• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.341-347
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• 2022

This research is designed to help and offer hold up to complete the requirements of aged and disable in a home. The control approach and the tone approach are used to manage the house appliances. The major organize system implementation in technology of wireless to offer distant contact from a phone Internet Protocol connectivity for access and calculating strategy and appliance remotely. The planned system no need a committed server PC with value of parallel systems and offers a new communication-protocol to observe and control a house environment with more than just the switch functionality. To express the possibility and efficiency of this system, devices like as lights switches, power plugs, and motion-sensors have been included with the planned home control system and supply more security manage on the control with low electrical energy activate method. The rank of switches is corresponding in all this control system whereby all user interfaces indicate the real time existing status. This system planned to manage electrical-appliances and devices in house with reasonably low cost of design, user friendly interface, easily install and provide high security. Research community generally specified that the network "Reconnaissance Attacks" in IPv6 are usually impossible due to they will take huge challenge to carry out address scanning of 264 hosts in an IPv6 subnet."It being deployed of IPv6 shows that it definitely enhances security and undermines the probability". This research of the IPv6 addressing-strategies at present utilizes and planned a new strategy and move toward to "mitigate reconnaissance attacks".

• 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.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.107-118
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• 2021

The term Internet of Things (IoTs) refers to the future where things are known daily through the Internet, whether in one way or another, as it is done by the method of collecting various information from various sensors to form a huge network through which people, things and machines are helped to make a link between them at all time and anywhere. The IoTs is everywhere around us such as connected appliances, smart homes security systems and wearable health monitors. However, the question is what if there is a malfunction or outside interference that affects the work of these IoTs based devises? This is the reason of the spread of security causes great concern with the widespread availability of the Internet and Internet devices that are subject to many attacks. Since there aren't many studies that combines requirements, mechanisms, and the attacks of the IoTs, this paper which explores recent published studies between 2017 and 2020 considering different security approaches of protection related to the authentication, integrity, availability and confidentiality Additionally, the paper addresses the different types of attacks in IoTs. We have also addressed the different approaches aim to prevention mechanisms according to several researchers' conclusions and recommendations.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.219-230
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• 2023

Wireless Body Area Networks (WBANs) have made it easier for healthcare workers and patients to monitor patients' status continuously in real time. WBANs have complex and diverse network structures; thus, management and control can be challenging. Therefore, considering emerging Software-defined networks (SDN) with WBANs is a promising technology since SDN implements a new network management and design approach. The SDN concept is used in this study to create more adaptable and dynamic network architectures for WBANs. The study focuses on comparing the performance of two SDN controllers, POX and Ryu, using Mininet, an open-source simulation tool, to construct network topologies. The performance of the controllers is evaluated based on bandwidth, throughput, and round-trip time metrics for networks using an OpenFlow switch with sixteen nodes and a controller for each topology. The study finds that the choice of network controller can significantly impact network performance and suggests that monitoring network performance indicators is crucial for optimizing network performance. The project provides valuable insights into the performance of SDN-based WBANs using POX and Ryu controllers and highlights the importance of selecting the appropriate network controller for a given network architecture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2861-2880
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• 2018

Mobile Ad hoc Networks (MANETs) have become a viable platform owing to their potential of providing communication without any pre-existing infrastructure and central administrating authority. Mutual support and co-operation among nodes are prerequisites for performing functions in such networks. The scarcity of resources makes it economical for nodes to conserve their resources and misbehave by avoiding participation in the network. Therefore, a mechanism is required to detect and handle such misbehaving nodes and promote co-operation in the network. Existing techniques for handling misbehaving nodes focus only on their current behaviour without considering the antecedent behaviour of nodes. In real world, a node may dynamically change its behaviour in accordance to its requirements. Hence, an efficient mechanism is required for providing security against such misbehaviour. This paper proposes an Adaptive Security Model which contemplates the present as well as anterior behaviour of nodes for providing security against dynamic node behaviour. The adaptivity of the model is nested in its ability to requite well-behaving nodes and penalize misbehaving ones in conformity with their overall behaviour. Simulation results indicate the efficiency of proposed scheme in securing the network from the menace of dynamic behaviour of nodes.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.237-245
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• 2022

The prominence of IoTs (Internet of Things) and exponential advancement of computer networks has resulted in massive essential applications. Recognizing various cyber-attacks or anomalies in networks and establishing effective intrusion recognition systems are becoming increasingly vital to current security. MLTs (Machine Learning Techniques) can be developed for such data-driven intelligent recognition systems. Researchers have employed a TFDNNs (Tensor Flow Deep Neural Networks) and DCNNs (Deep Convolution Neural Networks) to recognize pirated software and malwares efficiently. However, tuning the amount of neurons in multiple layers with activation functions leads to learning error rates, degrading classifier's reliability. HTFDNNs ( Hybrid tensor flow DNNs) and MRNs (Modified Residual Networks) or Resnet CNNs were presented to recognize software piracy and malwares. This study proposes HTFDNNs to identify stolen software starting with plagiarized source codes. This work uses Tokens and weights for filtering noises while focusing on token's for identifying source code thefts. DLTs (Deep learning techniques) are then used to detect plagiarized sources. Data from Google Code Jam is used for finding software piracy. MRNs visualize colour images for identifying harms in networks using IoTs. Malware samples of Maling dataset is used for tests in this work.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.212-218
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• 2021

Low-power and Lossy Networks (LLNs) have become the common network infrastructure for a wide scope of Internet of Things (IoT) applications. For efficient routing in LLNs, IETF provides a standard solution, namely the IPv6 Routing Protocol for LLNs (RPL). It enables effective interconnectivity with IP networks and flexibly can meet the different application requirements of IoT deployments. However, it still suffers from different open issues, particularly in large-scale setups. These include the node unreachability problem which leads to increasing routing losses at RPL sink nodes. It is a result of the event of memory overflow at LLNs devices due to their limited hardware capabilities. Although this can be alleviated by the establishment of multi-sink topologies, RPL still lacks the support for effective load balancing among multiple sinks. In this paper, we address the need for an efficient multi-sink load balancing solution to enhance the performance of PRL in large-scale scenarios and alleviate the node unreachability problem. We propose a new RPL objective function, Multi-Sink Load Balancing Objective Function (MSLBOF), and introduce the Memory Utilization metrics. MSLBOF enables each RPL node to perform optimal sink selection in a way that insure better memory utilization and effective load balancing. Evaluation results demonstrate the efficiency of MSLBOF in decreasing packet loss and enhancing network stability, compared to MRHOF in standard RPL.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.137-144
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• 2022

Wireless community networks (WCNs) are considered another form of ownership of internet protocol (IP) networks, where community members manage and own every piece of equipment in a decentralized way, and routing for traffic is done in a cooperative manner. However, the current routing protocols for WCNs suffer from stability and scalability issues. In this paper, an enhanced routing protocol is proposed based on the optimized link state routing (OLSR) protocol to meet the standards of efficiency in terms of stability and scalability. The proposed routing protocol is enhanced through two phases: multicasting expansion and multipoint relay (MPR) selection based on an analytical hierarchical process (AHP). The experimental results demonstrate that the proposed routing protocol outperforms the OLSR protocol in terms of network control overhead and packet delivery ratio by 18% and 1% respectively.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.207-213
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• 2021

Networks in Mobile ad hoc contain distribution and do not have a predefined structure which practically means that network modes can play the role of being clients or servers. The routing protocols used in mobile Ad-hoc networks (MANETs) are characterized by limited bandwidth, mobility, limited power supply, and routing protocols. Hybrid routing protocols solve the delay problem of reactive routing protocols and the routing overhead of proactive routing protocols. The Ant Colony Optimization (ACO) algorithm is used to solve other real-life problems such as the travelling salesman problem, capacity planning, and the vehicle routing challenge. Bio-inspired methods have probed lethal in helping to solve the problem domains in these networks. Hybrid routing protocols combine the distance vector routing protocol (DVRP) and the link-state routing protocol (LSRP) to solve the routing problem.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.97-102
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• 2022

Network intrusion detection is becoming an increasing necessity for both organizations and individuals alike. Detecting intrusions is one of the major components that aims to prevent information compromise. Automated systems have been put to use due to the voluminous nature of the domain. The major challenge for automated models is the noise and data imbalance components contained in the network transactions. This work proposes an ensemble model, Attribute Subset Selector Bagging (ASUB) that can be used to effectively handle noise and data imbalance. The proposed model performs attribute subset based bag creation, leading to reduction of the influence of the noise factor. The constructed bagging model is heterogeneous in nature, hence leading to effective imbalance handling. Experiments were conducted on the standard intrusion detection datasets KDD CUP 99, Koyoto 2006 and NSL KDD. Results show effective performances, showing the high performance of the model.