On the performance of non‐profiled side channel attacks based on deep learning techniques by Ngoc‐Tuan Do, Van‐Phuc Hoang, Van Sang Doan, Cong‐Kha Pham

“…This paper proposes and evaluates the applications of different DL techniques including the Convolutional Neural Network and the multilayer perceptron models for non‐profiled attacks on the AES‐128 encryption implementation. …”
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Modeling and Detection of Cyber and Physical Attacks on the Control Unit of PV Farm System by Aqeel Sajjad Shaeel, Huda Hussein Abed, Ahmed Fahim Al-Baghdadi

“… The use of solar panels is becoming increasingly important now as a source of renewable energy. With the different systems designed to invest solar energy and the different electronic attacks on renewable energy systems, the importance of designing a photovoltaic system with different features appears in terms of detecting the attack on the input of the control unit to the system, and thus knowing the electronic attacks targeting the control unit. …”
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Research of kinematic characteristics of basic attacking technical action young wrestlers freestyle by W.W. Yaremenko

“…Іdentified temporal characteristic structures basic attacking technicians action young wrestlers freestyle different qualifications. …”
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Research of Attack Angle on Quasi-static Derailment Criterion of the Rail Changing Robot by Chaoyan WU, Tianhong LUO, Chun YANG

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Boosting the Transferability of Ensemble Adversarial Attack via Stochastic Average Variance Descent by Lei Zhao, Zhizhi Liu, Sixing Wu, Wei Chen, Liwen Wu, Bin Pu, Shaowen Yao

“…However, most of the model ensemble attacks directly combine the different models’ output but ignore the large differences in optimization direction of them, which severely limits the transfer attack ability. …”
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A Robust Method to Protect Text Classification Models against Adversarial Attacks by BALA MALLIKARJUNARAO GARLAPATI, Ajeet Kumar Singh, Srinivasa Rao Chalamala

“…The diversity and sparseness of adversarial perturbations of different attack methods challenge these approaches. …”
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A Machine Learning-Based Framework for Measuring Attack Surfaces of IoT Systems by Bandar M. Alshammari

“…Several machine learning models have been used to show how to evaluate and validate the mapping process between different layers and various cyberattacks. Once higher performance results are obtained of the defined mapping, the security metrics proposed here are applied to measure the attack surface size of that particular architecture.…”
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Probabilistic models for evaluating network edge's resistance against scan and foothold attack by Shuo Wang, Qingqi Pei, Yang Xiao, Feng Shao, Shuai Yuan, Jiang Chu, Renjie Liao

“…Abstract The threat of Scan and Foothold Attack to the Network Edge (SFANE) is increasing, which greatly affects the application and development of edge computing network architecture. …”
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A survey on detection and localisation of false data injection attacks in smart grids by Muhammad Irfan, Alireza Sadighian, Adeen Tanveer, Shaikha J. Al‐Naimi, Gabriele Oligeri

“…For this purpose, more than 40 major research contributions were selected and inspected, while conducting a detailed analysis of the methodology and objectives in relation to the FDI attacks detection and localisation. Key findings of the identified papers were provided according to different criteria, such as employed FDI attacks localisation techniques, utilised evaluation scenarios, investigated FDI attack types, application scenarios, adopted methodologies and the use of additional data. …”
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Modelling the impact of a smallpox attack in India and influence of disease control measures by Abrar Ahmad Chughtai, C Raina MacIntyre, Biswajit Mohanty, Valentina Costantino, Jai Narain, Arpita Das

“…Objectives To estimate the impact of a smallpox attack in Mumbai, India, examine the impact of case isolation and ring vaccination for epidemic containment and test the health system capacity under different scenarios with available interventions.Setting The research is based on Mumbai, India population.Interventions We tested 50%, 70%, 90% of case isolation and contacts traced and vaccinated (ring vaccination) in the susceptible, exposed, infected, recovered model and varied the start of intervention between 20, 30 and 40 days after the initial attack.Primary and secondary outcome measures We estimated and incorporated in the model the effect of past vaccination protection, age-specific immunosuppression and contact rates and Mumbai population age structure in modelling disease morbidity and transmission.Results The estimated duration of an outbreak ranged from 127 days to 8 years under different scenarios, and the number of vaccine doses needed for ring vaccination ranged from 16 813 to 8 722 400 in the best-case and worst-case scenarios, respectively. …”
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An Incident Management System Design to Protect Critical Infrastructures from Cyber Attacks by Zeynep Gürkaş Aydın, Uğur Gürtürk

“…With the studies, a total of 10 different categories were analyzed, with the category consisting of nine types of attacks, namely Analysis, Backdoor, DoS, Exploits, Fuzzers, Generic, Reconnaissance, Shellcode, and Worms and Normal activities. …”
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Cyber-attacks to critical energy infrastructure and management issues: overview of selected cases by Tomas Plėta, Manuela Tvaronavičienė, Silvia Della Casa, Konstantin Agafonov

“…The analysis presented in the paper will take into consideration three different case scenarios of cyber-attacks to Critical Energy Infrastructures, and will evaluate the outcomes and the tactics used by the organizations’ response and recovery.…”
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Event-Triggered Quantized Stabilization of Markov Jump Systems under Deception Attacks by Jingjing Yan, Shuaibing Zhao, Xiaoliang Feng

“…This paper focuses on the event-triggered quantized control for Markov jump systems with deception attacks. First, we design an event-triggered scheme relying on dwell time and end instants of attacks. …”
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Efficient DDoS attack detection and prevention scheme based on SDN in cloud environment by Heng HE, Yan HU, Lianghan ZHENG, Zhengyuan XUE

“…For addressing the problem of two typical types of distributed denial of service (DDoS) attacks in cloud environment,a DDoS attack detection and prevention scheme called SDCC based on software defined network (SDN) architecture was proposed.SDCC used a combination of bandwidth detection and data flow detection,utilized confidence-based filtering (CBF) method to calculate the CBF score of packets,judged the packet of CBF score below the threshold as an attacking packet,added its attribute information to the attack flow feature library,and sent the flow table to intercept it through SDN controller.Simulation results show that SDCC can detect and prevent different types of DDoS attacks effectively,and it has high detection efficiency,reduces the controller’s computation overhead,and achieves a low false positive rate.…”
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Hybrid Machine Learning Model for Efficient Botnet Attack Detection in IoT Environment by Mudasir Ali, Mobeen Shahroz, Muhammad Faheem Mushtaq, Sultan Alfarhood, Mejdl Safran, Imran Ashraf

“…As the Internet of Things (IoT) technology is developing rapidly, many network devices have been subject to botnet attacks leading to substantial losses in different sectors. …”
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DDoS Attacks Detection With Deep Learning Approach Using Convolutional Neural Network by Rafiq Amalul Widodo, Mera Kartika Delimayanti, Asri Wulandari

“…The detection system of DDoS (Distributed Denial-of-Service) attacks aims to enhance network security across all facets of internet technology utilization. …”
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PKK’s Drone Attacks within the Perspective of Learning Organisation and Türkiye’s Counter Reaction by Cenk ÖZGEN, Selim KURT

“… PKK’s methods used in its terrorist attacks targeting Türkiye have been observed to transform over time. …”
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DoS and DDoS Attack Detection in IoT Infrastructure using Xception Model with Explainability by Nelly Elsayed, Zag ElSayed, Ahmed Abdelgawad

“…We employed the Xception model with fine-tuning, and we achieved an average of 91% accuracy in detecting eleven different types of DoS and DDoS attacks, which is higher than the current state-of-the-art by 5% targeting the same task. …”
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Attacks on Polish Bank Customers During the Pandemic: Cyberscams and the Role of Security Alerts by Wojciech Kaczmarczyk

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DDoS attack detection and defense based on hybrid deep learning model in SDN by Chuanhuang LI, Yan WU, Zhengzhe QIAN, Zhengjun SUN, Weiming WANG

“…Software defined network (SDN) is a new kind of network technology,and the security problems are the hot topics in SDN field,such as SDN control channel security,forged service deployment and external distributed denial of service (DDoS) attacks.Aiming at DDoS attack problem of security in SDN,a DDoS attack detection method called DCNN-DSAE based on deep learning hybrid model in SDN was proposed.In this method,when a deep learning model was constructed,the input feature included 21 different types of fields extracted from the data plane and 5 extra self-designed features of distinguishing flow types.The experimental results show that the method has high accuracy,it’s better than the traditional support vector machine (SVM) and deep neural network (DNN) and other machine learning methods.At the same time,the proposed method can also shorten the processing time of classification detection.The detection model is deployed in SDN controller,and the new security policy is sent to the OpenFlow switch to achieve the defense against specific DDoS attack.…”
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