Biblio
In the last decade, numerous Industrial IoT systems have been deployed. Attack vectors and security solutions for these are an active area of research. However, to the best of our knowledge, only very limited insight in the applicability and real-world comparability of attacks exists. To overcome this widespread problem, we have developed and realized an approach to collect attack traces at a larger scale. An easily deployable system integrates well into existing networks and enables the investigation of attacks on unmodified commercial devices.
Humans are a key part of software development, including customers, designers, coders, testers and end users. In this keynote talk I explain why incorporating human-centric issues into software engineering for next-generation applications is critical. I use several examples from our recent and current work on handling human-centric issues when engineering various `smart living' cloud- and edge-based software systems. This includes using human-centric, domain-specific visual models for non-technical experts to specify and generate data analysis applications; personality impact on aspects of software activities; incorporating end user emotions into software requirements engineering for smart homes; incorporating human usage patterns into emerging edge computing applications; visualising smart city-related data; reporting diverse software usability defects; and human-centric security and privacy requirements for smart living systems. I assess the usefulness of these approaches, highlight some outstanding research challenges, and briefly discuss our current work on new human-centric approaches to software engineering for smart living applications.
The evolving of context-aware applications are becoming more readily available as a major driver of the growth of future connected smart, autonomous environments. However, with the increasing of security risks in critical shared massive data capabilities and the increasing regulation requirements on privacy, there is a significant need for new paradigms to manage security and privacy compliances. These challenges call for context-aware and fine-grained security policies to be enforced in such dynamic environments in order to achieve efficient real-time authorization between applications and connected devices. We propose in this work a novel solution that aims to provide context-aware security model for Android applications. Specifically, our proposition provides automated context-aware access control model and leverages Attribute-Based Encryption (ABE) to secure data communications. Thorough experiments have been performed and the evaluation results demonstrate that the proposed solution provides an effective lightweight adaptable context-aware encryption model.
The subsystem of IoMT (Internet of Military of Things) called IoBT (Internet of Battle of Things) is the major resource of the military where the various stack holders of the battlefield and different categories of equipment are tightly integrated through the internet. The proposed architecture mentioned in this paper will be helpful to design IoBT effectively for warfare using irresistible technologies like information technology, embedded technology, and network technology. The role of Machine intelligence is essential in IoBT to create smart things and provide accurate solutions without human intervention. Non-Destructive Testing (NDT) is used in Industries to examine and analyze the invisible defects of equipment. Generally, the ultrasonic waves are used to examine and analyze the internal defects of materials. Hence the proposed architecture of IoBT is enhanced by ultrasonic based NDT to study the properties of the things of the battlefield without causing any damage.
Internet of Vehicle (IoV) is an essential part of the Intelligent Transportation system (ITS) which is growing exponentially in the automotive industry domain. The term IoV is used in this paper for Internet of Vehicles. IoV is conceptualized for sharing traffic, safety and several other vehicle-related information between vehicles and end user. In recent years, the number of connected vehicles has increased allover the world. Having information sharing and connectivity as its advantage, IoV also faces the challenging task in the cybersecurity-related matters. The future consists of crowded places in an interconnected world through wearable's, sensors, smart phones etc. We are converging towards IoV technology and interactions with crowded space of connected peoples. However, this convergence demands high-security mechanism from the connected crowd as-well-as other connected vehicles to safeguard of proposed IoV system. In this paper, we coin the term of smart people crowd (SPC) and the smart vehicular crowd (SVC) for the Internet of Vehicles (IoV). These specific crowds of SPC and SVC are the potential cyber attackers of the smart IoV. People connected to the internet in the crowded place are known as a smart crowd. They have interfacing devices with sensors and the environment. A smart crowd would also consist of the random number of smart vehicles. With the future converging in to the smart connected framework for crowds, vehicles and connected vehicles, we present a novel cyber-physical surveillance system (CPSS) framework to tackle the security threats in the crowded environment for the smart automotive industry and provide the cyber security mechanism in the crowded places. We also describe an overview of use cases and their security challenges on the Internet of Vehicles.
As Electric Power is one of the major concerns, so the concept of the automatic lighting and security system saves the electrical energy. By using the automatic lightning, the consumption of electrical power can be minimized to a greater extent and for that sensors and microcontrollers can be designed in such a manner such that lights get ON/OFF based on motion in a room. The various sensors used for sensing the motion in an area are PIR motion sensor, IR Motion Sensor. An IR sensor senses the heat of an object and detects its motion within some range as it emits infrared radiations and this complete process can be controlled by microcontroller. Along with that security system can be applied in this concept by programming the microcontroller in such a way that if there is some movement in an area then lights must get ON/OFF automatically or any alarm must start. This chapter proposes the framework for the smart lightning with security systems in a building so that electrical power can be utilized efficiently and secures the building.
As chips become more and more connected, they are more exposed (both to network and to physical attacks). Therefore one shall ensure they enjoy a sufficient protection level. Security within chips is accordingly becoming a hot topic. Incident detection and reporting is one novel function expected from chips. In this talk, we explain why it is worthwhile to resort to Artificial Intelligence (AI) for security event handling. Drivers are the need to aggregate multiple and heterogeneous security sensors, the need to digest this information quickly to produce exploitable information, and so while maintaining a low false positive detection rate. Key features are adequate learning procedures and fast and secure classification accelerated by hardware. A challenge is to embed such security-oriented AI logic, while not compromising chip power budget and silicon area. This talk accounts for the opportunities permitted by the symbiotic encounter between chip security and AI.
In rural/remote areas, resource constrained smart micro-grid (RCSMG) architectures can offer a cost-effective power management and supply alternative to national power grid connections. RCSMG architectures handle communications over distributed lossy networks to minimize operation costs. However, the unreliable nature of lossy networks makes privacy an important consideration. Existing anonymisation works on data perturbation work mainly by distortion with additive noise. Apply these solutions to RCSMGs is problematic, because deliberate noise additions must be distinguishable both from system and adversarial generated noise. In this paper, we present a brief survey of privacy risks in RCSMGs centered on inference, and propose a method of mitigating these risks. The lesson here is that while RCSMGs give users more control over power management and distribution, good anonymisation is essential to protecting personal information on RCSMGs.
A Cyber Physical Sensor System (CPSS) consists of a computing platform equipped with wireless access points, sensors, and actuators. In a Cyber Physical System, CPSS constantly collects data from a physical object that is under process and performs local real-time control activities based on the process algorithm. The collected data is then transmitted through the network layer to the enterprise command and control center or to the cloud computing services for further processing and analysis. This paper investigates the CPSS' most common cyber security threats and vulnerabilities and provides countermeasures. Furthermore, the paper addresses how the CPSS are attacked, what are the leading consequences of the attacks, and the possible remedies to prevent them. Detailed case studies are presented to help the readers understand the CPSS threats, vulnerabilities, and possible solutions.
The existing radial topology makes the power system less reliable since any part in the system failure will disrupt electrical power delivery in the network. The increasing security concerns, electrical energy theft, and present advancement in Information and Communication Technologies are some factors that led to modernization of power system. In a smart grid, a network of smart sensors offers numerous opportunities that may include monitoring of power, consumer-side energy management, synchronization of dispersed power storage, and integrating sources of renewable energy. Smart sensor networks are low cost and are ease to deploy hence they are favorable contestants for deployment smart power grids at a larger scale. These networks will result in a colossal volume of dissimilar range of data that require an efficient processing and analyzing process in order to realize an efficient smart grid. The existing technology can be used to collect data but dealing with the collected information proficiently as well as mining valuable material out of it remains challenging. The paper investigates communication technologies that maybe deployed in a smart grid. In this paper simulations results for the Additive White Gaussian Noise (AWGN) channel are illustrated. We propose a model and a communication network domain riding on the power system domain. The model was interrogated by simulation in MATLAB.