作者：
Ranade, PriyankaUniversity of Maryland
Baltimore County Department of Computer Science & Electrical Engineering 1000 Hilltop Circle BaltimoreMD21250 United States
Storytelling is an innate part of language-based communication. Today, current events are reported via Open Source Intelligence (OSINT) sources like news websites, blogs, and discussion forums. Scattered and fragmente...
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In this research, nature inspired metaheuristic optimization algorithms: Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) Techniques are formulated to tune optimal combinations of PID controller parameters...
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The urgent necessity of satellite cybersecurity was shown by the 2019 Galileo attack. Due to the rise in cyber risks and attacks caused by connected devices and the internet of things (IoT), advanced cybersecurity mod...
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The urgent necessity of satellite cybersecurity was shown by the 2019 Galileo attack. Due to the rise in cyber risks and attacks caused by connected devices and the internet of things (IoT), advanced cybersecurity models that can detect and respond to threats in real time are needed. AI can improve cybersecurity by enabling real-time cyberattack detection and response. This paper presents an AI-enabled satellite cybersecurity model to prevent hacks like the 2019 Galileo attack. Using satellite telemetry data, a deep learning algorithm detects satellite system behaviour patterns and abnormalities. The application can detect and classify cyber threats such unauthorized access, malware infestations, and data manipulation, and notify system operators in real time. Host and network-based intrusion detection systems may monitor satellite network endpoints. AI-based intrusion detection, firewalls, and endpoint security prevent cyberattacks. The firewall prevents unauthorized access, and the intrusion detection system (IDS) monitors satellite network trace for suspicious activities. Endpoint security can protect satellite system equipment and apps against malware and other cyberattacks. Vulnerability and patch management may update malware signatures daily. The simulation proved that the AI-enabled model can identify and react to cyber threats in real time, decreasing attack risk. Like Azure Sentinel, our AI will identify new threats, tactics, and mitigations. Integrating AI-based intrusion detection systems with satellite system telemetry data processing systems is recommended. New cyberthreats need model monitoring and updating. AI will enable cyberattacks as it improves. Reinforcement learning modules can assist in AI-based intrusion detection. This paper presents an AI- enabled cybersecurity paradigm for satellites, spacecraft, and ground control stations. The technique may improve system security and resilience, reduce cyber-attack risk, and protect critical infrastruc
This paper proposes a millimeter-wave substrate-integrated waveguide (SIW) multiplexer with high channel scalability and high isolation. To allow flexible increase in the number of channels while reducing the loading ...
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The primary focus of this paper is to evaluate the channel capacity of a Terahertz (THz) communication system using a Multiple Input Multiple Output (MIMO) technique. By deriving mathematical expressions for channel c...
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In this paper, in an effort to implement an unsupervised learning algorithm for silicon neurons, we present a mixed-signal Leaky Integrate-And-Fire (LIF) neuron with two different integrated homeostasis circuits using...
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Improving computer networks performance is a tremendous need in our life for meeting ever-changing quality of service (QoS) requirements of interesting applications. We are searching continuously on how to increase th...
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After Industry 4.0 was proposed, cyber-physical systems (CPS) were also introduced into the industrial environment called the industrial CPS. Internet-of-Things (IoT) services in the industry make intelligent decision...
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The energy efficiency of battery-operated sensing devices in IoT is a critical research area that needs further exploration. This paper employs lightweight reinforcement learning to improve energy savings in large-sca...
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Transition metal dichalcogenide(TMD)layered semiconductors possess immense potential in the design of photonic,electronic,optoelectronic,and sensor ***,the sub-bandgap light absorption of TMD in the range from near-in...
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Transition metal dichalcogenide(TMD)layered semiconductors possess immense potential in the design of photonic,electronic,optoelectronic,and sensor ***,the sub-bandgap light absorption of TMD in the range from near-infrared(NIR)to short-wavelength infrared(SWIR)is insufficient for applications beyond the bandgap ***,we report that the sub-bandgap photoresponse of MoS_(2)/Au heterostructures can be robustly modulated by the electrode fabrication method *** observed up to 60%sub-bandgap absorption in the MoS_(2)/Au heterostructure,which includes the hybridized interface,where the Au layer was applied via sputter *** greatly enhanced absorption of sub-bandgap light is due to the planar cavity formed by MoS_(2) and Au;as such,the absorption spectrum can be tuned by altering the thickness of the MoS_(2) *** in the SWIR wavelength range increases due to increased absorption,which means that broad wavelength detection from visible toward SWIR is *** also achieved rapid photoresponse(~150μs)and high responsivity(17 mA W^(-1))at an excitation wavelength of *** findings demonstrate a facile method for optical property modulation using metal electrode engineering and for realizing SWIR photodetection in wide-bandgap 2D materials.
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