Lightweight Models for Real-Time Steganalysis: A Comparison of MobileNet, ShuffleNet, and EfficientNet by Achmad Bauravindah, Dhomas Hatta Fudholi

“…Steganography conceals data within digital media, but its misuse for cyberattacks—such as embedding malware—has highlighted the need for steganalysis, the detection of hidden data. …”
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MSSA: multi-stage semantic-aware neural network for binary code similarity detection by Bangrui Wan, Jianjun Zhou, Ying Wang, Feng Chen, Ying Qian

“…Binary code similarity detection (BCSD) aims to identify whether a pair of binary code snippets is similar, which is widely used for tasks such as malware analysis, patch analysis, and clone detection. …”
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Consumer Protection of Girls from Cybercrime in a Gender Perspective by Susilowati Suparto, Deviana Yuanitasari, Sonny Dewi Judiasih, Yamudin Salaeh

“…Cybercrime covers a wide range of illegal acts carried out through the Internet or other digital devices, including fraud, identity theft, hacking, the spread of malware, to sexual exploitation of children. Girls are often the primary targets of these various forms of cybercrime. …”
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PROPOSALS FOR A BROADER APPROACH OF „MISUSE OF DEVICES AND PROGRAMS” PROVISION IN COMBATING CYBER-DEPENDENT AND CYBER-ENABLED CRIMES by Maxim DOBRINOIU

“…Taking into consideration the proliferation of illegal activities against personal information, confidential data or access credentials, especially the commercialization, especially in Dark Web, of codes, passwords, hacking tools, malware and other present or future cutting-edge system interference technologies, thus posing a great danger to the whole cyber-ecosystem, an improvement of art. 6, and of all the correspondent (related) articles in the special laws or the criminal codes adopted by the signatory countries, would contribute to the creation of an extensive and much comprehensive legal tool in the prevention and efficiently combating cybercrimes.…”
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Security Risks and Designs in the Connected Vehicle Ecosystem: In-Vehicle and Edge Platforms by Marco De Vincenzi, John Moore, Bradley Smith, Sanjay E. Sarma, Ilaria Matteucci

“…By analyzing case studies such as Android Automotive, Message Queuing Telemetry Transport (MQTT), and the Robot Operating System (ROS), we identify the primary security threats, including malware attacks, data manipulation, and Denial of Service (DoS) attacks. …”
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MODIFICAREA PEISAJULUI AMENINȚĂRILOR CIBERNETICE DATORITĂ IMPLICĂRII GRUPĂRILOR DE CYBERCRIME ÎN RĂZBOIUL RUSO-UCRAINEAN by Claudia-Alecsandra GABRIAN

“…There were identified changes in malware-as-a-service and ransomware-as-a-service attacks, as well as changes in cybercriminal tactics and methods to orchestrate an attack. …”
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New Heuristics Method for Malicious URLs Detection Using Machine Learning by Maher Kassem Hasan

“… Malicious URLs are a very prominent, dangerous form of cyber threats in view of the fact that they can enable many evils like phishing attacks, malware distribution, and several other kinds of cyber fraud. …”
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Cybersecurity Solutions for Industrial Internet of Things–Edge Computing Integration: Challenges, Threats, and Future Directions by Tamara Zhukabayeva, Lazzat Zholshiyeva, Nurdaulet Karabayev, Shafiullah Khan, Noha Alnazzawi

“…The findings underscore the widespread vulnerabilities across the IIoT architecture, particularly in relation to DoS, ransomware, malware, and MITM attacks. The review emphasizes the integration of advanced security technologies, including machine learning (ML), federated learning (FL), blockchain, blockchain–ML, deep learning (DL), encryption, cryptography, IT/OT convergence, and digital twins, as essential for enhancing the security and real-time data protection of CPS in IIoT–edge computing. …”
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Enhanced Intrusion Detection in Drone Networks: A Cross-Layer Convolutional Attention Approach for Drone-to-Drone and Drone-to-Base Station Communications by Mohammad Aldossary, Ibrahim Alzamil, Jaber Almutairi

“…Distributed Denial of Service (DDoS) attacks, malware infections, and communication abnormalities increase cybersecurity dangers to these networks, threatening operational safety and efficiency. …”
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Unveiling personalized and gamification-based cybersecurity risks within financial institutions by Amna Shahzadi, Kashif Ishaq, Naeem A. Nawaz, Fadhilah Rosdi, Fawad Ali Khan

“…The article also offers a comprehensive taxonomy of financial services, categorizing cyber threats into game-based (e.g., phishing, malware, APTs) and non-game-based (e.g., social engineering, compliance issues) threats. …”
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Reinforcement Learning-Based Generative Security Framework for Host Intrusion Detection by Yongsik Kim, Su-Youn Hong, Sungjin Park, Huy Kang Kim

“…When calculating the reward in reinforcement learning, we used the comparison value with the pre-trained Seq2Seq model, the malware log sequence detected by the rule set based on reinforcement learning, and the false positive value generated by the normal data to create its own rule set. …”
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Trends, challenges and solutions of digital information security in Central and Eastern Europe by Serhii Lubenets, Igor Harchenko, Tetiana Shediakova

“…Establishing a secure remote work environment remains a top priority, along with the ongoing fight against malicious malware attacks. It was determined that the use of cloud technologies remains particularly relevant for international companies and CEE institutions. …”
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Research on cloud-based traffic adaptive command and control method for mobile botnet by Wei CHEN, Shi-wen ZHOU, Cheng-yu YIN

“…Botnet is a serious attack evolved from traditional malwares.With the rapid development of computing capability and mobile Internet access technology，building a realistic mobile botnet has become a potential threat.An adaptive traffic control mechanism for cloud-based mobile botnet was proposed.It adopts different traffic consumption strategies according to different 3G or Wi-Fi network environments.Then scheduling algorithms to execute botnet commands was applied.The experimental results show the traffic adaptive algorithm can improve the stealthy and efficiency of mobile botnet while ensure that the botnet commands can be executed effectively.…”
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Detection of malicious domain name based on a classifier combination by Jiantao SHENG, Maofei CHEN, Dongxin LIU, Laifu WANG, Guoshui SHI, Huamin JIN

“…As a fundamental service on the internet,domain name system (DNS) can inevitably be abused by malicious activities.Based on the studies of Botnets and other malwares which made use of the domain generation algorithm (DGA),and researches on current major techniques of malicious domain detection,a malicious domain detection framework based on a classifier combination was proposed.The framework applied the support vector machine (SVM) as its main classifier and combined the naive Bayes classifier (NBC) supportively with some statistical characteristics.Experiment result demonstrates that the framework outperformes current techniques in the offline-training time and the capability of detecting unknow malicious domain families,which satisfies the requirement of internet service provider (ISP) to detect and analyze malicious domainson the internet.…”
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