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Long, Saiqin, Yu, Hao, Li, Zhetao, Tian, Shujuan, Li, Yun.  2020.  Energy Efficiency Evaluation Based on QoS Parameter Specification for Cloud Systems. 2020 IEEE 22nd International Conference on High Performance Computing and Communications; IEEE 18th International Conference on Smart City; IEEE 6th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). :27–34.
Energy efficiency evaluation (EEE) is a research difficulty in the field of cloud computing. The current research mainly considers the relevant energy efficiency indicators of cloud systems and weights the interrelationship between energy consumption, system performance and QoS requirements. However, it lacks a combination of subjective and objective, qualitative and quantitative evaluation method to accurately evaluate the energy efficiency of cloud systems. We propose a novel EEE method based on the QoS parameter specification for cloud systems (EEE-QoS). Firstly, it reduces the metric values that affect QoS requirements to the same dimension range and then establishes a belief rule base (BRB). The best-worst method is utilized to determine the initial weights of the premise attributes in the BRB model. Then, the BRB model parameters are optimized by the mean-square error, the activation weight is calculated, and the activation rules of the evidence reasoning algorithm are integrated to evaluate the belief of the conclusion. The quantitative and qualitative evaluation of the energy efficiency of cloud systems is realized. The experiments show that the proposed method can accurately and objectively evaluate the energy efficiency of cloud systems.
Zebari, Rizgar R., Zeebaree, Subhi R. M., Sallow, Amira Bibo, Shukur, Hanan M., Ahmad, Omar M., Jacksi, Karwan.  2020.  Distributed Denial of Service Attack Mitigation Using High Availability Proxy and Network Load Balancing. 2020 International Conference on Advanced Science and Engineering (ICOASE). :174–179.
Nowadays, cybersecurity threat is a big challenge to all organizations that present their services over the Internet. Distributed Denial of Service (DDoS) attack is the most effective and used attack and seriously affects the quality of service of each E-organization. Hence, mitigation this type of attack is considered a persistent need. In this paper, we used Network Load Balancing (NLB) and High Availability Proxy (HAProxy) as mitigation techniques. The NLB is used in the Windows platform and HAProxy in the Linux platform. Moreover, Internet Information Service (IIS) 10.0 is implemented on Windows server 2016 and Apache 2 on Linux Ubuntu 16.04 as web servers. We evaluated each load balancer efficiency in mitigating synchronize (SYN) DDoS attack on each platform separately. The evaluation process is accomplished in a real network and average response time and average CPU are utilized as metrics. The results illustrated that the NLB in the Windows platform achieved better performance in mitigation SYN DDOS compared to HAProxy in the Linux platform. Whereas, the average response time of the Window webservers is reduced with NLB. However, the impact of the SYN DDoS on the average CPU usage of the IIS 10.0 webservers was more than those of the Apache 2 webservers.
Nweke, Livinus Obiora, Wolthusen, Stephen D..  2020.  Modelling Adversarial Flow in Software-Defined Industrial Control Networks Using a Queueing Network Model. 2020 IEEE Conference on Communications and Network Security (CNS). :1–6.
In recent years, software defined networking (SDN) has been proposed for enhancing the security of industrial control networks. However, its ability to guarantee the quality of service (QoS) requirements of such networks in the presence of adversarial flow still needs to be investigated. Queueing theory and particularly queueing network models have long been employed to study the performance and QoS characteristics of networks. The latter appears to be particularly suitable to capture the behaviour of SDN owing to the dependencies between layers, planes and components in an SDN architecture. Also, several authors have used queueing network models to study the behaviour of different application of SDN architectures, but none of the existing works have considered the strong periodic network traffic in software-defined industrial control networks. In this paper, we propose a queueing network model for softwaredefined industrial control networks, taking into account the strong periodic patterns of the network traffic in the data plane. We derive the performance measures for the analytical model and apply the queueing network model to study the effect of adversarial flow in software-defined industrial control networks.
Song, Guanglei, He, Lin, Wang, Zhiliang, Yang, Jiahai, Jin, Tao, Liu, Jieling, Li, Guo.  2020.  Towards the Construction of Global IPv6 Hitlist and Efficient Probing of IPv6 Address Space. 2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS). :1–10.
Fast IPv4 scanning has made sufficient progress in network measurement and security research. However, it is infeasible to perform brute-force scanning of the IPv6 address space. We can find active IPv6 addresses through scanning candidate addresses generated by the state-of-the-art algorithms, whose probing efficiency of active IPv6 addresses, however, is still very low. In this paper, we aim to improve the probing efficiency of IPv6 addresses in two ways. Firstly, we perform a longitudinal active measurement study over four months, building a high-quality dataset called hitlist with more than 1.3 billion IPv6 addresses distributed in 45.2k BGP prefixes. Different from previous work, we probe the announced BGP prefixes using a pattern-based algorithm, which makes our dataset overcome the problems of uneven address distribution and low active rate. Secondly, we propose an efficient address generation algorithm DET, which builds a density space tree to learn high-density address regions of the seed addresses in linear time and improves the probing efficiency of active addresses. On the public hitlist and our hitlist, we compare our algorithm DET against state-of-the-art algorithms and find that DET increases the de-aliased active address ratio by 10%, and active address (including aliased addresses) ratio by 14%, by scanning 50 million addresses.
Odero, Stephen, Dargahi, Tooska, Takruri, Haifa.  2020.  Privacy Enhanced Interface Identifiers in IPv6. 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). :1—6.
The Internet Protocol Version 6 (IPV6) proposed to replace IPV4 to solve scalability challenges and improve quality of service and security. Current implementation of IPv6 uses static value that is determined from the Media Access Control (MAC) address as the Interface Identifier (IID). This results in a deterministic IID for each user that is the same regardless of any network changes. This provides an eavesdropper with the ability to easily track the physical location of the communicating nodes using simple tools, such as ping and traceroute. Moreover, this address generation method provides a means to correlate network traffic with a specific user which can be achieved by filtering the IID and traffic analysis. These serious privacy breaches need to be addressed before widespread deployment of IPv6. In this paper we propose a privacy-enhanced method for generating IID which combines different network parameters. The proposed method generates non-deterministic IIDs that is resistance against correlation attack. We validate our approach using Wireshark, ping and traceroute tools and show that our proposed approach achieves better privacy compared to the existing IID generation methods.
Fernandez, J., Allen, B., Thulasiraman, P., Bingham, B..  2020.  Performance Study of the Robot Operating System 2 with QoS and Cyber Security Settings. 2020 IEEE International Systems Conference (SysCon). :1—6.
Throughout the Department of Defense, there are ongoing efforts to increase cybersecurity and improve data transfer in unmanned robotic systems (UxS). This paper explores the performance of the Robot Operating System (ROS) 2, which is built with the Data Distribution Service (DDS) standard as a middleware. Based on how quality of service (QoS) parameters are defined in the robotic middleware interface, it is possible to implement strict delivery requirements to different nodes on a dynamic nodal network with multiple unmanned systems connected. Through this research, different scenarios with varying QoS settings were implemented and compared to baseline values to help illustrate the impact of latency and throughput on data flow. DDS security settings were also enabled to help understand the cost of overhead and performance when secured data is compared to plaintext baseline values. Our experiments were performed using a basic ROS 2 network consisting of two nodes (one publisher and one subscriber). Our experiments showed a measurable latency and throughput change between different QoS profiles and security settings. We analyze the trends and tradeoffs associated with varying QoS and security settings. This paper provides performance data points that can be used to help future researchers and developers make informative choices when using ROS 2 for UxS.
Kim, Dong Seong, Kim, Minjune, Cho, Jin-Hee, Lim, Hyuk, Moore, Terrence J., Nelson, Frederica F..  2020.  Design and Performance Analysis of Software Defined Networking Based Web Services Adopting Moving Target Defense. 2020 50th Annual IEEE-IFIP International Conference on Dependable Systems and Networks-Supplemental Volume (DSN-S). :43—44.
Moving Target Defense (MTD) has been emerged as a promising countermeasure to defend systems against cyberattacks asymmetrically while working well with legacy security and defense mechanisms. MTD provides proactive security services by dynamically altering attack surfaces and increasing attack cost or complexity to prevent further escalation of the attack. However, one of the non-trivial hurdles in deploying MTD techniques is how to handle potential performance degradation (e.g., interruptions of service availability) and maintain acceptable quality-of-service (QoS) in an MTD-enabled system. In this paper, we derive the service performance metrics (e.g., an extent of failed jobs) to measure how much performance degradation is introduced due to MTD operations, and propose QoS-aware service strategies (i.e., drop and wait) to manage ongoing jobs with the minimum performance degradation even under MTD operations running. We evaluate the service performance of software-defined networking (SDN)-based web services (i.e., Apache web servers). Our experimental results prove that the MTD-enabled system can minimize performance degradation by using the proposed job management strategies. The proposed strategies aim to optimize a specific service configuration (e.g., types of jobs and request rates) and effectively minimize the adverse impact of deploying MTD in the system with acceptable QoS while retaining the security effect of IP shuffling-based MTD.
Driss, Maha, Aljehani, Amani, Boulila, Wadii, Ghandorh, Hamza, Al-Sarem, Mohammed.  2020.  Servicing Your Requirements: An FCA and RCA-Driven Approach for Semantic Web Services Composition. IEEE Access. 8:59326—59339.
The evolution of Service-Oriented Computing (SOC) provides more efficient software development methods for building and engineering new value-added service-based applications. SOC is a computing paradigm that relies on Web services as fundamental elements. Research and technical advancements in Web services composition have been considered as an effective opportunity to develop new service-based applications satisfying complex requirements rapidly and efficiently. In this paper, we present a novel approach enhancing the composition of semantic Web services. The novelty of our approach, as compared to others reported in the literature, rests on: i) mapping user's/organization's requirements with Business Process Modeling Notation (BPMN) and semantic descriptions using ontologies, ii) considering functional requirements and also different types of non-functional requirements, such as quality of service (QoS), quality of experience (QoE), and quality of business (QoBiz), iii) using Formal Concept Analysis (FCA) technique to select the optimal set of Web services, iv) considering composability levels between sequential Web services using Relational Concept Analysis (RCA) technique to decrease the required adaptation efforts, and finally, v) validating the obtained service-based applications by performing an analytical technique, which is the monitoring. The approach experimented on an extended version of the OWLS-TC dataset, which includes more than 10830 Web services descriptions from various domains. The obtained results demonstrate that our approach allows to successfully and effectively compose Web services satisfying different types of user's functional and non-functional requirements.
Miatra, Ayati, Kumar, Sumit.  2020.  Security Issues With Fog Computing. 2020 10th International Conference on Cloud Computing, Data Science Engineering (Confluence). :123–128.
Fog computing or edge computing or fogging extends cloud computing to the edge of the network. It operates on the computing, storage and networking services between user-end devices and cloud computing data centres. However, in the process of caring out these operations, fog computing is faced with several security issues. These issues may be inherited from cloud computing systems or may arise due to fog computing systems alone. Some of the major gaps in providing a secure platform for the fog computing process arise from interim operational steps like authentication or identification, which often expands to large scale performance issues in fog computing. Thus, these issues and their implications on fog computing databases, and the possible available solutions are researched and provided for a better scope of future use and growth of fog computing systems by bridging the gaps of security issues in it.
Liu, Zhibin, Liu, Ziang, Huang, Yuanyuan, Liu, Xin, Zhou, Xiaokang, Zhou, Rui.  2020.  A Research of Distributed Security and QoS Testing Framework. 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :174—181.
Since the birth of the Internet, the quality of network service has been a widespread concerned problem. With the continuous development of communication and information technology, people gradually realized that the contradiction between the limited resources and the business requirements of network cannot be fundamentally solved. In this paper, we design and develop a distributed security quality of service testing framework called AweQoS(AwesomeQoS), to adapt to the current complex network environment. This paper puts forward the necessity that some security tests should be closely combined with quality of service testing, and further discusses the basic methods of distributed denial of service attack and defense. We introduce the design idea and working process of AweQoS in detail, and introduce a bandwidth test method based on user datagram protocol. Experimental results show that this new test method has better test performance and potential under the AweQoS framework.
Hasslinger, Gerhard, Ntougias, Konstantinos, Hasslinger, Frank, Hohlfeld, Oliver.  2020.  General Knapsack Bounds of Web Caching Performance Regarding the Properties of each Cacheable Object. 2020 IFIP Networking Conference (Networking). :821–826.
Caching strategies have been evaluated and compared in many studies, most often via simulation, but also in analytic methods. Knapsack solutions provide a general analytical approach for upper bounds on web caching performance. They assume objects of maximum (value/size) ratio being selected as cache content, with flexibility to define the caching value. Therefore the popularity, cost, size, time-to-live restrictions etc. per object can be included an overall caching goal, e.g., for reducing delay and/or transport path length in content delivery. The independent request model (IRM) leads to basic knapsack bounds for static optimum cache content. We show that a 2-dimensional (2D-)knapsack solution covers arbitrary request pattern, which selects dynamically changing content yielding maximum caching value for any predefined request sequence. Moreover, Belady's optimum strategy for clairvoyant caching is identified as a special case of our 2D-knapsack solution when all objects are unique. We also summarize a comprehensive picture of the demands and efficiency criteria for web caching, including updating speed and overheads. Our evaluations confirm significant performance gaps from LRU to advanced GreedyDual and score-based web caching methods and to the knapsack bounds.
Samriya, Jitendra Kumar, Kumar, Narander.  2020.  Fuzzy Ant Bee Colony For Security And Resource Optimization In Cloud Computing. 2020 5th International Conference on Computing, Communication and Security (ICCCS). :1—5.

Cloud computing (CC) systems prevail to be the widespread computational paradigms for offering immense scalable and elastic services. Computing resources in cloud environment should be scheduled to facilitate the providers to utilize the resources moreover the users could get low cost applications. The most prominent need in job scheduling is to ensure Quality of service (QoS) to the user. In the boundary of the third party the scheduling takes place hence it is a significant condition for assuring its security. The main objective of our work is to offer QoS i.e. cost, makespan, minimized migration of task with security enforcement moreover the proposed algorithm guarantees that the admitted requests are executed without violating service level agreement (SLA). These objectives are attained by the proposed Fuzzy Ant Bee Colony algorithm. The experimental outcome confirms that secured job scheduling objective with assured QoS is attained by the proposed algorithm.

Sarma, M. S., Srinivas, Y., Abhiram, M., Ullala, L., Prasanthi, M. S., Rao, J. R..  2017.  Insider Threat Detection with Face Recognition and KNN User Classification. 2017 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM). :39—44.
Information Security in cloud storage is a key trepidation with regards to Degree of Trust and Cloud Penetration. Cloud user community needs to ascertain performance and security via QoS. Numerous models have been proposed [2] [3] [6][7] to deal with security concerns. Detection and prevention of insider threats are concerns that also need to be tackled. Since the attacker is aware of sensitive information, threats due to cloud insider is a grave concern. In this paper, we have proposed an authentication mechanism, which performs authentication based on verifying facial features of the cloud user, in addition to username and password, thereby acting as two factor authentication. New QoS has been proposed which is capable of monitoring and detection of insider threats using Machine Learning Techniques. KNN Classification Algorithm has been used to classify users into legitimate, possibly legitimate, possibly not legitimate and not legitimate groups to verify image authenticity to conclude, whether there is any possible insider threat. A threat detection model has also been proposed for insider threats, which utilizes Facial recognition and Monitoring models. Security Method put forth in [6] [7] is honed to include threat detection QoS to earn higher degree of trust from cloud user community. As a recommendation, Threat detection module should be harnessed in private cloud deployments like Defense and Pharma applications. Experimentation has been conducted using open source Machine Learning libraries and results have been attached in this paper.
Nguyen, Q. N., Lopez, J., Tsuda, T., Sato, T., Nguyen, K., Ariffuzzaman, M., Safitri, C., Thanh, N. H..  2020.  Adaptive Caching for Beneficial Content Distribution in Information-Centric Networking. 2020 International Conference on Information Networking (ICOIN). :535–540.
Currently, little attention has been carried out to address the feasibility of in-network caching in Information-Centric Networking (ICN) for the design and real-world deployment of future networks. Towards this line, in this paper, we propose a beneficial caching scheme in ICN by storing no more than a specific number of replicas for each content. Particularly, to realize an optimal content distribution for deploying caches in ICN, a content can be cached either partially or as a full-object corresponding to its request arrival rate and data traffic. Also, we employ a utility-based replacement in each content node to keep the most recent and popular content items in the ICN interconnections. The evaluation results show that the proposal improves the cache hit rate and cache diversity considerably, and acts as a beneficial caching approach for network and service providers in ICN. Specifically, the proposed caching mechanism is easy to deploy, robust, and relevant for the content-based providers by enabling them to offer users high Quality of Service (QoS) and gain benefits at the same time.
Liao, S., Wu, J., Li, J., Bashir, A. K..  2020.  Proof-of-Balance: Game-Theoretic Consensus for Controller Load Balancing of SDN. IEEE INFOCOM 2020 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). :231–236.
Software Defined Networking (SDN) focus on the isolation of control plane and data plane, greatly enhancing the network's support for heterogeneity and flexibility. However, although the programmable network greatly improves the performance of all aspects of the network, flexible load balancing across controllers still challenges the current SDN architecture. Complex application scenarios lead to flexible and changeable communication requirements, making it difficult to guarantee the Quality of Service (QoS) for SDN users. To address this issue, this paper proposes a paradigm that uses blockchain to incentive safe load balancing for multiple controllers. We proposed a controller consortium blockchain for secure and efficient load balancing of multi-controllers, which includes a new cryptographic currency balance coin and a novel consensus mechanism Proof-of-Balance (PoB). In addition, we have designed a novel game theory-based incentive mechanism to incentive controllers with tight communication resources to offload tasks to idle controllers. The security analysis and performance simulation results indicate the superiority and effectiveness of the proposed scheme.
Sharma, P., Nair, J., Singh, R..  2020.  Adaptive Flow-Level Scheduling for the IoT MAC. 2020 International Conference on COMmunication Systems NETworkS (COMSNETS). :515—518.

Over the past decade, distributed CSMA, which forms the basis for WiFi, has been deployed ubiquitously to provide seamless and high-speed mobile internet access. However, distributed CSMA might not be ideal for future IoT/M2M applications, where the density of connected devices/sensors/controllers is expected to be orders of magnitude higher than that in present wireless networks. In such high-density networks, the overhead associated with completely distributed MAC protocols will become a bottleneck. Moreover, IoT communications are likely to have strict QoS requirements, for which the `best-effort' scheduling by present WiFi networks may be unsuitable. This calls for a clean-slate redesign of the wireless MAC taking into account the requirements for future IoT/M2M networks. In this paper, we propose a reservation-based (for minimal overhead) wireless MAC designed specifically with IoT/M2M applications in mind.

Morozov, M. Y., Perfilov, O. Y., Malyavina, N. V., Teryokhin, R. V., Chernova, I. V..  2020.  Combined Approach to SSDF-Attacks Mitigation in Cognitive Radio Networks. 2020 Systems of Signals Generating and Processing in the Field of on Board Communications. :1–4.
Cognitive radio systems aim to solve the issue of spectrum scarcity through implementation of dynamic spectrum management and cooperative spectrum access. However, the structure of such systems introduced unique types of vulnerabilities and attacks, one of which is spectrum sensing data falsification attack (SSDF). In such attacks malicious users provide incorrect observations to the fusion center of the system, which may result in severe quality of service degradation and interference for licensed users. In this paper we investigate this type of attacks and propose a combined approach to their mitigation. On the first step a reputational method is used to isolate the initially untrustworthy nodes, on the second step specialized q-out-of-m fusion rule is utilized to mitigate the remains of attack. In this paper we present theoretical analysis of the proposed combined method.
Le, T. V., Huan, T. T..  2020.  Computational Intelligence Towards Trusted Cloudlet Based Fog Computing. 2020 5th International Conference on Green Technology and Sustainable Development (GTSD). :141—147.

The current trend of IoT user is toward the use of services and data externally due to voluminous processing, which demands resourceful machines. Instead of relying on the cloud of poor connectivity or a limited bandwidth, the IoT user prefers to use a cloudlet-based fog computing. However, the choice of cloudlet is solely dependent on its trust and reliability. In practice, even though a cloudlet possesses a required trusted platform module (TPM), we argue that the presence of a TPM is not enough to make the cloudlet trustworthy as the TPM supports only the primitive security of the bootstrap. Besides uncertainty in security, other uncertain conditions of the network (e.g. network bandwidth, latency and expectation time to complete a service request for cloud-based services) may also prevail for the cloudlets. Therefore, in order to evaluate the trust value of multiple cloudlets under uncertainty, this paper broadly proposes the empirical process for evaluation of trust. This will be followed by a measure of trust-based reputation of cloudlets through computational intelligence such as fuzzy logic and ant colony optimization (ACO). In the process, fuzzy logic-based inference and membership evaluation of trust are presented. In addition, ACO and its pheromone communication across different colonies are being modeled with multiple cloudlets. Finally, a measure of affinity or popular trust and reputation of the cloudlets is also proposed. Together with the context of application under multiple cloudlets, the computationally intelligent approaches have been investigated in terms of performance. Hence the contribution is subjected towards building a trusted cloudlet-based fog platform.

Chakravorty, R., Prakash, J..  2020.  A Review on Prevention and Detection Schemes for Black Hole Attacks in MANET. 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). :801–806.
Mobile Ad hoc Network (MANET) is one of the emerging technologies to communicate between nodes and its decentralized structure, self-configuring nature are the few properties of this Ad hoc network. Due to its undefined structure, it has found its usage in the desired and temporary communication network. MANET has many routing protocols governing it and due to its changing topology, there can be many issues arise in recent times. Problems like no central node, limited energy, and the quality of service, performance, design issues, and security challenges have been bugging the researchers. The black hole attacks are the kind that cause ad hoc network to be at loss of information and make the source to believe that it has the actual least distance path to the destination, but in real scenario the packets do not get forwarded to neighbouring nodes. In this paper, we have discussed different solutions over the past years to deal with such attacks. A summary of the schemes with their results and drawbacks in terms of performance metrics is also given.
Omprakash, S. H., Suthar, M. K..  2020.  Mitigation Technique for Black hole Attack in Mobile Ad hoc Network. 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT). :1–5.
Mobile Ad hoc Network is a very important key technology for device to device communication without any support of extra infrastructure. As it is being used as a mode of communication in various fields, protecting the network from various attacks becomes more important. In this research paper, we have created a real network scenario using random mobility of nodes and implemented Black hole Attack and Gray hole Attack, which degrades the performance of the network. In our research, we have found a novel mitigation technique which is efficient to mitigate both the attack from the network.
Fiade, A., Triadi, A. Yudha, Sulhi, A., Masruroh, S. Ummi, Handayani, V., Suseno, H. Bayu.  2020.  Performance Analysis of Black Hole Attack and Flooding Attack AODV Routing Protocol on VANET (Vehicular Ad-Hoc Network). 2020 8th International Conference on Cyber and IT Service Management (CITSM). :1–5.
Wireless technology is widely used today and is growing rapidly. One of the wireless technologies is VANET where the network can communicate with vehicles (V2V) which can prevent accidents on the road. Energy is also a problem in VANET so it needs to be used efficiently. The presence of malicious nodes or nodes can eliminate and disrupt the process of data communication. The routing protocol used in this study is AODV. The purpose of this study is to analyze the comparison of blackhole attack and flooding attack against energy-efficient AODV on VANET. This research uses simulation methods and several supporting programs such as OpenStreetMap, SUMO, NS2, NAM, and AWK to test the AODV routing protocol. Quality of service (QOS) parameters used in this study are throughput, packet loss, and end to end delay. Energy parameters are also used to examine the energy efficiency used. This study uses the number of variations of nodes consisting of 20 nodes, 40 nodes, 60 nodes, and different network conditions, namely normal network conditions, network conditions with black hole attacks, and network conditions with flooding attacks. The results obtained can be concluded that the highest value of throughput when network conditions are normal, the greatest value of packet loss when there is a black hole attack, the highest end to end delay value and the largest remaining energy when there is a flooding attack.
Carrozzo, G., Siddiqui, M. S., Betzler, A., Bonnet, J., Perez, G. M., Ramos, A., Subramanya, T..  2020.  AI-driven Zero-touch Operations, Security and Trust in Multi-operator 5G Networks: a Conceptual Architecture. 2020 European Conference on Networks and Communications (EuCNC). :254—258.
The 5G network solutions currently standardised and deployed do not yet enable the full potential of pervasive networking and computing envisioned in 5G initial visions: network services and slices with different QoS profiles do not span multiple operators; security, trust and automation is limited. The evolution of 5G towards a truly production-level stage needs to heavily rely on automated end-to-end network operations, use of distributed Artificial Intelligence (AI) for cognitive network orchestration and management and minimal manual interventions (zero-touch automation). All these elements are key to implement highly pervasive network infrastructures. Moreover, Distributed Ledger Technologies (DLT) can be adopted to implement distributed security and trust through Smart Contracts among multiple non-trusted parties. In this paper, we propose an initial concept of a zero-touch security and trust architecture for ubiquitous computing and connectivity in 5G networks. Our architecture aims at cross-domain security & trust orchestration mechanisms by coupling DLTs with AI-driven operations and service lifecycle automation in multi-tenant and multi-stakeholder environments. Three representative use cases are identified through which we will validate the work which will be validated in the test facilities at 5GBarcelona and 5TONIC/Madrid.
Saputra, R., Andika, J., Alaydrus, M..  2020.  Detection of Blackhole Attack in Wireless Sensor Network Using Enhanced Check Agent. 2020 Fifth International Conference on Informatics and Computing (ICIC). :1–4.

Wireless Sensor Network (WSN) is a heterogeneous type of network consisting of scattered sensor nodes and working together for data collection, processing, and transmission functions[1], [2]. Because WSN is widely used in vital matters, aspects of its security must also be considered. There are many types of attacks that might be carried out to disrupt WSN networks. The methods of attack that exist in WSN include jamming attack, tampering, Sybil attack, wormhole attack, hello flood attack, and, blackhole attack[3]. Blackhole attacks are one of the most dangerous attacks on WSN networks. Enhanced Check Agent method is designed to detect black hole attacks by sending a checking agent to record nodes that are considered black okay. The implementation will be tested right on a wireless sensor network using ZigBee technology. Network topology uses a mesh where each node can have more than one routing table[4]. The Enhanced Check Agent method can increase throughput to 100 percent.

Abdelaal, M., Karadeniz, M., Dürr, F., Rothermel, K..  2020.  liteNDN: QoS-Aware Packet Forwarding and Caching for Named Data Networks. 2020 IEEE 17th Annual Consumer Communications Networking Conference (CCNC). :1–9.
Recently, named data networking (NDN) has been introduced to connect the world of computing devices via naming data instead of their containers. Through this strategic change, NDN brings several new features to network communication, including in-network caching, multipath forwarding, built-in multicast, and data security. Despite these unique features of NDN networking, there exist plenty of opportunities for continuing developments, especially with packet forwarding and caching. In this context, we introduce liteNDN, a novel forwarding and caching strategy for NDN networks. liteNDN comprises a cooperative forwarding strategy through which NDN routers share their knowledge, i.e. data names and interfaces, to optimize their packet forwarding decisions. Subsequently, liteNDN leverages that knowledge to estimate the probability of each downstream path to swiftly retrieve the requested data. Additionally, liteNDN exploits heuristics, such as routing costs and data significance, to make proper decisions about caching normal as well as segmented packets. The proposed approach has been extensively evaluated in terms of the data retrieval latency, network utilization, and the cache hit rate. The results showed that liteNDN, compared to conventional NDN forwarding and caching strategies, achieves much less latency while reducing the unnecessary traffic and caching activities.
Abdulkarem, H. S., Dawod, A..  2020.  DDoS Attack Detection and Mitigation at SDN Data Plane Layer. 2020 2nd Global Power, Energy and Communication Conference (GPECOM). :322—326.
In the coming future, Software-defined networking (SDN) will become a technology more responsive, fully automated, and highly secure. SDN is a way to manage networks by separate the control plane from the forwarding plane, by using software to manage network functions through a centralized control point. A distributed denial-of-service (DDoS) attack is the most popular malicious attempt to disrupt normal traffic of a targeted server, service, or network. The problem of the paper is the DDoS attack inside the SDN environment and how could use SDN specifications through the advantage of Open vSwitch programmability feature to stop the attack. This paper presents DDoS attack detection and mitigation in the SDN data-plane by applying a written SDN application in python language, based on the malicious traffic abnormal behavior to reduce the interference with normal traffic. The evaluation results reveal detection and mitigation time between 100 to 150 sec. The work also sheds light on the programming relevance with the open daylight controller over an abstracted view of the network infrastructure.