contamination is continuously dispersing infection and the entire network overall performance is dumped. The proposed security scheme is identified attacker and their loss effect. Attacker is utterly disabled by way of proposed protection mechanism and their loss is also evaluated. The proposed approach is now not only detecting but also stop community from DDoS attack. The overall performance of protection scheme and assault is measured in three distinctive scenarios of a range of node densities. The proposed scheme is offers attacker free routing and get better network performance after making use of it. The performance of ANT OPTIMIZED is almost equal. The packets receiving, throughput, and PDR are bettering but the loss of packets and unnecessary flooding is decreased in dynamic network.

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Mazur, Katarzyna, Bogdan Ksiezopolski, and Radoslaw Nielek. "Multilevel Modeling of Distributed Denial of Service Attacks in Wireless Sensor Networks." Journal of Sensors 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/5017248.

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The growing popularity of wireless sensor networks increases the risk of security attacks. One of the most common and dangerous types of attack that takes place these days in any electronic society is a distributed denial of service attack. Due to the resource constraint nature of mobile sensors, DDoS attacks have become a major threat to its stability. In this paper, we established a model of a structural health monitoring network, being disturbed by one of the most common types of DDoS attacks, the flooding attack. Through a set of simulations, we explore the scope of flood-based DDoS attack problem, assessing the performance and the lifetime of the network under the attack condition. To conduct our research, we utilized the Quality of Protection Modeling Language. With the proposed approach, it was possible to examine numerous network configurations, parameters, attack options, and scenarios. The results of the carefully performed multilevel analysis allowed us to identify a new kind of DDoS attack, the delayed distributed denial of service, by the authors, referred to as DDDoS attack. Multilevel approach to DDoS attack analysis confirmed that, examining endangered environments, it is significant to take into account many characteristics at once, just to not overlook any important aspect.

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Zhao, Yuntao, Wenbo Zhang, Yongxin Feng, and Bo Yu. "A Classification Detection Algorithm Based on Joint Entropy Vector against Application-Layer DDoS Attack." Security and Communication Networks 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/9463653.

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The application-layer distributed denial of service (AL-DDoS) attack makes a great threat against cyberspace security. The attack detection is an important part of the security protection, which provides effective support for defense system through the rapid and accurate identification of attacks. According to the attacker’s different URL of the Web service, the AL-DDoS attack is divided into three categories, including a random URL attack and a fixed and a traverse one. In order to realize identification of attacks, a mapping matrix of the joint entropy vector is constructed. By defining and computing the value of EUPI and jEIPU, a visual coordinate discrimination diagram of entropy vector is proposed, which also realizes data dimension reduction from N to two. In terms of boundary discrimination and the region where the entropy vectors fall in, the class of AL-DDoS attack can be distinguished. Through the study of training data set and classification, the results show that the novel algorithm can effectively distinguish the web server DDoS attack from normal burst traffic.

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A. Naagas, M., E. L. Mique Jr, T. D. Palaoag, and J. S. Dela Cruz. "Defense-through-Deception Network Security Model: Securing University Campus Network from DOS/DDOS Attack." Bulletin of Electrical Engineering and Informatics 7, no. 4 (December 1, 2018): 593–600. http://dx.doi.org/10.11591/eei.v7i4.1349.

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Denial of Service (DOS) and (DDOS) Distributed Denial of Service attacks have become a major security threat to university campus network security since most of the students and teachers prepare online services such as enrolment, grading system, library etc. Therefore, the issue of network security has become a priority to university campus network management. Using online services in university network can be easily compromised. However, traditional security mechanisms approach such as Defense-In-Depth (DID) Model is outdated in today’s complex network and DID Model has been used as a primary cybersecurity defense model in the university campus network today. However, university administration should realize that Defense-In-Depth (DID) are playing an increasingly limited role in DOS/DDoS protection and this paper brings this fact to light. This paper presents that the Defense-In-Depth (DID) is not capable of defending complex and volatile DOS/DDOS attacks effectively. The test results were presented in this study in order to support our claim. The researchers established a Defense-In-Depth (DID) Network model at the Central Luzon State University and penetrated the Network System using DOS/DDOS attack to simulate the real network scenario. This paper also presents the new approach Defense-through-Deception network security model that improves the traditional passive protection by applying deception techniques to them that give insights into the limitations posed by the Defense-In-Depth (DID) Model. Furthermore, this model is designed to prevent an attacker who has already entered the network from doing damage.

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Jeyanthi, N., and P. C. Mogankumar. "A Virtual Firewall Mechanism Using Army Nodes to Protect Cloud Infrastructure from DDoS Attacks." Cybernetics and Information Technologies 14, no. 3 (September 1, 2014): 71–85. http://dx.doi.org/10.2478/cait-2014-0034.

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Abstract Cloud is not exempted from the vulnerability of Distributed Denial of Service (DDoS) attack, a serious threat to any distributed network and has considerably less effective solutions to deploy in the network. This paper introduces a novel mechanism to protect and prevent the cloud from the spurious packets targeting the depletion of server resources. The army nodes called “Cloud DDoS Attack Protection” (CDAP) nodes are installed at the cloud server farm/ Datacenter (DC). These army nodes act as virtual firewall without destroying the Cloud Infrastructure and improve the availability of DC, even at the time of DDoS attack. By continuously monitoring the incoming packets, CDAP filters the attack packets intruding the Cloud DC. Availability is further improved by handing over the threat detection and attack mitigation to CDAP nodes and by redirecting the malicious user requests to the dump network. The simulation results prove that the introduction of CDAP nodes improve the availability and reduce the response time and the cost incurred.

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Kim, Dae Hwan, and Soo Jin Lee. "A Method for Preemptive Intrusion Detection and Protection Against DDoS Attacks." Journal of the Korea society of IT services 15, no. 2 (June 30, 2016): 157–67. http://dx.doi.org/10.9716/kits.2016.15.2.157.

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Kaur, Amarjeet, Gagandeep Kaur, and Gagandeep Kaur. "DdoS Attack Detection on Cloud Environment in Wireless Sensor Network: A Review." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 5 (June 2, 2018): 33. http://dx.doi.org/10.23956/ijarcsse.v8i5.662.

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In this sense, DoS, particularly DDoS, undermines the Internet, as well as debilitates the common security, because of its predominant utilization in digital wrongdoings. Accordingly to see well the attributes of DDoS issues and examine comparing protection instruments have noteworthy commitments for the scholarly world and industry, as well as for the government disability and crisis administration organizations, since they can utilize such learning to upgrade their capacities of hazard appraisals and help the partners to settle on suitable choices when confronting DDoS dangers. In the current research work the diverse sorts of issues, such viewpoint as far as distinguishing DoS assaults is to see the issue as that of a grouping issue on arrange state (and not on singular bundles or different units) by demonstrating ordinary and assault activity and characterizing the momentum condition of the system as great or terrible, in this way identifying assaults when they happen. Another is the Transmission disappointments or due date misses may bring about unsettling influences to the procedure, debasement of the general control execution. In future All these are settled with the assistance of a DDoS assault location and DSR Algorithm with Cryptography on Wireless Sensor organize and the WSN with BS, CH

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Tumbinskaya, Marina V., Vasily V. Vоlkоv, and Bulat G. Zagidullin. "Use of statistical methods for analysis and forecast of udp-flood attacks." Journal Of Applied Informatics 15, no. 89 (October 30, 2020): 85–102. http://dx.doi.org/10.37791/2687-0649-2020-15-5-85-102.

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Web resources are an integral part of the life of a modern person, who are now more and more often subjected to hacker attacks. The most popular types of attacks are the SQL-injections and cross-site scripting, but DDoS attacks continue to be in the top 10 of network attacks and lead to serious crashes and failures of web resources. The most common type of DDoS attack is UDP flood attack, based on the infinite sending of UDP packets to ports of various UDP services. The scientific novelty of the work lies in the fact that to increase the level of security of web resources a medium-term forecast of cyber attacks of the UDP-flood type, using the methods of correlation analysis, based on the additive time series model, is proposed taking into account seasonal factors and time duration, which will ensure the necessary level of web security -resources. The type of UDP-flood attacks was chosen as the object of study. Using the methods of correlation analysis and modeling, we calculated the seasonal index of UDP flood attacks, and the autocorrelation of the time series of this type of attack. Using the method of simple exponential smoothing, a forecast of UDP-flood attacks is constructed. The paper proposes a classification of DDoS attacks, describes protection methods. Based on the correlation analysis, the predicted values of the impact of UDP flood attacks on web resources are calculated, and the seasonal factor is revealed. The largest number of attacks is expected in the IV quarter of 2020. For DDoS attacks lasting up to 20 minutes, seasonality was also revealed in the 1st quarter of the calendar year, which means that in the 1st quarter of 2020 the largest number of attacks of this duration should be expected. Prospects for further research into the problem of protection against DDoS attacks are presented in the further development of the methodology for countering UDP flood attacks and information security algorithms for web resources, which will reduce the number of UDP flood attacks and increase the level of web resource security.

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Hosny, Khalid Mohamed, Ameer El-Sayed Gouda, and Ehab Rushdy Mohamed. "New Detection Mechanism for Distributed Denial of Service Attacks in Software Defined Networks." International Journal of Sociotechnology and Knowledge Development 12, no. 2 (April 2020): 1–30. http://dx.doi.org/10.4018/ijskd.2020040101.

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Software defined networks (SDN) are a recently developed form for controlling network management by providing centralized control unit called the Controller. This master Controller is a great power point but at the same time it is unfortunately a failure point and a serious loophole if it is targeted and dropped by attacks. One of the most serious types of attacks is the inability to access the Controller, which is known as the distributed denial of service (DDoS) attack. This research shows how DDoS attack can deplete the resources of the Controller and proposes a lightweight mechanism, which works at the Controller and detects a DDoS attack in the early stages. The proposed mechanism can not only detect the attack, but also identify attack paths and initiate a mitigation process to provide some degree of protection to network devices immediately after the attack is detected. The proposed mechanism depends on a hybrid technique that merges between the average flow initiation rate, and the flow specification of the coming traffic to the network.

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Borisenko, Konstantin, Ivan Kholod, and Andrey Shorov. "Framework for Infrastructure Attack Modeling in Hybrid Networks." International Journal of Mobile Computing and Multimedia Communications 6, no. 4 (October 2014): 98–114. http://dx.doi.org/10.4018/ijmcmc.2014100106.

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The paper considers a framework for modeling infrastructure attacks and protection mechanisms in hybrid networks. The developed framework saves time conducting tests and improves the accuracy of the experiments by connection the simulation system to real network nodes. The paper shows formal description of the modeling system components. Modeling system architecture and implementation are shown. The authors also describe modeling system verification. In addition, they provide the experiments devoted to DDoS attacks and operation of the protection techniques.

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Kodada, Basappa B., Gaurav Prasad, and Alwyn R. Pais. "Protection Against DDoS and Data Modification Attack in Computational Grid Cluster Environment." International Journal of Computer Network and Information Security 4, no. 7 (July 9, 2012): 12–18. http://dx.doi.org/10.5815/ijcnis.2012.07.02.

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Francois, Jérôme, Issam Aib, and Raouf Boutaba. "FireCol: A Collaborative Protection Network for the Detection of Flooding DDoS Attacks." IEEE/ACM Transactions on Networking 20, no. 6 (December 2012): 1828–41. http://dx.doi.org/10.1109/tnet.2012.2194508.

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Bhardwaj, Akashdeep, and Sam Goundar. "Comparing Single Tier and Three Tier Infrastructure Designs against DDoS Attacks." International Journal of Cloud Applications and Computing 7, no. 3 (July 2017): 59–75. http://dx.doi.org/10.4018/ijcac.2017070103.

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With the rise in cyber-attacks on cloud environments like Brute Force, Malware or Distributed Denial of Service attacks, information security officers and data center administrators have a monumental task on hand. Organizations design data center and service delivery with the aim of catering to maximize device provisioning & availability, improve application performance, ensure better server virtualization and end up securing data centers using security solutions at internet edge protection level. These security solutions prove to be largely inadequate in times of a DDoS cyber-attack. In this paper, traditional data center design is reviewed and compared to the proposed three tier data center. The resilience to withstand against DDoS attacks is measured for Real User Monitoring parameters, compared for the two infrastructure designs and the data is validated using T-Test.

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BACHMANOV, DMITRIY A., ANDREY R. OCHEREDKO, MICHAEL M. PUTYATO, and ALEXANDER S. MAKARYAN. "RESEARCH OF THE ISSUES OF IMPROVEMENT OF PROTECTION SYSTEMS AGAINST DDOS-ATTACKS BASED ON THE COMPREHENSIVE ANALYSIS OF MODERN INTERACTION MECHANISMS." CASPIAN JOURNAL: Control and High Technologies 53, no. 1 (2021): 63–74. http://dx.doi.org/10.21672/2074-1707.2021.53.1.063-074.

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The article presents the results of an analysis of the growth in the development of botnet networks and new cyber threats when they are used by cybercriminals. A review and comparison of the models for the implementation of botnet networks is carried out, as a result of which there are two main types. The main types of attacks carried out using the infrastructure of distributed computer networks are identified and classified, formed into 7 main groups, taking into account the relevance, prevalence and amount of damage. Based on the results of the analysis, it was determined that the most widespread and relevant type of attack is “Denial of Service”. The article presents a classification of services that provide services to ensure the protection of network resources from distributed attacks by the "Denial of Service" type, by the type of deployment, the level of security and the types of services provided. The comparison criteria are given taking into account their infrastructure, availability of technical support and a test period, available types of protection, capabilities, additional options, notification and reporting, as well as licensing. Practically implemented and shown a way to integrate the DDoS-Guard Protection service with an additional module at the application level, which made it possible to expand the methods of protection against DDoS attacks. Various modifications of the combined use of the module and the modified system make it possible to increase the expected level of detection and prevention of cyber - attacks.

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Serrano Mamolar, Ana, Pablo Salvá-García, Enrique Chirivella-Perez, Zeeshan Pervez, Jose M. Alcaraz Calero, and Qi Wang. "Autonomic protection of multi-tenant 5G mobile networks against UDP flooding DDoS attacks." Journal of Network and Computer Applications 145 (November 2019): 102416. http://dx.doi.org/10.1016/j.jnca.2019.102416.

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Haining Wang and K. G. Shin. "Transport-aware IP routers: A built-in protection mechanism to counter DDoS attacks." IEEE Transactions on Parallel and Distributed Systems 14, no. 9 (September 2003): 873–84. http://dx.doi.org/10.1109/tpds.2003.1233710.

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., Subhashini. "PROFILE BASED PROTECTION SCHEME AGAINST DDOS ATTACK IN WSN WITH DUAL CLUSTERING ALGORITHM." International Journal of Research in Engineering and Technology 04, no. 14 (April 25, 2015): 29–32. http://dx.doi.org/10.15623/ijret.2015.0414008.

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Wang, Bing, Yao Zheng, Wenjing Lou, and Y. Thomas Hou. "DDoS attack protection in the era of cloud computing and Software-Defined Networking." Computer Networks 81 (April 2015): 308–19. http://dx.doi.org/10.1016/j.comnet.2015.02.026.

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Wang, Li Hui. "Research on Security of P2P Technology." Applied Mechanics and Materials 644-650 (September 2014): 2826–29. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2826.

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This paper introduces P2P applications and its definition. Although this technology has the promising capability of anti-destruction and privacy protection, it still has quite a few intrinsic faults. In this paper, three popular methods of network attack against P2P: Sybil attack, Eclipse attack and DDOS attack. The differences among the three kinds of attack have been pointed out. At last, the defensive measures against the attacks have been introduced.

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Alatawi, Fahad. "Defense mechanisms against Distributed Denial of Service attacks: Comparative Review." Journal of Information Security and Cybercrimes Research 4, no. 1 (June 1, 2021): 81–94. http://dx.doi.org/10.26735/lqez4186.

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Distributed Denial of Service (DDoS) remains a big concern in Cybersecurity. DDoS attacks are implemented to prevent legitimate users from getting access to services. The attackers make use of multiple hosts that have been compromised (i.e., Botnets) to organize a large-scale attack on targets. Developing an effective defensive mechanism against existing and potential DDoS attacks remains a strong desire in the cybersecurity research community. However, development of effective mechanisms or solutions require adequate evaluation of existing defense mechanism and a critical analysis of how these methods have been implemented in preventing, detecting, and responding to DDoS attacks. This paper adopted a systematic review method to critically analyze the existing mechanisms. The review of existing literature helped classify the defense mechanism into four categories: source-based, core-router, victim-based, and distributed systems. A qualitative analysis was used to exhaustively evaluate these defense mechanisms and determine their respective effectiveness. The effectiveness of the defense mechanisms was evaluated on six key parameters: coverage, implementation, deployment, detection accuracy, response mechanism, and robustness. The comparative analysis reviewed the shortcomings and benefits of each mechanism. The evaluation determined that victim-based defense mechanisms have a high detection accuracy but is associated with massive collateral as the detection happens when it is too late to protect the system. On the other hand, whereas stopping an attack from the source-end is ideal, detection accuracy at this point is too low as it is hard to differentiate legitimate and malicious traffic. The effectiveness of the core-based defense systems is not ideal because the routers do not have enough CPU cycles and memory to profile the traffic. Distributed defense mechanisms are effective as components can be spread out across the three locations in a way that takes advantage of each location. The paper also established that the rate-limiting response mechanism is more effective than packet filtering method because it does not restrict legitimate traffic. The analysis revealed that there is no single defense mechanism that offers complete protection against DDoS attacks but concludes that the best defense mechanism is the use of distributed defense because it ensures that defense components are placed on all locations.

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Dake, Delali Kwasi, James Dzisi Gadze, Griffith Selorm Klogo, and Henry Nunoo-Mensah. "Multi-Agent Reinforcement Learning Framework in SDN-IoT for Transient Load Detection and Prevention." Technologies 9, no. 3 (June 29, 2021): 44. http://dx.doi.org/10.3390/technologies9030044.

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The fast emergence of IoT devices and its accompanying big and complex data has necessitated a shift from the traditional networking architecture to software-defined networks (SDNs) in recent times. Routing optimization and DDoS protection in the network has become a necessity for mobile network operators in maintaining a good QoS and QoE for customers. Inspired by the recent advancement in Machine Learning and Deep Reinforcement Learning (DRL), we propose a novel MADDPG integrated Multiagent framework in SDN for efficient multipath routing optimization and malicious DDoS traffic detection and prevention in the network. The two MARL agents cooperate within the same environment to accomplish network optimization task within a shorter time. The state, action, and reward of the proposed framework were further modelled mathematically using the Markov Decision Process (MDP) and later integrated into the MADDPG algorithm. We compared the proposed MADDPG-based framework to DDPG for network metrics: delay, jitter, packet loss rate, bandwidth usage, and intrusion detection. The results show a significant improvement in network metrics with the two agents.

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Maqbool, Zohaib, Raja Habib, Tariq Aziz, Asma Maqbool, and Oriba Altaf. "Internet Security Issues in Smart City Environment." Journal of Information Technology and Computing 1, no. 1 (December 31, 2020): 14–30. http://dx.doi.org/10.48185/jitc.v1i1.49.

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The invention of IoT devices brings innovation to solve and control house hold devices. The demand of IoT devices like Google and Amazon Echo family has increased after their invention. New inventions may leave a lot of security flaws that must be resolved or addressed. Invention of IoT devices especially devices made for household become, pre vulnerable to many cyber-attacks leading to the leak of privacy. Recent literature revealed that IoT devices have both positive and negative sides. Leakage of privacy and protection lea people into troubles due to the Denial of Service (DDoS) attacks.

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Vellalacheruvu, Hari Krishna, and Sanjeev Kumar. "Effectiveness of Built-in Security Protection of Microsoft’s Windows Server 2003 against TCP SYN Based DDoS Attacks." Journal of Information Security 02, no. 03 (2011): 131–38. http://dx.doi.org/10.4236/jis.2011.23013.

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Qin, Yu, Jingbin Liu, Shijun Zhao, Dengguo Feng, and Wei Feng. "RIPTE: Runtime Integrity Protection Based on Trusted Execution for IoT Device." Security and Communication Networks 2020 (September 23, 2020): 1–14. http://dx.doi.org/10.1155/2020/8957641.

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Software attacks like worm, botnet, and DDoS are the increasingly serious problems in IoT, which had caused large-scale cyber attack and even breakdown of important information infrastructure. Software measurement and attestation are general methods to detect software integrity and their executing states in IoT. However, they cannot resist TOCTOU attack due to their static features and seldom verify correctness of control flow integrity. In this paper, we propose a novel and practical scheme for software trusted execution based on lightweight trust. Our scheme RIPTE combines dynamic measurement and control flow integrity with PUF device binding key. Through encrypting return address of program function by PUF key, RIPTE can protect software integrity at runtime on IoT device, enabling to prevent the code reuse attacks. The results of our prototype’s experiment show that it only increases a small size TCB and has a tiny overhead in IoT devices under the constraint on function calling. In sum, RIPTE is secure and efficient in IoT device protection at runtime.

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Iyengar, N. Ch S. N., and Gopinath Ganapathy. "Trilateral Trust Based Defense Mechanism against DDoS Attacks in Cloud Computing Environment." Cybernetics and Information Technologies 15, no. 2 (June 1, 2015): 119–40. http://dx.doi.org/10.1515/cait-2015-0033.

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Abstract Distributed Denial of Service (DDoS) in a Cloud leads to a high rate of overload conditions, which subverts the Data Center (DC) performance and ends up in resource unavailability. This work proposes a “Trilateral Trust mechanism” which helps in detecting different kinds of attack groups at different points of time. It is the direct trust based defense mechanism for segregating legitimate and attack groups from the vast number of incoming requestors. It is a hybrid mechanism of trusts that follows the zero trust approach initially and eventually supports both Mutual trust and Momentary trust. This combinatorial trust mechanism helps in detecting almost all kinds of overload conditions at a cautionary period. Detecting the high rate of an attack at an earlier moment of time could reduce the traffic impact towards DC. The simulation results and profit analysis proved that the mechanism proposed is deployable at an attack-prone DC for resource protection, which would eventually benefit the DC economically as well.

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Salva-Garcia, Pablo, Jose M. Alcaraz-Calero, Qi Wang, Jorge Bernal Bernabe, and Antonio Skarmeta. "5G NB-IoT: Efficient Network Traffic Filtering for Multitenant IoT Cellular Networks." Security and Communication Networks 2018 (December 10, 2018): 1–21. http://dx.doi.org/10.1155/2018/9291506.

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Internet of Things (IoT) is a key business driver for the upcoming fifth-generation (5G) mobile networks, which in turn will enable numerous innovative IoT applications such as smart city, mobile health, and other massive IoT use cases being defined in 5G standards. To truly unlock the hidden value of such mission-critical IoT applications in a large scale in the 5G era, advanced self-protection capabilities are entailed in 5G-based Narrowband IoT (NB-IoT) networks to efficiently fight off cyber-attacks such as widespread Distributed Denial of Service (DDoS) attacks. However, insufficient research has been conducted in this crucial area, in particular, few if any solutions are capable of dealing with the multiple encapsulated 5G traffic for IoT security management. This paper proposes and prototypes a new security framework to achieve the highly desirable self-organizing networking capabilities to secure virtualized, multitenant 5G-based IoT traffic through an autonomic control loop featured with efficient 5G-aware traffic filtering. Empirical results have validated the design and implementation and demonstrated the efficiency of the proposed system, which is capable of processing thousands of 5G-aware traffic filtering rules and thus enables timely protection against large-scale attacks.

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Ngo, Duc-Minh, Cuong Pham-Quoc, and Tran Ngoc Thinh. "An Efficient High-Throughput and Low-Latency SYN Flood Defender for High-Speed Networks." Security and Communication Networks 2018 (December 24, 2018): 1–14. http://dx.doi.org/10.1155/2018/9562801.

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As one of the main types of Distributed Denial of Service (DDoS) attacks, SYN flood attacks have caused serious issues for servers when legitimate clients may be denied connections. There is an essential demand for a sufficient approach to mitigate SYN flood attacks. In this paper, we introduce an efficient high-throughput and low-latency SYN flood defender architecture, carefully designed with a pipeline model. A mathematical model is also introduced with the architecture for estimating SYN flood protection throughput and latency. The first prototype version based on the architecture with Verilog-HDL can function as standalone to alleviate high-rate SYN flood attacks and can be integrated into an OpenFlow switch for handling network packets. Our experiments with NetFPGA-10G platforms show that the core can protect servers against SYN flood attacks by up to 28+ millions packets per second that outperforms most well-known hardware-based approaches in the literature.

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Ghasabi, Mozhgan, and Mahmood Deypir. "Using optimized statistical distances to confront distributed denial of service attacks in software defined networks." Intelligent Data Analysis 25, no. 1 (January 26, 2021): 155–76. http://dx.doi.org/10.3233/ida-194796.

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Software-defined networks (SDN) are an emerging architecture that provides promising amends to put an end to current infrastructure constraints by optimized bandwidth utilization, flexibility in network management and configuration, and pulling down operating costs in traditional network structures. Despite the advantages of this architecture, SDNs may become the victim of a distributed denial of service (DDOS) attacks as the result of potential vulnerabilities in various layers. Therefore, the rapid detection of attack traffic in the early stages is very important. In this paper, we have proposed statistical solution to detect and to mitigate distributed denial of service attack in software-defined networks utilizing the unique capabilities of the SDN architecture. Here, the exponential weighted moving average protection mechanism (EWMA) in statistical distances is exploited. The simulation results of our extensive experiments showed that our mechanism is able to quick detection of attack traffics and take amendatory actions. Moreover, the evaluations show the superiority of the proposed algorithm with respect to other statistical methods.

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Alkahtani, Hasan, Theyazn H. H. Aldhyani, and Mohammed Al-Yaari. "Adaptive Anomaly Detection Framework Model Objects in Cyberspace." Applied Bionics and Biomechanics 2020 (December 9, 2020): 1–14. http://dx.doi.org/10.1155/2020/6660489.

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Telecommunication has registered strong and rapid growth in the past decade. Accordingly, the monitoring of computers and networks is too complicated for network administrators. Hence, network security represents one of the biggest serious challenges that can be faced by network security communities. Taking into consideration the fact that e-banking, e-commerce, and business data will be shared on the computer network, these data may face a threat from intrusion. The purpose of this research is to propose a methodology that will lead to a high level and sustainable protection against cyberattacks. In particular, an adaptive anomaly detection framework model was developed using deep and machine learning algorithms to manage automatically-configured application-level firewalls. The standard network datasets were used to evaluate the proposed model which is designed for improving the cybersecurity system. The deep learning based on Long-Short Term Memory Recurrent Neural Network (LSTM-RNN) and machine learning algorithms namely Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) algorithms were implemented to classify the Denial-of-Service attack (DoS) and Distributed Denial-of-Service (DDoS) attacks. The information gain method was applied to select the relevant features from the network dataset. These network features were significant to improve the classification algorithm. The system was used to classify DoS and DDoS attacks in four stand datasets namely KDD cup 199, NSL-KDD, ISCX, and ICI-ID2017. The empirical results indicate that the deep learning based on the LSTM-RNN algorithm has obtained the highest accuracy. The proposed system based on the LSTM-RNN algorithm produced the highest testing accuracy rate of 99.51% and 99.91% with respect to KDD Cup’99, NSL-KDD, ISCX, and ICI-Id2017 datasets, respectively. A comparative result analysis between the machine learning algorithms, namely SVM and KNN, and the deep learning algorithms based on the LSTM-RNN model is presented. Finally, it is concluded that the LSTM-RNN model is efficient and effective to improve the cybersecurity system for detecting anomaly-based cybersecurity.

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Kovalenko, Ya I. "THE NEED TO IMPLEMENT AT THE LEGISLATIVE LEVEL MEANS OF PROTECTION OF THE RIGHT TO A DOMAIN NAME FROM DOS (DDOS) ATTACKS IN UKRAINE." Juridical scientific and electronic journal, no. 1 (2021): 84–87. http://dx.doi.org/10.32782/2524-0374/2021-1/18.

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Zak, Michal, and J. Andrew Ware. "Cloud based Distributed Denial of Service Alleviation System." Annals of Emerging Technologies in Computing 4, no. 1 (January 1, 2020): 44–53. http://dx.doi.org/10.33166/aetic.2020.01.005.

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Cloud computing is a phenomenon that is changing information technology, with many companies no longer having data and resources retained within their own premises. Instead they are utilising cloud computing and its centralised resources. There are many benefits of this approach such as pay-per-use model, elasticity of operation and on demand resourcing. However, this approach also introduces additional security challenges. Security involves a triad of considerations, those being confidentiality, integrity and availability, often abbreviated to CIA. This work focusses on the last aspect of the CIA triad – availability, which is even more crucial for cloud-based platforms as centralised resources need to be provided at a distance to the end customers. Several factors including ‘denial of service’ attack impact availability. Moreover, current protection frameworks do not sufficiently consider the issues of verification, scalability and end-to-end latency. Hence, a new framework has been designed to fill the identified gap. The framework referred to as the cloud-based Distributed Denial of Service Alleviation System (DDoSAS) is based on its predecessor Enhanced DDoS-MS. The new framework has been implemented using Amazon Web Services. The work serves to provide a baseline for measuring end-to-end latency in real-life scenarios.

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Lakhno, Valerii, Andrii Blozva, Borys Husiev, Tetiana Osypova, and Yurii Matus. "INTEGRATION AND PROTECTION OF IOT DEVICES IN THE AVAILABLE INFRASTRUCTURE OF THE COMPUTER NETWORK OF THE EDUCATIONAL INSTITUTIONS." Cybersecurity: Education, Science, Technique 3, no. 11 (2021): 5–99. http://dx.doi.org/10.28925/2663-4023.2021.11.8599.

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The development of computer networks is gaining momentum. There are new challenges to data security and the end users themselves. With the advent of the Internet of Things, this problem has become quite acute for network engineers and cyber analysts. Increasingly, there are illegal actions to interfere with the work of the network itself and the use of users' devices for criminal purposes. Various distributed attacks, SQL injections and identity theft are becoming more complex. Given the growing infrastructure of both the network and IoT devices, there is a need to protect them. Especially when it comes to the computer network of a higher education institution. Where little attention is usually paid to full infrastructure protection, and with the integration of IoT devices, such possible gaps can occur quite a lot. This article attempts to reveal theoretical approaches to the design and implementation of a computer network of higher education institutions, which in recent years are increasingly beginning to suffer from outside interference. Possible attacks on the infrastructure of higher education institutions are analyzed, as well as the possibility of attack and interference in the work of IoT devices based on the killer chain approach. Internet The possibility of using a web application firewall and appropriate software for security and incident management at the L5-L7 OSI level is considered in such networks. Preliminary testing of the network for the ability to respond to L3-L4 level attacks using standard firewall capabilities. And with the response to interventions at the upper levels of the OSI L5-L7 model, namely: SQL injections, distributed DDoS, bot-net attacks. The results are summarized and further directions of research are determined, which are based on the improvement of the group security policy for the higher education institution. Development of security infrastructure for IoT devices and the ability to respond quickly to non-standard attacks.

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Isiaka, Fatima M., Salihu Abdullahi Audu, and Mustafa Ahmed Umar. "Developing a fail-safe culture in a cyber environment using MySQL replication technique." International Journal of Crowd Science 4, no. 2 (April 4, 2020): 149–70. http://dx.doi.org/10.1108/ijcs-04-2018-0008.

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Purpose The dependence on the use of information systems for nearly every activity and functions in the internet is increasingly high. This form of interconnectedness has bolstered national economies, enhanced how governments interact with their citizens and how ordinary people connect with friends and family. However, this dependence has equally resulted to a high rise in vulnerability, threat and risk associated with more use of information and communication technology. Cyber-attacks that have the potential to disrupt or damage information system infrastructure are getting more complex with some level of sophistication. Traditional protection of information system infrastructure is no longer sufficient; systems have proven to be immune to failure or incidents. This paper aims to ensure that there is a continuous availability of services through a fail-safe proof. Design/methodology/approach MYSQL replication technique was used to develop a model based on three-tier layers using the principle of network interdependency and the replication techniques. Tier 1 depicts a Telecom organization serving as service provider that provides internet service to Tier 2 organization – a Bank; Tier 3 is the financial App that can be used by bank staff and customers. The fail-safe mode integrated mechanism enables Tier 3 to continue to render its services in the event of an attack on Tier 1 such as DDoS without disruption. Findings This technique succeeded in mitigating the loss of data if cyber incident occurred or reception of uninterrupted services is countered, which give rise to future master-to-master architecture. Research limitations/implications The study conducted is limited to the design and development of a fail-safe system for interdependent networks or systems using MYSQL replication technique. Originality/value In an interdependent environment such as the cyberspace, the sectors are interdependent for optimal results. The originality of the work ensures that there is availability of services which is sustained and that data integrity is assured using the fail-safe technique based on MySQL replication method.

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Klymash, M. M., O. M. Shpur, and N. V. Pelekh. "WEB SERVICE AVAILABILITY MONITORING IN DISTRIBUTED INFOCOMMUNICATION SYSTEMS." Visnyk Universytetu “Ukraina”, no. 1 (28) 2020 (2020): 137–50. http://dx.doi.org/10.36994/2707-4110-2020-1-28-12.

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In this paper has been improved technique of security of web services against DDOS attacks based on the analysis of service information, which is based on monitoring of session duration spelled out in log files. This will increase the effectiveness of monitoring the security of web applications in distributed information systems after the attack of the first stage of its protection. The algorithm for monitoring the status of system based on log messages that are written to a file during the firewall stage has been proposed. Each message receives information such as web service request time and ip address. Using the time of access to the web service, you can track the attendance, and in the case of sharp differences with the number of visits in the previous intervals, to say about a possible attack. IP addresses us by tracking the number of requests from each request source, tracking who is causing the attack. Investigation of the effectiveness developed web application security monitoring system in distributed information communications systems has shown that at a time when the number of visits is increasing dramatically, the schedule is growing rapidly. This indicates a possible attack. If the current number of visits increases 10 times more than the average per day, the system will notify you. To do this, the data on visits for the year were uploaded to the database and the system was checked when the load increased. From the test results, we were able to verify that as the number of visits for the current hour increased, the system reported an attack. To visually check the operation of the algorithm, a graphical interface was proposed, which shows the state of the system, and a schedule of visits at 3 intervals: per day, per month, per year. Visual inspection allows you to quickly make sure that the conclusion about the attack is not wrong

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Ivanova, Xenia A. "Online voting as an element of cybersecurity of megacities." Law Enforcement Review 3, no. 2 (September 13, 2019): 31–37. http://dx.doi.org/10.24147/2542-1514.2019.3(2).31-37.

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The subject. The author explores the possibility of online voting during the elections from the perspective of urban security.The purpose of the paper is to confirm or disprove hypothesis that introduction of online voting in the elections in large cities contributes to the growth of the electorate’s confidence and reduction of absenteeism, but only if cybersecurity of metropolises is ensured.The methodology of the study includes general scientific methods (analysis, synthesis, description) and the method of comparative law.The main results and scope of their application. The very essence of online voting involves the use of a dedicated Internet platform and digital devices. This method has many advantages, including the ability to attract many people, the convenience and reliability of the whole process, as well as the automatic calculation of results. However, the issue of online voting in large cities directly affects the problem of ensuring their cybersecurity. Electronic voting can be subject to certain risks like any Internet procedure. Some of them have their own offline counterparts, such as the sale of votes. Others are unique to the digital environment, such as cyber violations and DDoS-attacks.Conclusions. Electronic voting helps to solve the problem of low voters’ turnout, unites communities, universities, companies and people. This new process must be protected from any potential threats to security.An inefficient voter authentication procedure can adversely affect the reliability of the entire online voting system. Hacking the authentication system can lead to fraud and theft of data and votes. The blockchain system provides effective protection against such hacks and cyberattacks. It would be effective if it was possible to download a special anti-virus program from the election commission website to clean the user's computer from malicious content or at least check the presence of viral content. The license key of such a program may be valid only for the period of the elections. The decision against forcing an electronic vote for a particular candidate can be made by an online voting system that allows you to change your choice several times. We need well-thought-out training and advanced training programmes for state and municipal employees, including programmes for initial technical training, to reduce security risks. It is necessary to train possible users of the online voting system, since the security of a computer or smartphone, the absence of virus programs, as well as the timeliness of voting are in the area of responsibility of online voters. Online voting may not be the only way a voter can express his or her will. It is always necessary to keep the possibility of classical voting by paper ballots.

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Andrysiak, Tomasz, Łukasz Saganowski, Mirosław Maszewski, and Piotr Grad. "A DDoS Attacks Detection Based on Conditional Heteroscedastic Time Series Models." Image Processing & Communications 20, no. 1 (March 1, 2015): 23–33. http://dx.doi.org/10.1515/ipc-2015-0027.

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Abstract Dynamic development of various systems providing safety and protection to network infrastructure from novel, unknown attacks is currently an intensively explored and developed domain. In the present article there is presented an attempt to redress the problem by variability estimation with the use of conditional variation. The predictions of this variability were based on the estimated conditional heteroscedastic statistical models ARCH, GARCH and FIGARCH. The method used for estimating the parameters of the exploited models was determined by calculating maximum likelihood function. With the use of compromise between conciseness of representation and the size of estimation error there has been selected as a sparingly parameterized form of models. In order to detect an attack-/anomaly in the network traffic there were used differences between the actual network traffic and the estimated model of the traffic. The presented research confirmed efficacy of the described method and cogency of the choice of statistical models.

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Apiecionek, Łukasz, and Matusz Biedziak. "Fuzzy Adaptive Data Packets Control Algorithm for IoT System Protection." JUCS - Journal of Universal Computer Science 26, no. 11 (November 28, 2020): 1435–54. http://dx.doi.org/10.3897/jucs.2020.076.

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One of huge problem for recent IT systems are attacks on their resources called Distributed Denial of Service attacks. Many servers which are accessible from public network were a victim of such attacks or could be in the future. Unfortunately, there is still no effective method for protecting network servers against source of the attack, while such attack could block network resources for many hours. Existing solutions for protecting networks and IoT systems are using mainly firewalls and IDS/IPS mechanisms, which is not sufficient. This article presents the method minimizing the DDoS attacks. Proposed method provides possibilities for the network administrators to protect their servers and IoT network resources during the attack. The proposed fuzzy adaptive algorithm is using Ordered Fuzzy Numbers for predicting amount of packets which could be passed over the network boarder gateway. Proposed solution will give the opportunity for ordinary users to finish their work when the attack occurs.

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Wani, Azka, and S. Revathi. "Ransomware protection in IoT using software defined networking." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (June 1, 2020): 3166. http://dx.doi.org/10.11591/ijece.v10i3.pp3166-3175.

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Internet of things (IoT) is the network of physical objects connected to provide various services. IoT is expanding rapidly, and is positively influencing many areas. The impact of IoT is evident in medical field, manufacturing units and livestock. The IoT is also vulnerable to many cyber threats, owing to its limited resources and battery operation. In contemporary times the security threats like DDoS, botnet malware, man in the middle, flood attacks and ransomware are affecting the smooth functioning of IoT. Ransomware has emerged as one of the biggest threat in cyber world. Ransomware is a type of malware that stops the access to files by encrypting them and decrypts the files only when a ransom is paid. The negligence towards the IoT ransomware can result in disastrous outcomes. In this paper, the growth of ransomware attacks for past few years is shown with special focus on ransomwares threatening IoT. A detection mechanism for IoT ransomware attack is presented that is designed after study of ransomware for IoT. The proposed model monitors the incoming IoT traffic through Software Defined Network (SDN) gateway. It uses policies framed in SDN controller for detection and alleviation of ransomware in IoT.

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Journal articles on the topic 'DDoS-Protection'

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