Information assurance and security

Abstract Protecting residential properties through CCTV surveillance has become a crucial aspect of contemporary living. In the age of data-driven security, detecting unusual and infrequent patterns within CCTV footage is of significant importance. Conventional anomaly detection methods often need help to handle the intricacies and distinctiveness of home environments, where family members and potential intruders co-exist. To address these challenges, this research incorporates extensive datasets, various machine-learning techniques, and thorough evaluation measures to pinpoint rare patterns that might signal threats to residential premises. These findings provide valuable insights for homeowners, security professionals, and developers working on surveillance systems.

Mintu Movi

Abdul Jabbar P

Journal of Information assurance and security

Unveiling Rare Patterns: Anomaly Detection in CCTV Footage for Safeguarding Home Premises

揭示罕见模式：用于保护家庭场所的监控录像异常检测

Abstract Transportation systems are a necessity of modern life. To achieve safe and fast transportation, the intelligent transportation system is being developed. In this system, the main base station facilitates communication between vehicles and all other roadside entities using vehicle to everything networks. Various technologies have been built to support this communication. After receiving the information, vehicles can make their own decisions. This data communication is done in real time. But, if any of these data packets are dropped, the vehicle will make inaccurate decisions, so we need to have reliable data communication. All data communication will be accomplished through a system of neighboring nodes. There may be some malfunctioning nodes that lose packets in between, so a trusted and reliable link is necessary for efficient and secure data communication among the nodes. This paper presents a survey of various algorithms designed for the reliable delivery of data packets, algorithms for secure data transfer, and various types of attacks. After that, various schemes for building trust in parties sending data packets if also presented for survey.

Wajid Ali

Shalini Z. Ninoria

Gulista Khan

Kamal Kumar Gola

State of the Art, Reliable, and Trusted Communication in Vehicle to Everything (V2X) Networks

车辆到一切（V2X）网络中的最先进、可靠和可信通信

Abstract Agriculture represents a major turning point in economic development, and many modern technologies, such as the Internet of Things (IoT) and blockchain technology, are playing an effective role in making farming practices simpler and smarter. IoT is a common model of information technology, and its use in agriculture has become widespread, with integrated applications for recording and updating various activities. Sensors make it easier for farmers to gather basic information and details in the field, for example by monitoring soil and crops. However, with the growing sophistication of IoT attacks, the threat vectors are increasing. This is where blockchain technology comes in to address the security and privacy challenges associated with IoT use. Blockchain can extend the scope of IoT applications. This article aims to present a comprehensive review of existing and recent research concerning blockchain and IoT technologies, as well as future research directions in the field of intelligent agricultural systems.

Fatma Marzougui

Mohamed Elleuch

Monji Kherallah

Survey of Recent Literature on Advanced Technologies in Digital Agriculture: Internet of Things and Blockchain

数字农业先进技术近期文献综述：物联网与区块链

Abstract In today’s world, document security has become essential. That stands for either a hard copy or a soft copy of any document. The concept of online, or digital, transactions has become increasingly prevalent in recent years. To accommodate these transactions, there arises a need to transform hard copies of documents into soft copies. This would further lead to a crisis where there is a need to provide security for these soft copies. The documents, when maintained as soft copies, are vulnerable to all sorts of attacks, either through bugs and/or human errors. These human errors are the ones that need to be taken care of on a large scale. Some people believe in sharing documents online with their peers or others of the same interest. This may lead to the misuse of these documents when they fall into the wrong hands. Then, the security of these documents becomes a topic to dwell on. In this paper, a study was conducted based on the ways to secure data and the techniques or algorithms that can be used to do it. There are many different technologies based on the type of data that is being encrypted. These are being discussed along with the papers that were taken into account for various data Security methods.

C. Yamini

N. Priya

Security Features on and with Documents: A Survey

文件及其上的安全特征：一项调查

Abstract Intrusion detection systems (IDS) are an important tool for securing computer networks from various types of cyberattacks. The increasing complexity of network attacks demands more sophisticated approaches to intrusion detection. This paper presents an innovative method for IDS that involves combining Z-Score outlier detection, KMeans clustering, and Random Forest classification techniques. We tested our methodology using the CICIDS2017 dataset, which is a standardization dataset for intrusion detection that is frequently utilized. Our proposed approach first uses Z-Score outlier detection to identify abnormal traffic flows in the network. Next, KMeans clustering is used to group the traffic flows into different clusters based on their similarity. Finally, Random Forest classification is used to classify each traffic flow into normal or abnormal categories. Based on our experimental results, our approach for intrusion detection shows superior performance compared to several other state-of-the-art methods in terms of accuracy and precision. Our proposed method achieved an accuracy rate of 95.75% and a precision of 95.76%, surpassing the performance of KNN, SVM, and decision trees approaches. In conclusion, the proposed Z-K-R approach offers a promising solution for IDS by leveraging the strengths of Z-Score outlier detection, KMeans clustering, and Random Forest classification techniques. This strategy has the potential to increase the efficiency of IDS and boost network security in applications that take place in the real world.

S. Sandosh

Akila Bala

Nithin Kodipyaka

Z-K-R: A Novel Framework in Intrusion Detection system through enhanced techniques

Z-K-R：通过增强技术实现入侵检测系统的新型框架

Abstract Face recognition plays an important role in various areas of life and has attracted the interest of many scholars in the domain of computer vision, pattern recognition, and artificial intelligence. Most of the existing techniques adopted in the recognition of humans through facial images were found to be efficient but are computationally expensive due to the high dimension of facial images, which in turn increases processing speed and memory consumption. In this research, an enhanced model is proposed. Consequently, 6 facial images from 60 individuals were locally acquired using a Canon digital camera of default size 1200 × 1200. Thereafter, 240 images were used for training, while 120 images were used for testing. The enhanced model reduced the high dimension of images with improved feature extraction accuracy. Results showed significant improvement when compared to the existing ones.

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Journal Impact	0.12
国际分区	COMPUTER SCIENCE, INFORMATION SYSTEMS(Q4)

出版信息	出版商: ，出版周期: ，期刊类型: journal，开源期刊: 否
基本数据	创刊年份: ，原创研究文献占比: 100.00%，自引率:0.00%， Gold OA占比: 0.00%

Information assurance and security

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Unveiling Rare Patterns: Anomaly Detection in CCTV Footage for Safeguarding Home Premises

State of the Art, Reliable, and Trusted Communication in Vehicle to Everything (V2X) Networks

Survey of Recent Literature on Advanced Technologies in Digital Agriculture: Internet of Things and Blockchain

Security Features on and with Documents: A Survey

Z-K-R: A Novel Framework in Intrusion Detection system through enhanced techniques

Security Features on and with Documents: A Survey

Z-K-R: A Novel Framework in Intrusion Detection system through enhanced techniques

Development of an Enhanced Human Face Recognition Model

Unveiling Rare Patterns: Anomaly Detection in CCTV Footage for Safeguarding Home Premises

State of the Art, Reliable, and Trusted Communication in Vehicle to Everything (V2X) Networks