Incremental Adversarial Learning for Polymorphic Attack Detection by Ulya Sabeel, Shahram Shah Heydari, Khalil El-Khatib, Khalid Elgazzar

“…AI-based Network Intrusion Detection Systems (NIDS) provide effective mechanisms for cybersecurity analysts to gain insights and thwart several network attacks. …”
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A Survey on Adversarial Attacks for Malware Analysis by Kshitiz Aryal, Maanak Gupta, Mahmoud Abdelsalam, Pradip Kunwar, Bhavani Thuraisingham

“…However, minor perturbations or ineffectual byte insertions can easily ‘fool’ these trained ML classifiers, making them ineffective against these crafted and smart malicious software. This survey aims to provide an encyclopedic overview of adversarial evasion attacks specifically targeting malware detection and classification systems, standing apart from previous surveys by focusing exclusively and comprehensively on this unique application domain. …”
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Routing Attacks and Countermeasures in the RPL-Based Internet of Things by Linus Wallgren, Shahid Raza, Thiemo Voigt

“…In this paper we provide a comprehensive analysis of IoT technologies and their new security capabilities that can be exploited by attackers or IDSs. …”
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An SDN-Based Approach to Ward Off LAN Attacks by René Rietz, Radoslaw Cwalinski, Hartmut König, Andreas Brinner

“…In this paper, we propose based on an analysis of typical LAN-based attacks an approach for preventing these attacks for both IPv4 and IPv6 networks. …”
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Cloud Survivability Scenarios Under Attacks With and Without Countermeasures by Rachid Beghdad, Faiza Benmenzer, Alaa Eddine Khalfoune

“…This highlights the importance of optimizing countermeasures, especially to handle high-intensity attacks. Conclusion: This study provides valuable insights for cloud managers to enhance resilience and face sophisticated DDoS attacks. …”
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Investigate the Use of Deep Learning in IoT Attack Detection by Mohamed Saddek Ghozlane, Adlen Kerboua, Smaine Mazouzi, Lakhdar Laimeche

“…This study contributes a comprehensive comparative analysis of deep learning models for IoT security, focusing on the effectiveness of weighted features in improving detection accuracy. The results provide valuable information for the advancement of real-time IoT attack detection systems.…”
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Visual Scheme for the Detection of Mobile Attack on WSN Simulator by Young-Sik Jeong, Hyun-Woo Kim, Jong Hyuk Park

“…Sensors can be efficiently arranged through this sensor node information, and when the sensors have been arranged, security simulation functions applied with data encryption for data transmission between sensor nodes are provided. This paper also proposes an external detection trace simulator (EDTS) that would make sensing data transmitted between sensors visually provide information on the sensing of external attacks.…”
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Preventing Stealthy Attacks on Power Electronics Dominated Grids by Stephanie Harshbarger, Mohsen Hosseinzadehtaher, Alireza Zare, Amin Y. Fard, Mohammad B. Shadmand, George Amariucai

“…Another advantage to the attacker is an increased amount of telecommunication devices in PEDGs which provides the attacker with a larger attack surface. …”
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Command Injection Attacks in Smart Grids: A Survey by Muhammad Usama, Muhammad Naveed Aman

“…Several studies have been conducted to discuss different types of cyberattacks and provide their countermeasures. The false command injection attack (FCIA) is considered one of the most critical attacks that have been studied. …”
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Investigating Brute Force Attack Patterns in IoT Network by Deris Stiawan, Mohd. Yazid Idris, Reza Firsandaya Malik, Siti Nurmaini, Nizar Alsharif, Rahmat Budiarto

“…At the same time, password matching/theft holding is among the popular attacks as the intruders attack the IoT network. Thus, this paper attempts to provide an insight of this type of attack with the main aim of coming up with attack patterns that may help the IoT system administrator to analyze any similar attacks. …”
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Preparing a Family Communication Plan for Terrorist Attacks by Rose Barnett

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Preparing a Family Communication Plan for Terrorist Attacks by Rose Barnett

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Side-Channel Attack on ARADI in Non-Profiling Scenarios by Donggeun Kwon, Seokhie Hong

“…These findings highlight critical weaknesses in the physical security of ARADI and emphasize the need for robust countermeasures to address side-channel vulnerabilities without compromising performance. This research provides new insights into the practical security of ARADI, underscoring the importance of integrating physical attack resilience in cryptographic designs.…”
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Localizing Adversarial Attacks To Produces More Imperceptible Noise by Pavan Reddy, Aditya Sanjay Gujral

“…This work provides a comprehensive analysis of localized adversarial attacks, offering practical insights for advancing attack strategies and designing robust defensive systems. …”
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Vulnerability Assessment of Hazmat Storage Tanks to Shooting Attacks by Matteo Iaiani, Alessandro Tugnoli, Valerio Cozzani

“…The present study addresses this gap and provide a novel scientifically based modelling approach to calculate baseline values of standoff distances for atmospheric storage equipment that can be used to assess the potential damage of shooting attacks targeting them. …”
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The impact of terrorist attacks on cultural values as expressed in books. by Daniel Hart, I-Ming Chiu, Richard Epstein

“…We assessed the effects of the 9/11/2001 terrorist attacks on the salience of moral words and phrases in the United States, Great Britain, and Spanish-speaking countries, focusing particularly on those phrases related to authority and loyalty. …”
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Deterioration of service reservoirs due to soft water attack by Brueckner Rene, Griffiths Graham, Hesling Jed, Taylor Christopher, Telford Amber

“…The paper discusses the findings of the field and laboratory investigation after one and seven years of immersion. It provides an indication of the most resistant mix designs, effects of the use of fly ash and ground granulated blastfurnace slag, and reliable water parameters that can be utilised to assess the risk and rate of attack.…”
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Leveraging Graph Neural Networks for IoT Attack Detection by Mevlüt Uysal, Erdal Özdoğan, Onur Ceran

“…High accuracy, precision, recall, and AUC values indicate the model's robustness in detecting attacks while minimizing false alarms. The study advances IoT security by introducing synergistic solutions and provides practical insights for implementing intrusion detection systems in real-world IoT environments.…”
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Review of Research on Adversarial Attack in Three Kinds of Images by XU Yuhui, PAN Zhisong, XU Kun

“…Finally, the current status of image adversarial samples is analyzed, the possible research directions of adversarial attacks in the future image field are prospected, the potential problems that may be encountered in the future are summarized, and corresponding solutions are provided.…”
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Resilience of Named Entity Recognition models against adversarial attacks by Paweł Walkowiak

“…Adversarial Attacks are actions that aims to mislead models by introducing subtle and often imperceptible changes in model’s input. …”
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