Biblio

Recognising user's risky behaviours in real-time is an important element of providing appropriate solutions and recommending suitable actions for responding to cybersecurity threats. Employing user modelling and machine learning can make this process automated by requires high-performance intelligent agent to create the user security profile. User profiling is the process of producing a profile of the user from historical information and past details. This research tries to identify the monitoring factors and suggests a novel observation solution to create high-performance sensors to generate the user security profile for a home user concerning the user's privacy. This observer agent helps to create a decision-making model that influences the user's decision following real-time threats or risky behaviours.

A Distributed Denial of Service (DDoS) attack is an attack that compromised the bandwidth of the whole network by choking down all the available network resources which are publically available, thus makes access to that resource unavailable. The DDoS attack is more vulnerable than a normal DoS attack because here the sources of attack origin are more than one, so users cannot even estimate how to detect and where to take actions so that attacks can be dissolved. This paper proposed a unique approach for DDoS detection using the shortest path algorithm. This Paper suggests that the remedy that must be taken in order to counter-affect the DDoS attack in a smart home network.

This paper describes a system that comprises of control, safety and security subsystem for industries and homes. The entire system is based on the Bolt IoT platform. Using this system, the user can control the devices such as LEDs, speed of the fan or DC motor, monitor the temperature of the premises with an alert sub-system for critical temperatures through SMS and call, monitor the presence of anyone inside the premises with an alert sub-system about any intrusion through SMS and call. If the system is used specifically in any industry then instead of monitoring the temperature any other physical quantity, which is critical for that industry, can be monitored using suitable sensors. In addition, the cloud connectivity is provided to the system using the Bolt IoT module and temperature data is sent to the cloud where using machine-learning algorithm the future temperature is predicted to avoid any accidents in the future.

The advancement in technologies like IoT, device-to-device communication lead to concepts like smart home and smart cities, etc. In smart home architecture, different devices such as home appliances, personal computers, surveillance cameras, etc. are connected to the Internet and enable the user to monitor and control irrespective of time and location. IPv6-enabled 6LoWPAN is a low-power, low-range communication protocol designed and developed for the short-range IoT applications. 6LoWPAN is based on IEEE 802.15.4 protocol and IPv6 network protocol for low range wireless applications. Although 6LoWPAN supports different routing protocols, RPL is the widely used routing protocol for low power and lossy networks. In this work, we have taken an IoT enabled smart home environment, in which 6LoWPAN is used as a communication and RPL as a routing protocol. The performance of this proposed network model is analyzed based on the different performance metrics such as latency, PDR, and throughput. The proposed model is simulated using Cooja simulator running over the Contiki OS. Along with the Cooja simulator, the network analyzer tool Wireshark is used to analyze the network behaviors.

In view of the problem that the health status and safety monitoring of the traditional intelligent home are mainly dependent on the manual inspection, this paper introduces the intelligent home-based remote monitoring system by introducing the Internet-based Internet of Things technology into the intelligent home condition monitoring and safety assessment. The system's Android remote operation based on the MVP model to develop applications, the use of neural networks to deal with users daily use of operational data to establish the network data model, combined with S3C2440A microcontrollers in the gateway to the embedded Linux to facilitate different intelligent home drivers development. Finally, the power line communication network is used to connect the intelligent electrical appliances to the gateway. By calculating the success rate of the routing nodes, the success rate of the network nodes of 15 intelligent devices is 98.33%. The system can intelligent home many electrical appliances at the same time monitoring, to solve the system data and network congestion caused by the problem can not he security monitoring.

For the security enhancement of the conventional visible light (VL) communication which allows the easy intrusion by adjacent adversary due to visible signal characteristic, the VL communication technique based on the asymmetric Rivest-Shamir-Adleman (RSA) encryption method is proposed for smart indoor service in this paper, and the optimal key length of the RSA encryption process for secure VL communication technique is investigated, and also the error performance dependent on the various asymmetric encryption key is analyzed for the performance evaluation of the proposed technique. Then we could see that the VL communication technique based on the RSA encryption gives the similar RMSE performance independent of the length of the public or private key and provides the better error performance as the signal to noise ratio (SNR) increases.

Ever-driven by technological innovation, the Internet of Things (IoT) is continuing its exceptional evolution and growth into the common consumer space. In the wake of these developments, this paper proposes a framework for an IoT home security system that is secure, expandable, and accessible. Congruent with the ideals of the IoT, we are proposing a system utilizing an ultra-low-power wireless sensor network which would interface with a central hub via Bluetooth 4, commonly referred to as Bluetooth Low Energy (BLE), to monitor the home. Additionally, the system would interface with an Amazon Echo to accept user voice commands. The aforementioned central hub would also act as a web server and host an internet accessible configuration page from which users could monitor and customize their system. An internet-connected system would carry the capability to notify the users of system alarms via SMS or email. Finally, this proof of concept is intended to demonstrate expandability into other areas of home automation or building monitoring functions in general.

Recently, the home healthcare system has emerged as one of the most useful technology for e-healthcare. Contrary to classical recording methods of patient's medical data, which are, based on paper documents, nowadays all this sensitive data can be managed and forwarded through digital systems. These make possible for both patients and healthcare workers to access medical data or receive remote medical treatment using wireless interfaces whenever and wherever. However, simplifying access to these sensitive and private data can directly put patient's health and life in danger. In this paper, we propose a secure and lightweight biometric-based remote patient authentication scheme using elliptic curve encryption through which two mobile healthcare system communication parties could authenticate each other in public mobile healthcare environments. The security and performance analysis demonstrate that our proposal achieves better security than other concurrent schemes, with lower storage, communication and computation costs.

In this proposed method, the traditional elevators are upgraded in such a way that any alarming situation in the elevator can be detected and then sent to a main center where further action can be taken accordingly. Different emergency situation can be handled by implementing the system. Smart elevator system works by installing different modules inside the elevator such as speed sensors which will detect speed variations occurring above or below a certain threshold of elevator speed. The smart elevator system installed within the elevator sends a message to the emergency response center and sends an automated call as well. The smart system also includes an emotion detection algorithm which will detect emotions of the individual based on their expression in the elevator. The smart system also has a whisper detection system as well to know if someone stuck inside the elevator is alive during any hazardous situation. A broadcast signal is used as a check in the elevator system to evaluate if every part of the system is in stable state. Proposed system can completely replace the current elevator systems and become part of smart homes.