• Title/Summary/Keyword: information and computer technology

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Implementing Firewall to Mitigate YOYO Attack on Multi Master Cluster Nodes Using Fail2Ban

  • Muhammad Faraz Hyder;Muhammad Umer Farooq;Mustafa Latif;Faizan Razi Khan;Abdul Hameed;Noor Qayyum Khan;M. Ahsan Siddiqui
    • International Journal of Computer Science & Network Security
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    • 제23권2호
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    • pp.126-132
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    • 2023
  • Web technology is evolving with the passage of time, from a single node server to high availability and then in the form of Kubernetes. In recent years, the research community have been trying to provide high availability in the form of multi master cluster with a solid election algorithm. This is helpful in increasing the resources in the form of pods inside the worker node. There are new impact of known DDoS attack, which is utilizing the resources at its peak, known as Yoyo attack. It is kind of burst attack that can utilize CPU and memory to its limit and provide legit visitors with a bad experience. In this research, we tried to mitigate the Yoyo attack by introducing a firewall at load-balancer level to prevent the attack from going to the cluster network.

Customer Activity Recognition System using Image Processing

  • Waqas, Maria;Nasir, Mauizah;Samdani, Adeel Hussain;Naz, Habiba;Tanveer, Maheen
    • International Journal of Computer Science & Network Security
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    • 제21권9호
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    • pp.63-66
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    • 2021
  • The technological advancement in computer vision has made system like grab-and-go grocery a reality. Now all the shoppers have to do now is to walk in grab the items and go out without having to wait in the long queues. This paper presents an intelligent retail environment system that is capable of monitoring and tracking customer's activity during shopping based on their interaction with the shelf. It aims to develop a system that is low cost, easy to mount and exhibit adequate performance in real environment.

SYN Flood DoS Detection System Using Time Dependent Finite Automata

  • Noura AlDossary;Sarah AlQahtani;Reem Alzaher;Atta-ur-Rahman
    • International Journal of Computer Science & Network Security
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    • 제23권6호
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    • pp.147-154
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    • 2023
  • Network intrusion refers to any unauthorized penetration or activity on a computer network. This upsets the confidentiality, integrity, and availability of the network system. One of the major threats to any system's availability is a Denial-of-Service (DoS) attack, which is intended to deny a legitimate user access to resources. Therefore, due to the complexity of DoS attacks, it is increasingly important to abstract and describe these attacks in a way that will be effectively detected. The automaton theory is used in this paper to implement a SYN Flood detection system based on Time-Dependent Finite Automata (TDFA).

Network Forensics and Intrusion Detection in MQTT-Based Smart Homes

  • Lama AlNabulsi;Sireen AlGhamdi;Ghala AlMuhawis;Ghada AlSaif;Fouz AlKhaldi;Maryam AlDossary;Hussian AlAttas;Abdullah AlMuhaideb
    • International Journal of Computer Science & Network Security
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    • 제23권4호
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    • pp.95-102
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    • 2023
  • The emergence of Internet of Things (IoT) into our daily lives has grown rapidly. It's been integrated to our homes, cars, and cities, increasing the intelligence of devices involved in communications. Enormous amount of data is exchanged over smart devices through the internet, which raises security concerns in regards of privacy evasion. This paper is focused on the forensics and intrusion detection on one of the most common protocols in IoT environments, especially smart home environments, which is the Message Queuing Telemetry Transport (MQTT) protocol. The paper covers general IoT infrastructure, MQTT protocol and attacks conducted on it, and multiple network forensics frameworks in smart homes. Furthermore, a machine learning model is developed and tested to detect several types of attacks in an IoT network. A forensics tool (MQTTracker) is proposed to contribute to the investigation of MQTT protocol in order to provide a safer technological future in the warmth of people's homes. The MQTT-IOT-IDS2020 dataset is used to train the machine learning model. In addition, different attack detection algorithms are compared to ensure the suitable algorithm is chosen to perform accurate classification of attacks within MQTT traffic.

Mobile Botnet Attacks - an Emerging Threat: Classification, Review and Open Issues

  • Karim, Ahmad;Ali Shah, Syed Adeel;Salleh, Rosli Bin;Arif, Muhammad;Noor, Rafidah Md;Shamshirband, Shahaboddin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권4호
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    • pp.1471-1492
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    • 2015
  • The rapid development of smartphone technologies have resulted in the evolution of mobile botnets. The implications of botnets have inspired attention from the academia and the industry alike, which includes vendors, investors, hackers, and researcher community. Above all, the capability of botnets is uncovered through a wide range of malicious activities, such as distributed denial of service (DDoS), theft of business information, remote access, online or click fraud, phishing, malware distribution, spam emails, and building mobile devices for the illegitimate exchange of information and materials. In this study, we investigate mobile botnet attacks by exploring attack vectors and subsequently present a well-defined thematic taxonomy. By identifying the significant parameters from the taxonomy, we compared the effects of existing mobile botnets on commercial platforms as well as open source mobile operating system platforms. The parameters for review include mobile botnet architecture, platform, target audience, vulnerabilities or loopholes, operational impact, and detection approaches. In relation to our findings, research challenges are then presented in this domain.

EM 알고리즘을 이용한 전문용어 온톨로지 클래스간 관계 정의를 위한 동사 클러스터링 (Verb Clustering for Defining Relations between Ontology Classes of Technical Terms Using EM Algorithm)

  • 김미훈;남상협;이용훈;이종혁
    • 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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    • 한국정보과학회언어공학연구회 2007년도 제19회 한글 및 한국어 정보처리 학술대회
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    • pp.233-240
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    • 2007
  • 온톨로지 구축에서 클래스간 관계 설정은 중요한 부분이다. 본 논문에서는 클래스간 상 하위 관계 외의 관계 설정을 위한 클래스간 관계 자동 정의를 목적으로 의존구문분석의 (주어, 용언) (목적어, 용언) 쌍들을 추출하고, 이렇게 추출된 데이터를 이용하여 용언들을 클러스터링 하는 방법을 제안한다. 도메인 전문 코퍼스 데이터 희귀성 문제를 해결하고자, 웹검색을 결합한 방식을 선택하여 도메인 온톨로지 구축 클래스간 관계 자동 설정에 대한 방법론을 제시한다.

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A VIDEO GEOGRAPHIC INFORMATION SYSTEM FOR SUPPORTING BI-DIRECTIONAL SEARCH FOR VIDEO DATA AND GEOGRAPHIC INFORMATION

  • Yoo, Jea-Jun;Joo, In-Hak;Park, Jong-Huyn;Lee, Jong-Hun
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.151-156
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    • 2002
  • Recently, as the geographic information system (GIS) which searches, manages geographic information is used more widely, there is more requests for some systems which can search and display more actual and realistic information. As a response to these requests, the video geographic information system which connects video data obtained by using cameras and geographic information as it is by displaying the obtained video data is being more popular. However, because most existing video geographic information systems consider video data as an attribute of geographic information or use simple one-way links from geographic information to video data to connect video data with geographic information, they support only displaying video data through searching geographic information. In this paper, we design and implement a video geographic information system which connects video data with geographic information and supports hi-directional search; searching geographic information through searching video data and searching video data through searching geographic information. To do this, we 1) propose an ER data model to represent connection information related to video data, geographic information, 2) propose a process to extract and to construct connection information from video data and geographic information, 3) show a component based system architecture to organize the video geographic information system.

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A Neuro-Fuzzy Based Circular Pattern Recognition Circuit Using Current-mode Techniques

  • Eguchi, Kei;Ueno, Fumio;Tabata, Toru;Zhu, Hongbing;Tatae, Yoshiaki
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 ITC-CSCC -2
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    • pp.1029-1032
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    • 2000
  • A neuro-fuzzy based circuit to recognize circuit pat-terns is proposed in this paper. The simple algorithm and exemption from the use of template patterns as well as multipliers enable the proposed circuit to implement on the hardware of an economical scale. Furthermore, thanks to the circuit design by using current-mode techniques, the proposed circuit call achieve easy extendability of tile circuit and efficient pattern recognition with high-speed. The validity of the proposed algorithm and tile circuit design is confirmed by computer simulations. The proposed pattern recognition circuit is integrable by a standard CMOS technology.

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Implementation of ML Algorithm for Mung Bean Classification using Smart Phone

  • Almutairi, Mubarak;Mutiullah, Mutiullah;Munir, Kashif;Hashmi, Shadab Alam
    • International Journal of Computer Science & Network Security
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    • 제21권11호
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    • pp.89-96
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    • 2021
  • This work is an extension of my work presented a robust and economically efficient method for the Discrimination of four Mung-Beans [1] varieties based on quantitative parameters. Due to the advancement of technology, users try to find the solutions to their daily life problems using smartphones but still for computing power and memory. Hence, there is a need to find the best classifier to classify the Mung-Beans using already suggested features in previous work with minimum memory requirements and computational power. To achieve this study's goal, we take the experiments on various supervised classifiers with simple architecture and calculations and give the robust performance on the most relevant 10 suggested features selected by Fisher Co-efficient, Probability of Error, Mutual Information, and wavelet features. After the analysis, we replace the Artificial Neural Network and Deep learning with a classifier that gives approximately the same classification results as the above classifier but is efficient in terms of resources and time complexity. This classifier is easily implemented in the smartphone environment.