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Article
Computer Science, Information Systems
Anusha Vangala et al.
Summary: Agricultural industry, being a vital contributor to the economy, has witnessed significant changes in its operation with the advancement of precision farming and IoT. This paper explores the security scenarios in husbandry and proposes an architecture for smart farming. It conducts a literature survey on security protocols and authentication protocols in smart agriculture, as well as studies the current progress in IoT-based tools and systems.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Automation & Control Systems
Xingxia Dai et al.
Summary: This article investigates the application of mobile edge computing and device-to-device offloading in the industrial Internet of Things, proposing a co-offloading framework and a learning-based algorithm to address challenges such as mobility, selfishness, and incomplete information.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Theory & Methods
Yu Yao et al.
Summary: This study uses Distributed Kalman Filtering (DKF) and Deep Reinforcement Learning (DRL) techniques to improve anti-eavesdropping communication capacity and mitigate jamming interference in connected and autonomous vehicle networks. The researchers develop a DKF algorithm to more accurately track attackers by sharing state estimates among adjacent nodes. They also establish a design problem for controlling transmission power and selecting communication channels while ensuring the requirements of authorized vehicular users. A hierarchical Deep Q-Network (DQN)-based architecture is developed to design anti-eavesdropping power control and channel selection policies in uncertain and dynamic eavesdropping and jamming scenarios.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Article
Computer Science, Theory & Methods
Zhenguang Liu et al.
Summary: This paper tackles the challenges of smart contracts from three aspects: generating function invocation sequences by considering data dependencies, using a branch distance-based measure to evolve test cases towards target branches, and employing a branch search algorithm to discover rare and vulnerable branches. The proposed IR-Fuzz method achieves higher branch coverage, detects more vulnerabilities, and is fast in generating test cases.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Article
Computer Science, Information Systems
Hengwei Zhang et al.
Summary: This study integrates potential differential game theory with complex networks to propose a global optimal defense decision algorithm that considers the structural characteristics of complex networks and the attack-defense characteristics of cybersecurity. A network attack-defense potential differential game model is constructed based on the evolutionary analysis of network security states. Adversarial analysis is carried out on the overall attack-defense strategy, and a defense decision algorithm is designed based on a saddle point equilibrium strategy. Simulation tests are conducted to evaluate the effectiveness of the proposed method.
COMPUTERS & SECURITY
(2023)
Article
Computer Science, Information Systems
Wei Zheng et al.
Summary: This paper studies a static fuzzy mutation method for program code, which can improve the efficiency of mutation sample generation according to the vulnerability evolution law, thus promoting the development of zero-day vulnerability detection methods based on deep learning techniques.
INFORMATION AND SOFTWARE TECHNOLOGY
(2023)
Review
Computer Science, Artificial Intelligence
Siyu Lu et al.
Summary: Visual Question Answering (VQA) is a significant cross-disciplinary issue that requires a computer to output a natural language answer based on pictures and questions. The attention mechanism plays a key role in integrating text features and visual features. This article explores the development status of attention mechanisms, analyzes existing methods, and discusses the future direction of VQA.
PEERJ COMPUTER SCIENCE
(2023)
Article
Computer Science, Theory & Methods
Yujia Song et al.
Summary: This paper proposes a deep learning-based anomaly detection method for multivariate time series in real-world operational clouds. The method utilizes two parallel graph neural networks (GNN) to learn the time and feature inter-dependencies, resulting in fewer false positives. The evaluation shows that the proposed method outperforms seven baseline methods with an average F1-Score of 0.871, improving by 19.9% compared to state-of-the-art methods. Additionally, the method correctly identifies the root cause of detected anomalies with up to 74.1% accuracy.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Humanities, Multidisciplinary
Xuan Liu et al.
Summary: The computational identification and categorization of opinions in text is crucial for providing better understanding and services to online users. However, the current multi-label automatic classification is still inadequate. This study proposes a modified MLkNN classifier that considers both in-sentence and adjacent sentence features, resulting in improved accuracy and speed in emotion classification for short texts on Twitter.
HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS
(2023)
Article
Social Sciences, Interdisciplinary
Xuan Liu et al.
Summary: Facing the growing need to extract textual features of online texts for better communication in the Digital Media Age, sentiment classification, by developing corpora with annotation of emotions, is considered the key method to catch emotions of online communication. However, the manual annotation process is labor-intensive and costly, resulting in the lack of corpora for emotional words. Therefore, there is an urgent need for improvement in the methods of automatic emotion tagging with multiple emotion labels to construct new semantic corpora.
Article
Engineering, Electrical & Electronic
Ryhan Uddin et al.
Summary: The integration of IoT devices and machine learning technologies has led to automation in various sectors guided by AI. In the context of space exploration, AI-powered IoT networks will play a crucial role in self-governing systems in space colonies. However, ensuring data protection is essential for widespread adoption. This paper proposes a federated learning based approach to address data breach in the satellite-IoT framework and implements an SDN backbone with a traffic regulator for network security. The system achieves a promising accuracy rate of 79.47% in detecting attacks.
IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION
(2023)
Article
Computer Science, Information Systems
Wei Jiang et al.
Summary: Computation offloading via device-to-device communications improves the performance of mobile edge computing. Existing optimization-based schemes lack self-adaptive abilities in dynamic environments. The proposed hierarchical deep reinforcement learning (HDRL) framework solves the joint computation offloading and resource allocation problem by combining deep Q-network (DQN) and deep deterministic policy gradient (DDPG) methods. Simulation results demonstrate the effectiveness of the HDRL algorithm in reducing task computation latency.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Song Han et al.
Summary: Privacy-preserving federated learning is a promising approach for IoT in healthcare, and this article proposes two practical noninteractive federated learning schemes, HE-NFRT and Mask-NFRT, which can protect the privacy of data owners' training data, resist collusion attacks, and support strong verification.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Cybernetics
Feifei Qiao et al.
Summary: Federated learning is used in financial risk management for fraud detection to improve model accuracy without exchanging training data. Existing defenses for GAN-based poisoning attacks have limitations, and to address these, we propose a privacy-aware and incremental defense (PID) method to detect malicious participants and protect privacy.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Review
Chemistry, Analytical
Aleksandr Ometov et al.
Summary: This literature review examines the research interest in information security and privacy and the development of computing paradigms, and addresses the security and privacy challenges arising from their heterogeneity. The study identifies essential security and privacy threats in these paradigms and highlights the deployment techniques used to mitigate and enhance security and privacy shortcomings.
Article
Computer Science, Information Systems
Shivani Singh et al.
Summary: Edge computing is a technological advancement that connects sensors and provides services at the device end, but security is a major concern. This article explores the security and privacy issues in different layers of the Edge computing architecture and the machine learning algorithms used to address these concerns. It also discusses various types of attacks on the Edge network and introduces intrusion detection systems and machine learning algorithms that overcome these security and privacy challenges.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Jie Li et al.
Summary: This study investigates a cloud-edge based hybrid smart grid fault detection system using embedded devices and lightweight neural networks. By optimizing communication and computational resource allocation, the processing throughput and resource utilization of the system are improved.
ACM TRANSACTIONS ON SENSOR NETWORKS
(2022)
Article
Computer Science, Information Systems
Ayush Kumar et al.
Summary: In this work, a solution called EDIMA is presented for IoT botnet detection. It consists of lightweight modules deployed at edge gateways in home networks, with additional modules implemented on cloud servers. EDIMA aims to detect IoT botnets prior to an attack, featuring a novel two-stage Machine Learning-based detector. The solution achieves high accuracies in bot scanning and bot-CnC traffic detection, with low false positive rates, and is shown to be robust to increasing IoT device connections. Performance analysis demonstrates low bot detection delays and RAM consumption. EDIMA outperforms existing detection techniques for bot scanning traffic and bot-CnC server communication.
COMPUTERS & SECURITY
(2022)
Article
Chemistry, Analytical
Mamoona Majid et al.
Summary: This article introduces the fourth industrial revolution (Industry 4.0) and its applications in the fields of Internet of Things (IoT) and wireless sensor networks (WSN), discusses the various issues and future directions in this area, and provides a systematic literature review of relevant research in recent years.
Article
Computer Science, Information Systems
Segun Popoola et al.
Summary: This article proposes a federated deep learning method for zero-day botnet attack detection in IoT-edge devices. The method generates a global model by coordinating the training of independent models in multiple IoT-edge devices, achieving high-performance classification detection of zero-day botnet attacks and ensuring data privacy and security.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Mohammad Wazid et al.
Summary: The combination of machine learning and cyber security can enhance model security, improve performance, and enable effective detection of zero day attacks. This paper discusses the integration of these two concepts, as well as the advantages, issues, challenges, and future research directions.
Article
Computer Science, Information Systems
Jaskaran Singh et al.
Summary: Cyber physical systems integrate sensing, computation, control, and networking processes into physical objects and infrastructure. The tight coupling of cyber systems with physical systems introduces challenges in stability, security, efficiency, and reliability. Machine learning security aims to protect machine learning models against various cyber attacks. In this article, various machine learning security attacks in cyber physical systems are discussed, along with defense mechanisms and a comparative study of ML models' performance under the influence of these attacks.
COMPUTER COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Kunrui Cao et al.
Summary: This paper investigates the security of semi-grant-free NOMA transmission in the presence of passive and active eavesdropping attacks. Different scheduling schemes are proposed to combat eavesdropping attacks for different user scenarios. The system performance is evaluated by analyzing the secrecy outage probability. Simulation results validate the superiority of the proposed schemes.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Bin Li et al.
Summary: This article investigates a dynamic event-triggered security control problem in networked control systems under deception attacks and packet dropouts. A combined cyberattack model is proposed to reflect randomly occurring cyber-attacks. A dynamic event-triggered protocol is constructed to reduce data transmission and relieve bandwidth pressure. An online model predictive control algorithm is established to ensure stochastic stability and expected performance. Two examples are simulated to verify the effectiveness of the proposed design strategy.
INFORMATION SCIENCES
(2022)
Article
Business
Rana Faisal Hayat et al.
Summary: Distributed denial of service (DDoS) attacks and botnet-based attacks are critical security vulnerabilities in IoT environments. This article proposes a multilevel DDoS mitigation approach using blockchain technology to protect IoT devices. The proposed framework achieves significant improvements in throughput, latency, and CPU utilization compared to existing methods.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Computer Science, Information Systems
Anastasios N. Bikos et al.
Summary: With the rapid proliferation of IoT devices and sensors, the security implications for these devices are becoming more concerning. Blockchain technology, particularly the DAG-based implementation like IOTA, is seen as a promising solution to ensure the security of IoT devices and data. This paper provides a thorough analysis of existing security studies for IOTA and proposes future research recommendations to address the gaps and limitations in current security schemes.
Article
Computer Science, Information Systems
Ramin Firouzi et al.
Summary: Over the past decade, the Internet of Things (IoT) has shifted towards edge computing. Existing paradigms lack the use of edge devices for decision making, while distributed intelligence can strengthen IoT. To provide dynamic and efficient IoT services, integrating transport network control with distributed edge and cloud resources is necessary. A distributed SDN-based architecture is proposed, deploying Federated Learning Applications on the gateways to provide distributed intelligence at the edge.
Article
Computer Science, Hardware & Architecture
Dan Tang et al.
Summary: LDoS attacks reduce network performance by sending short-term high-pulse packets, making it indistinguishable from normal traffic. The proposed method in this paper, based on multi-feature fusion and CNN, effectively detects LDoS attacks.
MOBILE NETWORKS & APPLICATIONS
(2021)
Article
Computer Science, Information Systems
D. Aishwarya et al.
Summary: Closed Circuit Television (CCTV) based Surveillance is now a fundamental part of security systems, with the emergence of Edge Computing bringing hope for real time crime prevention. The proposed architecture employs a Convolutional Neural Network (CNN) to classify different actions and locate identified activities in image frames, proving to be efficient when tested against a dataset from SRM IST campus.
Article
Computer Science, Artificial Intelligence
Rajesh Kumar Dhanaraj et al.
Summary: The study introduces a method based on EGSA-SABD to detect and isolate BH attackers in WSNs by clustering sensor nodes and evaluating the possibility of BH attacks in deployed nodes. With this approach, the BH attack detection probability rate is significantly improved, and energy consumption is reduced significantly.
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Information Systems
Yasser Alharbi et al.
Summary: By utilizing the lightweight KNN optimization algorithm and information gain rate, this study aims to enhance the performance of DoS intrusion detection in IPv6 network environment through feature dimensionality reduction and distance optimization.
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
(2021)
Article
Construction & Building Technology
Vikas Hassija et al.
Summary: Smart healthcare is becoming more integrated with software, allowing control and monitoring of medical devices. However, this connectivity also poses security threats that need to be addressed.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Computer Science, Information Systems
Jaspreet Singh et al.
Summary: The increase in usage of embedded and IoT devices has led to a rise in LTE usage. Edge computing and multiaccess edge computing have been introduced to address challenges such as security and latency, while the proposed software-defined perimeter framework provides additional security protection.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Anil Kumar Rangisetti et al.
Summary: NFV and SDN technologies support the deployment of data centers in Cloud-Fog-Edge platforms. However, multi-tenant sharing platforms may lead to security issues for customer applications.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Hardware & Architecture
Dan Tang et al.
Summary: The LDoS attack exploits vulnerabilities in network protocols and application services, with attack traffic closely resembling normal traffic, making it difficult to detect using traditional methods. This study proposes a novel fractal residual based real-time detection method, FR-RED, which shows high accuracy in estimating the beginning and end of the LDoS attack in real-time.
IEEE TRANSACTIONS ON RELIABILITY
(2021)
Article
Telecommunications
Sathish Kumar et al.
Summary: The concept of Internet of Vehicles (IoV) involves sharing data between vehicles and infrastructure, which is important for enhancing vehicular services but also makes IoV vulnerable to security and privacy issues. Blockchain technology has been increasingly used to address security concerns in IoV due to its robust design.
TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES
(2021)
Article
Computer Science, Information Systems
Ye Ding et al.
Summary: The article introduces a system called FraudTrip, which effectively and efficiently detects unmetered taxi trips, solving the problem that existing detection methods cannot be applied to real-world scenarios.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Sakhnini Jacob et al.
Summary: The integration of sensors and communication technology in power systems, known as the smart grid, is an emerging topic in science and technology. One critical issue facing the smart grid is its increased vulnerability to cyber-threats. This paper presents a bibliometric survey of research papers focused on the security aspects of Internet of Things (IoT) aided smart grids, and offers insights into the types of cyber-threats, security mechanisms, and research gaps in this field.
INTERNET OF THINGS
(2021)
Review
Computer Science, Information Systems
S. Sullivan et al.
Summary: 5G envisions a broader range of services but also brings about increased hacker activity, necessitating strong security measures. This paper provides an objective overview of 5G security issues, focusing on vulnerabilities, challenges, and research problems in each OSI layer.
Article
Computer Science, Theory & Methods
Kunrui Cao et al.
Summary: This study investigates the secrecy transmission of uplink non-orthogonal multiple access (NOMA) with energy harvesting jammers. Three different friendly EH jammer selection schemes are proposed to enhance system secrecy performance. Analytical and numerical results show that these schemes can achieve better secrecy performance than conventional schemes without EH jammers, with different levels of secrecy diversity orders and convergence to the same effective secrecy throughput floor.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2021)
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Mikail Mohammed Salim et al.
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IEEE INTERNET OF THINGS JOURNAL
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ACM TRANSACTIONS ON INTERNET OF THINGS
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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
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IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
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IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
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IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
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