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121
MSSA: multi-stage semantic-aware neural network for binary code similarity detection
Published 2025-01-01“…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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122
Software Authority Transition through Multiple Distributors
Published 2014-01-01“…Such openness, however, can promote serious threats, including malware and illegal usage. In order to prevent such threats, several stores use online authentication techniques. …”
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123
A New Sensors-Based Covert Channel on Android
Published 2014-01-01“…Accelerometers generate signals that reflect user motions, and malware applications can apparently only read their data. …”
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124
Cybersecurity Solutions for Industrial Internet of Things–Edge Computing Integration: Challenges, Threats, and Future Directions
Published 2025-01-01“…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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125
A Review about Internet of Things (IoT) integration with Cloud Computing with a Limelight on Security
Published 2024-01-01“…Through an in-depth analysis of recent research, we examine the security challenges associated with IoT-based cloud computing, including account hacking, phishing, malware, middleman attacks, and service denial. We also discuss the potential benefits, architectural integration options, and the impact of IoT on cloud computing. …”
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126
Fusion of Focal Loss’s cyber threat intelligence entity extraction
Published 2022-07-01“…Cyber threat intelligence contains a wealth of knowledge of threat behavior.Timely analysis and process of threat intelligence can promote the transformation of defense from passive to active.Nowadays, most threat intelligence that exists in the form of natural language texts contains a large amount of unstructured data, which needs to be converted into structured data for subsequent processing using entity extraction methods.However, since threat intelligence contains numerous terminology such as vulnerability names, malware and APT organizations, and the distribution of entities are extremely unbalanced, the performance of extraction methods in general field are severely limited when applied to threat intelligence.Therefore, an entity extraction model integrated with Focal Loss was proposed, which improved the cross-entropy loss function and balanced sample distribution by introducing balance factor and modulation coefficient.In addition, for the problem that threat intelligence had a complex structure and a wide range of sources, and contained a large number of professional words, token and character features were added to the model, which effectively improved OOV (out of vocabulary) problem in threat intelligence.Experiment results show that compared with existing mainstream model BiLSTM and BiLSTM-CRF, the F1 scores of the proposed model is increased by 7.07% and 4.79% respectively, which verifies the effectiveness of introducing Focal Loss and character features.…”
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127
Research and practice of SASE cloud security
Published 2022-01-01“…With the development of the Internet today, earth shaking changes have taken place compared with the traditional network.In today's network reform, "cloud" has become the mainstream direction of the evolution of enterprise IT architecture, so the requirements for cloud security are becoming higher and higher.The practical deployment scheme of SASE cloud security architecture was introduced to solve the problem of cloud security for customers.A unique and complete SASE solution was proposed, which combined security functions with SD-WAN functions, and realized real-time monitoring, intelligent analysis and automatic interception of malware or malicious activities by building a unified management and control platform and centralized deployment of core security resource pool.Practice has proved that the scheme achieves the expected results in unified management and control, intrusion detection and defense, fine access control and so on, and can fully ensure the cloud security of enterprises.…”
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128
Narrowing the semantic gap in virtual machine introspection
Published 2015-08-01“…Virtual machine introspection(VMI)has been widely used in areas such as intrusion detection and malware analysis.However,due to the existence of semantic gap,the generality and the efficiency of VMI were partly influenced while getting internal information of a virtual machine.By analyzing the deficiencies of existing technology of semantic gap restoration,a method called ModSG was proposed to bridge the semantic gap.ModSG was a modularity system,it divided semantic restoration into two parts.One was online phase that interact directly with user to construct semantic views,the other was offline phase that only interact with operating system to parse high-level semantic knowledge.Both were implemented via independent module,and the latter provided the former with necessary kernel information during semantic view construction.Experiments on different virtual machine states and different kernel versions show that the ModSG is accurate and efficient in narrowing semantic gap.The modular design and deployment also make ModSG easily to be extended to other operating systems and virtualization platforms.…”
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129
Research on cloud-based traffic adaptive command and control method for mobile botnet
Published 2014-11-01“…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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130
Detection of malicious domain name based on a classifier combination
Published 2020-05-01“…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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131
Analisis Perilaku Entitas untuk Pendeteksian Serangan Internal Menggunakan Kombinasi Model Prediksi Memori dan Metode PCA
Published 2023-12-01“…External attacks can be prevented using firewalls, anti-virus software, and special software for intruder and malware detection. This study intention is to build a model for analyzing entity behavior using a memory prediction model and uses the principal component analysis (PCA) as a feature selection method and implement it to detect cyber-attacks and anomalies involving insiders. …”
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132
Trends, challenges and solutions of digital information security in Central and Eastern Europe
Published 2024-06-01“…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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133
Security Risks and Designs in the Connected Vehicle Ecosystem: In-Vehicle and Edge Platforms
Published 2025-01-01“…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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134
Behaviour Analysis of Mobile Malicious Software in Network
Published 2015-08-01“…A behavior analysis method of mobile malicious softwares and a corresponding solution on the network-side were proposed.The method combined network behaviors and virus-inner behaviors of a mobile malicious software to improve the accuracy and the timeliness.The method was a useful guidance for communication operators to block mobile malware in real time.…”
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135
Identifikasi Malicious Host dalam Local Area Network Menggunakan Teknik Graph Clustering dan Filtering
Published 2020-05-01“…Actions to reduce the spread of malware in the LAN can be done by identifying malicious hosts. …”
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136
Approaches to cyber weapons classification problem
Published 2013-04-01“…Working criteria for differentiation between information warfare and practical cyber warfare is suggested for proper classification of malware, espionage toolkits, hacking tools and combat software.…”
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137
Deep visualization classification method for malicious code based on Ngram-TFIDF
Published 2024-06-01“…With the continuous increase in the scale and variety of malware, traditional malware analysis methods, which relied on manual feature extraction, become time-consuming and error-prone, rendering them unsuitable. …”
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138
Research on Clue Mining in Criminal Cases of Smart Phone Trojan Horse under the Background of Information Security
Published 2022-01-01“…With the massive popularity and wide application of Android smartphones, there are more and more malware targeting Android smartphones. Research and analysis Android smart phone Trojan horses can provide corresponding technical support for malware detection on Android smart phones, which has good scientific research significance and broad market value. …”
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139
APT Adversarial Defence Mechanism for Industrial IoT Enabled Cyber-Physical System
Published 2023-01-01“…Two datasets, the DAPT2020 malware, and Edge I-IoT datasets are used to evaluate the approach, and it attains the highest detection accuracy of 96.97% and 95.97%, with prediction time of 20.56 seconds and 21.65 seconds, respectively. …”
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