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2022-05-24
Grewe, Dennis, Wagner, Marco, Ambalavanan, Uthra, Liu, Liming, Nayak, Naresh, Schildt, Sebastian.  2021.  On the Design of an Information-Centric Networking Extension for IoT APIs. 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall). :1–6.
Both the Internet of Things (IoT) and Information Centric Networking (ICN) have gathered a lot of attention from both research and industry in recent years. While ICN has proved to be beneficial in many situations, it is not widely deployed outside research projects, also not addressing needs of IoT application programming interfaces (APIs). On the other hand, today's IoT solutions are built on top of the host-centric communication model associated with the usage of the Internet Protocol (IP). This paper contributes a discussion on the need of an integration of a specific form of IoT APIs, namely WebSocket based streaming APIs, into an ICN. Furthermore, different access models are discussed and requirements are derived from real world APIs. Finally, the design of an ICN-style extension is presented using one of the examined APIs.
Safitri, Cutifa, Nguyen, Quang Ngoc, Deo Lumoindong, Christoforus Williem, Ayu, Media Anugerah, Mantoro, Teddy.  2021.  Advanced Forwarding Strategy Towards Delay Tolerant Information-Centric Networking. 2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED). :1–5.
Information-Centric Networking (ICN) is among the promising architecture that can drive the need and versatility towards the future generation (xG) needs. In the future, support for network communication relies on the area of telemedicine, autonomous vehicles, and disaster recovery. In the disaster recovery case, there is a high possibility where the communication path is severed. Multicast communication and DTN-friendly route algorithm are becoming suitable options to send a packet message to get a faster response and to see any of the nodes available for service, this approach could give burden to the core network. Also, during disaster cases, many people would like to communicate, receive help, and find family members. Flooding the already disturbed/severed network will further reduce communication performance efficiency even further. Thus, this study takes into consideration prioritization factors to allow networks to process and delivering priority content. For this purpose, the proposed technique introduces the Routable Prefix Identifier (RP-ID) that takes into account the prioritization factor to enable optimization in Delay Tolerant ICN communication.
Huang, Yudong, Wang, Shuo, Feng, Tao, Wang, Jiasen, Huang, Tao, Huo, Ru, Liu, Yunjie.  2021.  Towards Network-Wide Scheduling for Cyclic Traffic in IP-based Deterministic Networks. 2021 4th International Conference on Hot Information-Centric Networking (HotICN). :117–122.
The emerging time-sensitive applications, such as industrial automation, smart grids, and telesurgery, pose strong demands for enabling large-scale IP-based deterministic networks. The IETF DetNet working group recently proposes a Cycle Specified Queuing and Forwarding (CSQF) solution. However, CSQF only specifies an underlying device-level primitive while how to achieve network-wide flow scheduling remains undefined. Previous scheduling mechanisms are mostly oriented to the context of local area networks, making them inapplicable to the cyclic traffic in wide area networks. In this paper, we design the Cycle Tags Planning (CTP) mechanism, a first mathematical model to enable network-wide scheduling for cyclic traffic in large-scale deterministic networks. Then, a novel scheduling algorithm named flow offset and cycle shift (FO-CS) is designed to compute the flows' cycle tags. The FO-CS algorithm is evaluated under long-distance network topologies in remote industrial control scenarios. Compared with the Naive algorithm without using FO-CS, simulation results demonstrate that FO-CS improves the scheduling flow number by 31.2% in few seconds.
Nakamura, Ryo, Kamiyama, Noriaki.  2021.  Proposal of Keyword-Based Information-Centric Delay-Tolerant Network. 2021 IEEE International Workshop Technical Committee on Communications Quality and Reliability (CQR 2021). :1–7.
In this paper, we focus on Information-Centric Delay-Tolerant Network (ICDTN), which incorporates the communication paradigm of Information-Centric Networking (ICN) into Delay-Tolerant Networking (DTN). Conventional ICNs adopt a naming scheme that names the content with the content identifier. However, a past study proposed an alternative naming scheme that describes the name of content with the content descriptor. We believe that, in ICDTN, it is more suitable to utilize the approach using the content descriptor. In this paper, we therefore propose keyword-based ICDTN that resolves content requests and deliveries contents based on keywords, i.e., content descriptor, in the request and response messages.
Lei, Kai, Ye, Hao, Liang, Yuzhi, Xiao, Jing, Chen, Peiwu.  2021.  Towards a Translation-Based Method for Dynamic Heterogeneous Network Embedding. ICC 2021 - IEEE International Conference on Communications. :1–6.
Network embedding, which aims to map the discrete network topology to a continuous low-dimensional representation space with the major topological properties preserved, has emerged as an essential technique to support various network inference tasks. However, incorporating both the evolutionary nature and the network's heterogeneity remains a challenge for existing network embedding methods. In this study, we propose a novel Translation-Based Dynamic Heterogeneous Network Embedding (TransDHE) approach to consider both the aspects simultaneously. For a dynamic heterogeneous network with a sequence of snapshots and multiple types of nodes and edges, we introduce a translation-based embedding module to capture the heterogeneous characteristics (e.g., type information) of each single snapshot. An orthogonal alignment module and RNN-based aggregation module are then applied to explore the evolutionary patterns among multiple successive snapshots for the final representation learning. Extensive experiments on a set of real-world networks demonstrate that TransDHE can derive the more informative embedding result for the network dynamic and heterogeneity over state-of-the-art network embedding baselines.
Fazea, Yousef, Mohammed, Fathey, Madi, Mohammed, Alkahtani, Ammar Ahmed.  2021.  Review on Network Function Virtualization in Information-Centric Networking. 2021 International Conference of Technology, Science and Administration (ICTSA). :1–6.
Network function virtualization (NFV / VNF) and information-centric networking (ICN) are two trending technologies that have attracted expert's attention. NFV is a technique in which network functions (NF) are decoupling from commodity hardware to run on to create virtual communication services. The virtualized class nodes can bring several advantages such as reduce Operating Expenses (OPEX) and Capital Expenses (CAPEX). On the other hand, ICN is a technique that breaks the host-centric paradigm and shifts the focus to “named information” or content-centric. ICN provides highly efficient content retrieval network architecture where popular contents are cached to minimize duplicate transmissions and allow mobile users to access popular contents from caches of network gateways. This paper investigates the implementation of NFV in ICN. Besides, reviewing and discussing the weaknesses and strengths of each architecture in a critical analysis manner of both network architectures. Eventually, highlighted the current issues and future challenges of both architectures.
Pellenz, Marcelo E., Lachowski, Rosana, Jamhour, Edgard, Brante, Glauber, Moritz, Guilherme Luiz, Souza, Richard Demo.  2021.  In-Network Data Aggregation for Information-Centric WSNs using Unsupervised Machine Learning Techniques. 2021 IEEE Symposium on Computers and Communications (ISCC). :1–7.
IoT applications are changing our daily lives. These innovative applications are supported by new communication technologies and protocols. Particularly, the information-centric network (ICN) paradigm is well suited for many IoT application scenarios that involve large-scale wireless sensor networks (WSNs). Even though the ICN approach can significantly reduce the network traffic by optimizing the process of information recovery from network nodes, it is also possible to apply data aggregation strategies. This paper proposes an unsupervised machine learning-based data aggregation strategy for multi-hop information-centric WSNs. The results show that the proposed algorithm can significantly reduce the ICN data traffic while having reduced information degradation.
Raza, Khuhawar Arif, Asheralieva, Alia, Karim, Md Monjurul, Sharif, Kashif, Gheisari, Mehdi, Khan, Salabat.  2021.  A Novel Forwarding and Caching Scheme for Information-Centric Software-Defined Networks. 2021 International Symposium on Networks, Computers and Communications (ISNCC). :1–8.
This paper integrates Software-Defined Networking (SDN) and Information -Centric Networking (ICN) framework to enable low latency-based stateful routing and caching management by leveraging a novel forwarding and caching strategy. The framework is implemented in a clean- slate environment that does not rely on the TCP/IP principle. It utilizes Pending Interest Tables (PIT) instead of Forwarding Information Base (FIB) to perform data dissemination among peers in the proposed IC-SDN framework. As a result, all data exchanged and cached in the system are organized in chunks with the same interest resulting in reduced packet overhead costs. Additionally, we propose an efficient caching strategy that leverages in- network caching and naming of contents through an IC-SDN controller to support off- path caching. The testbed evaluation shows that the proposed IC-SDN implementation achieves an increased throughput and reduced latency compared to the traditional information-centric environment, especially in the high load scenarios.
Sukjaimuk, Rungrot, Nguyen, Quang N., Sato, Takuro.  2021.  An Efficient Congestion Control Model utilizing IoT wireless sensors in Information-Centric Networks. 2021 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunication Engineering. :210–213.
Congestion control is one of the essential keys to enhance network efficiency so that the network can perform well even in the case of packet drop. This problem is even more challenging in Information-Centric Networking (ICN), a typical Future Internet design, which employs the packet flooding policy for forwarding the information. To diminish the high traffic load due to the huge number of packets in the era of the Internet of Things (IoT), this paper proposes an effective caching and forwarding algorithm to diminish the congestion rate of the IoT wireless sensor in ICN. The proposed network system utilizes accumulative popularity-based delay transmission time for forwarding strategy and includes the consecutive chunks-based segment caching scheme. The evaluation results using ndnSIM, a widely-used ns-3 based ICN simulator, demonstrated that the proposed system can achieve less interest packet drop rate, more cache hit rate, and higher network throughput, compared to the relevant ICN-based benchmarks. These results prove that the proposed ICN design can achieve higher network efficiency with a lower congestion rate than that of the other related ICN systems using IoT sensors.
Fazea, Yousef, Mohammed, Fathey.  2021.  Software Defined Networking based Information Centric Networking: An Overview of Approaches and Challenges. 2021 International Congress of Advanced Technology and Engineering (ICOTEN). :1–8.
ICN (Information-Centric Networking) is a traditional networking approach which focuses on Internet design, while SDN (Software Defined Networking) is known as a speedy and flexible networking approach. Integrating these two approaches can solve different kinds of traditional networking problems. On the other hand, it may expose new challenges. In this paper, we study how these two networking approaches are been combined to form SDN-based ICN architecture to improve network administration. Recent research is explored to identify the SDN-based ICN challenges, provide a critical analysis of the current integration approaches, and determine open issues for further research.
Daughety, Nathan, Pendleton, Marcus, Xu, Shouhuai, Njilla, Laurent, Franco, John.  2021.  vCDS: A Virtualized Cross Domain Solution Architecture. MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM). :61–68.
With the paradigm shift to cloud-based operations, reliable and secure access to and transfer of data between differing security domains has never been more essential. A Cross Domain Solution (CDS) is a guarded interface which serves to execute the secure access and/or transfer of data between isolated and/or differing security domains defined by an administrative security policy. Cross domain security requires trustworthiness at the confluence of the hardware and software components which implement a security policy. Security components must be relied upon to defend against widely encompassing threats – consider insider threats and nation state threat actors which can be both onsite and offsite threat actors – to information assurance. Current implementations of CDS systems use suboptimal Trusted Computing Bases (TCB) without any formal verification proofs, confirming the gap between blind trust and trustworthiness. Moreover, most CDSs are exclusively operated by Department of Defense agencies and are not readily available to the commercial sectors, nor are they available for independent security verification. Still, more CDSs are only usable in physically isolated environments such as Sensitive Compartmented Information Facilities and are inconsistent with the paradigm shift to cloud environments. Our purpose is to address the question of how trustworthiness can be implemented in a remotely deployable CDS that also supports availability and accessibility to all sectors. In this paper, we present a novel CDS system architecture which is the first to use a formally verified TCB. Additionally, our CDS model is the first of its kind to utilize a computation-isolation approach which allows our CDS to be remotely deployable for use in cloud-based solutions.
Liu, Yizhong, Xia, Yu, Liu, Jianwei, Hei, Yiming.  2021.  A Secure and Decentralized Reconfiguration Protocol For Sharding Blockchains. 2021 7th IEEE Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS). :111–116.
Most present reconfiguration methods in sharding blockchains rely on a secure randomness, whose generation might be complicated. Besides, a reference committee is usually in charge of the reconfiguration, making the process not decentralized. To address the above issues, this paper proposes a secure and decentralized shard reconfiguration protocol, which allows each shard to complete the selection and confirmation of its own shard members in turn. The PoW mining puzzle is calculated using the public key hash value in the member list confirmed by the last shard. Through the mining and shard member list commitment process, each shard can update its members safely and efficiently once in a while. Furthermore, it is proved that our protocol satisfies the safety, consistency, liveness, and decentralization properties. The honest member proportion in each confirmed shard member list is guaranteed to exceed a certain safety threshold, and all honest nodes have an identical view on the list. The reconfiguration is ensured to make progress, and each node has the same right to participate in the process. Our secure and decentralized shard reconfiguration protocol could be applied to all committee-based sharding blockchains.
Boulemtafes, Amine, Derhab, Abdelouahid, Ali Braham, Nassim Ait, Challal, Yacine.  2021.  PReDIHERO – Privacy-Preserving Remote Deep Learning Inference based on Homomorphic Encryption and Reversible Obfuscation for Enhanced Client-side Overhead in Pervasive Health Monitoring. 2021 IEEE/ACS 18th International Conference on Computer Systems and Applications (AICCSA). :1–8.
Homomorphic Encryption is one of the most promising techniques to deal with privacy concerns, which is raised by remote deep learning paradigm, and maintain high classification accuracy. However, homomorphic encryption-based solutions are characterized by high overhead in terms of both computation and communication, which limits their adoption in pervasive health monitoring applications with constrained client-side devices. In this paper, we propose PReDIHERO, an improved privacy-preserving solution for remote deep learning inferences based on homomorphic encryption. The proposed solution applies a reversible obfuscation technique that successfully protects sensitive information, and enhances the client-side overhead compared to the conventional homomorphic encryption approach. The solution tackles three main heavyweight client-side tasks, namely, encryption and transmission of private data, refreshing encrypted data, and outsourcing computation of activation functions. The efficiency of the client-side is evaluated on a healthcare dataset and compared to a conventional homomorphic encryption approach. The evaluation results show that PReDIHERO requires increasingly less time and storage in comparison to conventional solutions when inferences are requested. At two hundreds inferences, the improvement ratio could reach more than 30 times in terms of computation overhead, and more than 8 times in terms of communication overhead. The same behavior is observed in sequential data and batch inferences, as we record an improvement ratio of more than 100 times in terms of computation overhead, and more than 20 times in terms of communication overhead.
Chan, Matthew.  2021.  Bare-metal hypervisor virtual servers with a custom-built automatic scheduling system for educational use. 2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT). :1–5.
In contrast to traditional physical servers, a custom-built system utilizing a bare-metal hypervisor virtual server environment provides advantages of both cost savings and flexibility in terms of systems configuration. This system is designed to facilitate hands-on experience for Computer Science students, particularly those specializing in systems administration and computer networking. This multi-purpose and functional system uses an automatic advanced virtual server reservation system (AAVSRsv), written in C++, to schedule and manage virtual servers. The use of such a system could be extended to additional courses focusing on such topics as cloud computing, database systems, information assurance, as well as ethical hacking and system defense. The design can also be replicated to offer training sessions to other information technology professionals.
Khan, Mohd, Chen, Yu.  2021.  A Randomized Switched-Mode Voltage Regulation System for IoT Edge Devices to Defend Against Power Analysis based Side Channel Attacks. 2021 IEEE Intl Conf on Parallel Distributed Processing with Applications, Big Data Cloud Computing, Sustainable Computing Communications, Social Computing Networking (ISPA/BDCloud/SocialCom/SustainCom). :1771–1776.
The prevalence of Internet of Things (IoT) allows heterogeneous and lightweight smart devices to collaboratively provide services with or without human intervention. With an ever-increasing presence of IoT-based smart applications and their ubiquitous visibility from the Internet, user data generated by highly connected smart IoT devices also incur more concerns on security and privacy. While a lot of efforts are reported to develop lightweight information assurance approaches that are affordable to resource-constrained IoT devices, there is not sufficient attention paid from the aspect of security solutions against hardware-oriented attacks, i.e. side channel attacks. In this paper, a COTS (commercial off-the-shelf) based Randomized Switched-Mode Voltage Regulation System (RSMVRS) is proposed to prevent power analysis based side channel attacks (P-SCA) on bare metal IoT edge device. The RSMVRS is implemented to direct power to IoT edge devices. The power is supplied to the target device by randomly activating power stages with random time delays. Therefore, the cryptography algorithm executing on the IoT device will not correlate to a predictable power profile, if an adversary performs a SCA by measuring the power traces. The RSMVRS leverages COTS components and experimental study has verified the correctness and effectiveness of the proposed solution.
Aranha, Helder, Masi, Massimiliano, Pavleska, Tanja, Sellitto, Giovanni Paolo.  2021.  Securing the metrological chain in IoT environments: an architectural framework. 2021 IEEE International Workshop on Metrology for Industry 4.0 IoT (MetroInd4.0 IoT). :704–709.
The Internet of Things (IoT) paradigm, with its highly distributed and interconnected architecture, is gaining ground in Industry 4.0 and in critical infrastructures like the eHealth sector, the Smart Grid, Intelligent Power Plants and Smart Mobility. In these critical sectors, the preservation of metrological characteristics and their traceability is a strong legal requirement, just like cyber-security, since it offers the ground for liability. Any vulnerability in the system in which the metrological network is embedded can endanger human lives, the environment or entire economies. This paper presents a framework comprised of a methodology and some tools for the governance of the metrological chain. The proposed methodology combines the RAMI 4.0 model, which is a Reference Architecture used in the field of Industrial Internet of Things (IIoT), with the the Reference Model for Information Assurance & Security (RMIAS), a framework employed to guarantee information assurance and security, merging them with the well established paradigms to preserve calibration and referability of metrological instruments. Thus, metrological traceability and cyber-security are taken into account straight from design time, providing a conceptual space to achieve security by design and to support the maintenance of the metrological chain over the entire system lifecycle. The framework lends itself to be completely automatized with Model Checking to support automatic detection of non conformity and anomalies at run time.
Qin, Yishuai, Xiao, Bing, Li, Yaodong, Yu, Jintao.  2021.  Structure adjustment of early warning information system based on timeliness. 2021 IEEE 5th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). 5:2742–2747.
Aimed at the high requirement of timeliness in the process of information assurance, this paper describes the average time delay of information transmission in the system, and designs a timeliness index that can quantitatively describe the ability of early warning information assurance. In response to the problem that system capability cannot meet operational requirements due to enemy attacks, this paper analyzes the structure of the early warning information system, Early warning information complex network model is established, based on the timeliness index, a genetic algorithm based on simulated annealing with special chromosome coding is proposed.the algorithm is used to adjust the network model structure, the ability of early warning information assurance has been improved. Finally, the simulation results show the effectiveness of the proposed method.
Zamry, Nurfazrina Mohd, Zainal, Anazida, Rassam, Murad A..  2021.  LEACH-CR: Energy Saving Hierarchical Network Protocol Based on Low-Energy Adaptive Clustering Hierarchy for Wireless Sensor Networks. 2021 3rd International Cyber Resilience Conference (CRC). :1–6.
Wireless Sensor Network consists of hundreds to thousands of tiny sensor nodes deployed in the large field of the target phenomenon. Sensor nodes have advantages for its size, multifunctional, and inexpensive features; unfortunately, the resources are limited in terms of memory, computational, and in energy, especially. Network transmission between nodes and base station (BS) needs to be carefully designed to prolong the network life cycle. As the data transmission is energy consuming compared to data processing, designing sensor nodes into hierarchical network architecture is preferable because it can limit the network transmission. LEACH is one of the hierarchical network protocols known for simple and energy saving protocols. There are lots of modification made since LEACH was introduced for more energy efficient purposed. In this paper, hybridization of LEACH-C and LEACH-R and the modification have been presented for a more energy saving LEACH called LEACH-CR. Experimental result was compared with previous LEACH variant and showed to has advantages over the existing LEACH protocols in terms of energy consumption, dead/alive nodes, and the packet sent to Base Station. The result reflects that the consideration made for residual energy to select the cluster head and proximity transmission lead to a better energy consumption in the network.
Leong Chien, Koh, Zainal, Anazida, Ghaleb, Fuad A., Nizam Kassim, Mohd.  2021.  Application of Knowledge-oriented Convolutional Neural Network For Causal Relation Extraction In South China Sea Conflict Issues. 2021 3rd International Cyber Resilience Conference (CRC). :1–7.
Online news articles are an important source of information for decisions makers to understand the causal relation of events that happened. However, understanding the causality of an event or between events by traditional machine learning-based techniques from natural language text is a challenging task due to the complexity of the language to be comprehended by the machines. In this study, the Knowledge-oriented convolutional neural network (K-CNN) technique is used to extract the causal relation from online news articles related to the South China Sea (SCS) dispute. The proposed K-CNN model contains a Knowledge-oriented channel that can capture the causal phrases of causal relationships. A Data-oriented channel that captures the position information was added to the K-CNN model in this phase. The online news articles were collected from the national news agency and then the sentences which contain relation such as causal, message-topic, and product-producer were extracted. Then, the extracted sentences were annotated and converted into lower form and base form followed by transformed into the vector by looking up the word embedding table. A word filter that contains causal keywords was generated and a K-CNN model was developed, trained, and tested using the collected data. Finally, different architectures of the K-CNN model were compared to find out the most suitable architecture for this study. From the study, it was found out that the most suitable architecture was the K-CNN model with a Knowledge-oriented channel and a Data-oriented channel with average pooling. This shows that the linguistic clues and the position features can improve the performance in extracting the causal relation from the SCS online news articles. Keywords-component; Convolutional Neural Network, Causal Relation Extraction, South China Sea.
Khan, Wazir Zada, Khurram Khan, Muhammad, Arshad, Qurat-ul-Ain, Malik, Hafiz, Almuhtadi, Jalal.  2021.  Digital Labels: Influencing Consumers Trust and Raising Cybersecurity Awareness for Adopting Autonomous Vehicles. 2021 IEEE International Conference on Consumer Electronics (ICCE). :1–4.
Autonomous vehicles (AVs) offer a wide range of promising benefits by reducing traffic accidents, environmental pollution, traffic congestion and land usage etc. However, to reap the intended benefits of AVs, it is inevitable that this technology should be trusted and accepted by the public. The consumer's substantial trust upon AVs will lead to its widespread adoption in the real-life. It is well understood that the preservation of strong security and privacy features influence a consumer's trust on a product in a positive manner. In this paper, we introduce a novel concept of digital labels for AVs to increase consumers awareness and trust regarding the security level of their vehicle. We present an architecture called Cybersecurity Box (CSBox) that leverages digital labels to display and inform consumers and passengers about cybersecurity status of the AV in use. The introduction of cybersecurity digital labels on the dashboard of AVs would attempt to increase the trust level of consumers and passengers on this promising technology.
2022-05-20
Zahra, Ayima, Asif, Muhammad, Nagra, Arfan Ali, Azeem, Muhammad, Gilani, Syed A..  2021.  Vulnerabilities and Security Threats for IoT in Transportation and Fleet Management. 2021 4th International Conference on Computing Information Sciences (ICCIS). :1–5.
The fields of transportation and fleet management have been evolving at a rapid pace and most of these changes are due to numerous incremental developments in the area. However, a comprehensive study that critically compares and contrasts all the existing techniques and methodologies in the area is still missing. This paper presents a comparative analysis of the vulnerabilities and security threats for IoT and their mitigation strategies in the context of transportation and fleet management. Moreover, we attempt to classify the existing strategies based on their underlying principles.
Choi, Changhee, Shin, Sunguk, Shin, Chanho.  2021.  Performance evaluation method of cyber attack behaviour forecasting based on mitigation. 2021 International Conference on Information and Communication Technology Convergence (ICTC). :13–15.
Recently, most of the processes are being computerized, due to the development of information and communication technology. In proportion to this, cyber-attacks are also increasing, and state-sponsored cyber-attacks are becoming a great threat to the country. These attacks are often composed of stages and proceed step-by-step, so for defense, it is necessary to predict the next action and perform appropriate mitigation. To this end, the paper proposes a mitigation-based performance evaluation method. We developed the new true positive which can have a value between 0 and 1 according to the mitigation. The experiment result and case studies show that the proposed method can effectively measure forecasting results under cyber security defense system.
Hasan, Raiful, Hasan, Ragib.  2021.  Towards a Threat Model and Security Analysis of Video Conferencing Systems. 2021 IEEE 18th Annual Consumer Communications Networking Conference (CCNC). :1–4.
Video Conferencing has emerged as a new paradigm of communication in the age of COVID-19 pandemic. This technology is allowing us to have real-time interaction during the social distancing era. Even before the current crisis, it was increasingly commonplace for organizations to adopt a video conferencing tool. As people adopt video conferencing tools and access data with potentially less secure equipment and connections, meetings are becoming a target to cyber attackers. Enforcing appropriate security and privacy settings prevents attackers from exploiting the system. To design the video conferencing system's security and privacy model, an exhaustive threat model must be adopted. Threat modeling is a process of optimizing security by identifying objectives, vulnerabilities, and defining the plan to mitigate or prevent potential threats to the system. In this paper, we use the widely accepted STRIDE threat modeling technique to identify all possible risks to video conferencing tools and suggest mitigation strategies for creating a safe and secure system.
Cotae, Paul, Reindorf, Nii Emil Alexander.  2021.  Using Counterfactual Regret Minimization and Monte Carlo Tree Search for Cybersecurity Threats. 2021 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom). :1–6.
Mitigating cyber threats requires adequate understanding of the attacker characteristics in particular their patterns. Such knowledge is essential in addressing the defensive measures that mitigate the attack. If the attacker enters in the network system, the game tree model generates resources by to counter such threat. This is done by altering the parity in the next game tree iteration which yield an adequate response to counter it. If an attacker enters a network system, and a game tree models the resources he must interface with, then that game tree can be altered, by changing the parity on the next to last iteration. This paper analyzes the sequence of patterns based on incoming attacks. The detection of attacker’s pattern and subsequent changes in iterations to counter threat can be viewed as adequate resource or know how in cyber threat mitigations It was realized that changing the game tree of the hacker deprives the attacker of network resources and hence would represent a defensive measure against the attack; that is changing varying or understanding attacker paths, creates an effective defensive measure to protect the system against the incoming threats.. In this paper we analyze a unique combination of CFR and MCTS that attempts to detect the behavior of a hacker. Counterfactual Regret (CFR) is a game theory concept that helps identify patterns of attacks. The pattern recognition concept of Monte Carlo Tree Search (MCTS) is used in harmony with CFR in order to enhance the detection of attacks.
Phan, Cao-Thanh, Rahali, Mohamed, Morin, Cédric.  2021.  Threat detection and mitigation with MonB5G components in the aLTEr scenario. 2021 IEEE International Mediterranean Conference on Communications and Networking (MeditCom). :1–2.
This demo presents a new approach to detecting and countering the aLTEr attack by proactively searching for the threat and automatically remediating it. These processes leverage AI/ML techniques and the automation framework offered by the MonB5G architecture.