The Intelligent Surveillance Support System(ISSS) is an innovative software solution that enables real-time monitoring and analysis of security footage to detect and identify potential threats. This system incorporate...
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The big data clustering is a requisite for generating the data in the digitalised globe. The old-fashioned clustering approaches are not large sized and highly unorganised big data. Thus, to obtain the efficiency of b...
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In the current digital era, video surveillance has become a part of daily life. The person re-identification(re-ID) task involves choosing a person as a target in one camera feed and recognizing that target in footage...
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Facial image captured under uncontrolled environment often degraded by blur, noise and low-light effect which significantly affect the performance of different real life applications. To solve this problem numerous fa...
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With the popularity of the Internet of Vehicles(IoV),a large amount of data is being generated every *** to securely share data between the IoV operator and various value-added service providers becomes one of the cri...
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With the popularity of the Internet of Vehicles(IoV),a large amount of data is being generated every *** to securely share data between the IoV operator and various value-added service providers becomes one of the critical *** to its flexible and efficient fine-grained access control feature,Ciphertext-Policy Attribute-Based Encryption(CP-ABE)is suitable for data sharing in ***,there are many flaws in most existing CP-ABE schemes,such as attribute privacy leakage and key *** paper proposes a Traceable and Revocable CP-ABE-based Data Sharing with Partially hidden policy for IoV(TRE-DSP).A partially hidden access structure is adopted to hide sensitive user attribute values,and attribute categories are sent along with the ciphertext to effectively avoid privacy *** addition,key tracking and malicious user revocation are introduced with broadcast encryption to prevent key *** the main computation task is outsourced to the cloud,the burden of the user side is relatively *** of security and performance demonstrates that TRE-DSP is more secure and practical for data sharing in IoV.
Web Navigation Prediction (WNP) has been popularly used for finding future probable web pages. Obtaining relevant information from a large web is challenging, as its size is growing with every second. Web data may con...
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The Internet has become an important origin of text information, which is then used inside a wide range of research domains. This has been regarded as a necessary foundation for institutions to obtain valuable informa...
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Occurrence of crimes has been on the constant rise despite the emerging discoveries and advancements in the technological field in the past *** of the most tedious tasks is to track a suspect once a crime is *** most ...
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Occurrence of crimes has been on the constant rise despite the emerging discoveries and advancements in the technological field in the past *** of the most tedious tasks is to track a suspect once a crime is *** most of the crimes are committed by individuals who have a history of felonies,it is essential for a monitoring system that does not just detect the person’s face who has committed the crime,but also their ***,a smart criminal detection and identification system that makes use of the OpenCV Deep Neural Network(DNN)model which employs a Single Shot Multibox Detector for detection of face and an auto-encoder model in which the encoder part is used for matching the captured facial images with the criminals has been *** detection and extraction of the face in the image by face cropping,the captured face is then compared with the images in the *** comparison is performed by calculating the similarity value between each pair of images that are obtained by using the Cosine Similarity *** plotting the values in a graph to find the threshold value,we conclude that the confidence rate of the encoder model is 0.75 and above.
The ubiquity of handheld devices and easy access to the Internet help users get easy and quick updates from social media. Generally, people share information with their friends and groups without inspecting the posts...
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The proposed work objective is to adapt Online social networking (OSN) is a type of interactive computer-mediated technology that allows people to share information through virtual networks. The microblogging feature ...
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The proposed work objective is to adapt Online social networking (OSN) is a type of interactive computer-mediated technology that allows people to share information through virtual networks. The microblogging feature of Twitter makes cyberspace prominent (usually accessed via the dark web). The work used the datasets and considered the Scrape Twitter Data (Tweets) in Python using the SN-Scrape module and Twitter 4j API in JAVA to extract social data based on hashtags, which is used to select and access tweets for dataset design from a profile on the Twitter platform based on locations, keywords, and hashtags. The experiments contain two datasets. The first dataset has over 1700 tweets with a focus on location as a keypoint (hacking-for-fun data, cyber-violence data, and vulnerability injector data), whereas the second dataset only comprises 370 tweets with a focus on reposting of tweet status as a keypoint. The method used is focused on a new system model for analysing Twitter data and detecting terrorist attacks. The weights of susceptible keywords are found using a ternary search by the Aho-Corasick algorithm (ACA) for conducting signature and pattern matching. The result represents the ACA used to perform signature matching for assigning weights to extracted words of tweet. ML is used to evaluate Twitter data for classifying patterns and determining the behaviour to identify if a person is a terrorist. SVM (Support Vector Machine) proved to be a more accurate classifier for predicting terrorist attacks compared to other classifiers (KNN- K-Nearest Neighbour and NB-Naïve Bayes). The 1st dataset shows the KNN-Acc. -98.38% and SVM Accuracy as 98.85%, whereas the 2nd dataset shows the KNN-Acc. -91.68% and SVM Accuracy as 93.97%. The proposed work concludes that the generated weights are classified (cyber-violence, vulnerability injector, and hacking-for-fun) for further feature classification. Machine learning (ML) [KNN and SVM] is used to predict the occurrence and
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