Опубликована: Авг. 23, 2024
Язык: Английский
Sensors, Год журнала: 2023, Номер 23(21), С. 8749 - 8749
Опубликована: Окт. 26, 2023
This research paper investigates the integration of blockchain technology to enhance security Android mobile app data storage. Blockchain holds potential significantly improve and reliability, yet faces notable challenges such as scalability, performance, cost, complexity. In this study, we begin by providing a thorough review prior identifying critical gaps in field. Android’s dominant position market justifies our focus on platform. Additionally, delve into historical evolution its relevance modern dedicated section. Our examination encryption techniques effectiveness securing storage yields important insights. We discuss advantages over traditional methods their practical implications. The central contribution is Blockchain-based Secure Data Storage (BSADS) framework, now consisting six comprehensive layers. address related costs, mobile-specific constraints, proposing technical optimization strategies overcome these obstacles effectively. To maintain transparency provide holistic perspective, acknowledge limitations study. Furthermore, outline future directions, stressing importance leveraging lightweight nodes, tackling scalability issues, integrating emerging technologies, enhancing user experiences while adhering regulatory requirements.
Язык: Английский
Процитировано
14
Artificial Intelligence Review, Год журнала: 2025, Номер 58(6)
Опубликована: Март 21, 2025
Язык: Английский
Процитировано
0
IEEE Access, Год журнала: 2024, Номер 12, С. 63282 - 63291
Опубликована: Янв. 1, 2024
Cybersecurity in the Internet of Things (IoT) is practice implementing measures to secure networks and connected devices from data breaches, cyber threats, unauthorized access. It essential owing increasing interconnectivity devices, ranging smart home appliances industrial sensors. The potential attack surface expands, necessitating strong cybersecurity protect sensitive data, ensure privacy, prevent disruptions critical services with these number IoT devices. Artificial intelligence (AI) technologies, particularly deep learning (DL) machine (ML) approaches, hold mitigate identify cyberattacks on networks. DL demonstrates promise for effectively preventing detecting security threats within Despite importance Intrusion Detection Systems (IDS) maintaining confidentiality by suspicious activities, classical IDS solutions might face difficulties platform. Therefore, this study presents an Orca Algorithm Ensemble Learning cyberattack detection classification (AOAEL-CDC) methodology environment IoT. presented AOAEL-CDC technique exploited feature selection (FS) approach ensemble recognition identification atmosphere. In developed model, takes place using AOA technique. For process, process carried out use three models such as bidirectional long short-term memory (BiLSTM), gated recurrent unit (GRU), extreme (ELM). Finally, hyperparameter range techniques marine predator's algorithm (MPA). To examine performance analysis methodology, a series simulations take benchmark dataset. An extensive comparative reported that BCODL-SDSC reaches effective other maximum accuracy 99.31%.
Язык: Английский
Процитировано
4
Transactions on Emerging Telecommunications Technologies, Год журнала: 2025, Номер 36(1)
Опубликована: Янв. 1, 2025
ABSTRACT The Internet of Things (IoT) is transforming numerous sectors but also presents unique security challenges due to its interconnected and resource‐constrained devices. This study introduces the Bidirectional Gaussian Hummingbird Optimized End‐to‐End Blockchain (BGHO‐E2EB) model, designed detect classify cyberattacks within IoT environments. Unlike preventive approaches, developed model focuses on real‐time detection categorization attacks, enabling timely responses emerging threats. proposed integrates blockchain technology through Ethereum‐based smart contracts enhance integrity data exchanges networks. Additionally, a Artificial Algorithm employed for optimal feature selection, minimizing dimensionality computational load. A Long Short‐Term Memory (Bi‐LSTM) network further improves model's capability by accurately detecting categorizing cyber threats based selected features. Adam optimizer used efficient parameter tuning Bi‐LSTM network, ensuring high‐performance cyberattack detection. was evaluated using established benchmarks, including UNSW‐NB15, BOT‐IoT, NSL‐KDD datasets, accomplishing an accuracy 98.7%, precision 96.3%, level 99.5%, significantly outperforming traditional methods. These results demonstrate effectiveness BGHO‐E2EB as robust tool classifying in networks, making it suitable real‐world deployment dynamic environments where paramount.
Язык: Английский
Процитировано
0
Alexandria Engineering Journal, Год журнала: 2025, Номер 121, С. 128 - 137
Опубликована: Фев. 27, 2025
Язык: Английский
Процитировано
0
Communications in computer and information science, Год журнала: 2025, Номер unknown, С. 313 - 322
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
International Journal of Innovations in Science Engineering and Management., Год журнала: 2025, Номер unknown, С. 27 - 33
Опубликована: Апрель 12, 2025
Cybersecurity risks are heightened by the quick proliferation of smart things and growing frequency severity intrusions. primarily guards against external assaults on data, software, hardware that part a system with an active internet connection. is used organizations to guard unwanted access their records systems. In this article review various literature’s study deep learning in cybersecurity. Additionally, explore challenges, application future prospects Cybersecurity. It concluded plays crucial role cybersecurity enhancing intrusion detection, malware classification, anomaly detection. Techniques like SMOTE address class imbalance, while models such as CatBoost XGBoost outperform identifying cyber threats. Challenges include handling untidy, hierarchical optimizing model parameters, balancing accuracy training time. Future advancements will focus improving detection performance, securing neural networks adversarial attacks, for resource-constrained environments. Integrating multiple parallel can enhance efficiency, making vital tool IoT addressing evolving
Язык: Английский
Процитировано
0
Computers & Electrical Engineering, Год журнала: 2025, Номер 124, С. 110368 - 110368
Опубликована: Апрель 19, 2025
Язык: Английский
Процитировано
0
Information, Год журнала: 2023, Номер 14(12), С. 666 - 666
Опубликована: Дек. 18, 2023
The increasing complexity and connectivity of automotive systems have raised concerns about their vulnerability to security breaches. As a result, the integration formal methods validation techniques has become crucial in ensuring systems. This survey research paper aims provide comprehensive overview current state-of-the-art employed industry for system security. begins by discussing challenges associated with potential consequences Then, it explores various methods, such as model checking, theorem proving, abstract interpretation, which been widely used analyze verify properties Additionally, highlights ensure effectiveness measures, including penetration testing, fault injection, fuzz testing. Furthermore, examines within development lifecycle, requirements engineering, design, implementation, testing phases. It discusses benefits limitations these approaches, considering factors scalability, efficiency, applicability real-world Through an extensive review relevant literature case studies, this provides insights into trends, challenges, open questions field findings can serve valuable resource researchers, practitioners, policymakers involved development, evaluation secure
Язык: Английский
Процитировано
9
Cluster Computing, Год журнала: 2024, Номер 27(8), С. 10467 - 10485
Опубликована: Май 6, 2024
Abstract The Industrial Internet of Things (IIoT) is a paradigm that enables the integration cyber-physical systems in critical infrastructures, such as power grids, water distribution networks, and transportation systems. IIoT devices, sensors, actuators, controllers, can provide various benefits, performance optimization, efficiency improvement, remote management. However, these devices also pose new security risks challenges, they be targeted by malicious actors to disrupt normal operation infrastructures are connected or cause physical damage harm. Therefore, it essential develop effective intelligent solutions detect prevent attacks on ensure resilience infrastructures. In this paper, we present comprehensive analysis types impacts based literature review data real-world incidents. We classify into four categories: denial-of-service, manipulation, device hijacking, tampering. discuss potential consequences safety, reliability, availability then propose an expert system using artificial intelligence techniques, rule-based reasoning, anomaly detection, reinforcement learning. describe architecture implementation our system, which consists three main components: collector, analyzer, actuator. table summarizes features capabilities compared existing solutions. evaluate effectiveness testbed consisting programmable logic controllers (PLCs) protocols, Modbus MQTT. simulate measure accuracy, latency, overhead system. Our results show successfully mitigate different with high accuracy low latency overhead. demonstrate enhance preventing minimizing devices.
Язык: Английский
Процитировано
2