Biblio

When we setup a computer network, we need to know if an attacker can get into the system. We need to do a series of test that shows the vulnerabilities of the network setup. These series of tests are commonly known Penetration Test. The need for penetration testing was not well known before. This paper highlights how penetration started and how it became as popular as it has today. The internet played a big part into the push to getting the idea of penetration testing started. The styles of penetration testing can vary from physical to network or virtual based testing which either can be a benefit to how a company becomes more secure. This paper presents the steps of penetration testing that a company or organization needs to carry out, to find out their own security flaws.

Modern hardware systems are composed of a variety of third-party Intellectual Property (IP) cores to implement their overall functionality. Since hardware design is a globalized process involving various (untrusted) stakeholders, a secure management of the valuable IP between authors and users is inevitable to protect them from unauthorized access and modification. To this end, the widely adopted IEEE standard 1735-2014 was created to ensure confidentiality and integrity. In this paper, we outline structural weaknesses in IEEE 1735 that cannot be fixed with cryptographic solutions (given the contemporary hardware design process) and thus render the standard inherently insecure. We practically demonstrate the weaknesses by recovering the private keys of IEEE 1735 implementations from major Electronic Design Automation (EDA) tool vendors, namely Intel, Xilinx, Cadence, Siemens, Microsemi, and Lattice, while results on a seventh case study are withheld. As a consequence, we can decrypt, modify, and re-encrypt all allegedly protected IP cores designed for the respective tools, thus leading to an industry-wide break. As part of this analysis, we are the first to publicly disclose three RSA-based white-box schemes that are used in real-world products and present cryptanalytical attacks for all of them, finally resulting in key recovery.

Recent works have empirically shown that neural network interpretability is susceptible to malicious manipulations. However, existing attacks against Interpretable Deep Learning Systems (IDLSes) all focus on the white-box setting, which is obviously unpractical in real-world scenarios. In this paper, we make the first attempt to attack IDLSes in the decision-based black-box setting. We propose a new framework called Dual Black-box Adversarial Attack (DBAA) which can generate adversarial examples that are misclassified as the target class, yet have very similar interpretations to their benign cases. We conduct comprehensive experiments on different combinations of classifiers and interpreters to illustrate the effectiveness of DBAA. Empirical results show that in all the cases, DBAA achieves high attack success rates and Intersection over Union (IoU) scores.

Wrist-worn devices enable access to essential information and they are suitable for a wide range of applications, such as gesture and activity recognition. Wrist-worn devices require appropriate technologies when used in sensitive areas, overcoming vulnerabilities in regard to security and privacy. In this work, we propose an approach to recognize wrist rotation by utilizing Visible Light Communication (VLC) that is enabled by low-cost LEDs in an indoor environment. In this regard, we address the channel model of a VLC communicating wristband (VLCcw) in terms of the following factors. The directionality and the spectral composition of the light and the corresponding spectral sensitivity and the directional characteristics of the utilized photodiode (PD). We verify our VLCcw from the simulation environment by a small-scale experimental setup. Then, we analyze the system when white and RGBW LEDs are used. In addition, we optimized the VLCcw system by adding more receivers for the purpose of reducing the number of LEDs on VLCcw. Our results show that the proposed approach generates a feasible real-world simulation environment.

In the near future, the high data rate challenge would not be possible by using the radio frequency (RF) only. As the user will increase, the network traffic will increase proportionally. Visible light communication (VLC) is a good solution to support huge number of indoor users. VLC has high data rate over RF communication. The way internet users are increasing, we have to think over VLC technology. Not only the data rate is a concern but also its security, cost, and reliability have to be considered for a good communication network. Quantum technology makes a great impact on communication and computing in both areas. Quantum communication technology has the ability to support better channel capacity, higher security, and lower latency. This paper combines the quantum technology over the existing VLC and compares the performance between quantum visible light communication performance (QVLC) over the existing VLC system. Research findings clearly show that the performance of QVLC is better than the existing VLC system.

Over earlier years of huge technical developments, the need for a communication system has risen tremendously. Inrecent times, public realm interaction has been a popular area, hence the research group is emphasizing the necessity of quick and efficient broadband speeds, as well as upgraded security protocols. The main objective of this project work is to combine conventional Li-Fi and VLC techniques for video communication. VLC is helping to deliver fast data speeds, bandwidth efficiency, and a relatively secure channel of communication. Li-Fi is an inexpensive wireless communication (WC) system. Li-Fi can transmit information (text, audio, and video) to any electronic device via the LEDs that are positioned in the space to provide lighting. Li-Fi provides more advantages than Wi-Fi, such as security, high efficiency, speed, throughput, and low latency. The information can be transferred based on the flash property of the LED. Communication is accomplished by turning on and off LED lights at a faster pace than the human visual system can detect.

The expanding streaming culture of large amounts of data, as well as the requirement for faster and more reliable data transport systems, necessitates the development of innovative communication technologies such as Visible Light Communication (VLC). Nonetheless, incorporating VLC into next-generation networks is challenging due to technological restrictions such as air absorption, shadowing, and beam dispersion. One technique for addressing some of the challenges is to use the multiple input multiple output (MIMO) technique, which involves the simultaneous transmission of data from several sources, hence increasing data rate. In this work, the data transmission performance of the MIMO-VLC system is evaluated using a variety of factors such as distance from the source, data bit rate, and modulation method.

Vehicular Ad-hoc Networks (VANETs) is a very fast emerging research area these days due to their contribution in designing Intelligent transportation systems (ITS). ITS is a well-organized group of wireless networks. It is a derived class of Mobile Ad-hoc Networks (MANETs). VANET is an instant-formed ad-hoc network, due to the mobility of vehicles on the road. The goal of using ITS is to enhance road safety, driving comfort, and traffic effectiveness by alerting the drivers at right time about upcoming dangerous situations, traffic jams, road diverted, weather conditions, real-time news, and entertainment. We can consider Vehicular communication as an enabler for future driverless cars. For these all above applications, it is necessary to make a threat-free environment to establish secure, fast, and efficient communication in VANETs. In this paper, we had discussed the overviews, characteristics, securities, applications, and various data dissemination techniques in VANET.

Key management for self-organized wireless ad-hoc networks using peer-to-peer (P2P) keys is the primary goal of this article (SOWANs). Currently, wireless networks have centralized security architectures, making them difficult to secure. In most cases, ad-hoc wireless networks are not connected to trusted authorities or central servers. They are more prone to fragmentation and disintegration as a result of node and link failures. Traditional security solutions that rely on online trusted authorities do not work together to protect networks that are not planned. With open wireless networks, anyone can join or leave at any time with the right equipment, and no third party is required to verify their identity. These networks are best suited for this proposed method. Each node can make, distribute, and revoke its keying material in this paper. A minimal amount of communication and computation is required to accomplish this task. So that they can authenticate one another and create shared keys, nodes in the self-organized version of the system must communicate via a secure side channel between the users' devices.

Security and privacy are one of crucial factor in the area of information technology and iys applications. Ad-hoc network is a type of non-infrastructure wireless network that is more prone to be attacked and abused due to its properties. Deploying the ad-hoc network in vehicular environment needs the additional security consideration to prevent the attacks that can cause the serious harms like accidents, crashes and fatality of living being lives. In this paper we have explored analysis and requirements of the security solution for the ad hoc network under the vehicular environment. Different categories of threats, their risks are evaluated and then various issues related to deploying the security solutions are addressed by mentioning the proper security technologies and tools.

Resilience and antifragility under duress present significant challenges for autonomic and self-adaptive systems operating in contested environments. In such settings, the system has to continually plan ahead, accounting for either an adversary or an environment that may negate its actions or degrade its capabilities. This will involve projecting future states, as well as assessing recovery options, counter-measures, and progress towards system goals. For antifragile systems to be effective, we envision three self-* properties to be of key importance: self-exploration, self-learning and self-training. Systems should be able to efficiently self-explore – using adversarial search – the potential impact of the adversary’s attacks and compute the most resilient responses. The exploration can be assisted by prior knowledge of the adversary’s capabilities and attack strategies, which can be self-learned – using opponent modelling – from previous attacks and interactions. The system can self-train – using reinforcement learning – such that it evolves and improves itself as a result of being attacked. This paper discusses those visions and outlines their realisation in AWaRE, a cyber-resilient and self-adaptive multi-agent system.

Cyber Physical Systems (CPS), which contain devices to aid with physical infrastructure activities, comprise sensors, actuators, control units, and physical objects. CPS sends messages to physical devices to carry out computational operations. CPS mainly deals with the interplay among cyber and physical environments. The real-time network data acquired and collected in physical space is stored there, and the connection becomes sophisticated. CPS incorporates cyber and physical technologies at all phases. Cyber Physical Systems are a crucial component of Internet of Things (IoT) technology. The CPS is a traditional concept that brings together the physical and digital worlds inhabit. Nevertheless, CPS has several difficulties that are likely to jeopardise our lives immediately, while the CPS's numerous levels are all tied to an immediate threat, therefore necessitating a look at CPS security. Due to the inclusion of IoT devices in a wide variety of applications, the security and privacy of users are key considerations. The rising level of cyber threats has left current security and privacy procedures insufficient. As a result, hackers can treat every person on the Internet as a product. Deep Learning (DL) methods are therefore utilised to provide accurate outputs from big complex databases where the outputs generated can be used to forecast and discover vulnerabilities in IoT systems that handles medical data. Cyber-physical systems need anomaly detection to be secure. However, the rising sophistication of CPSs and more complex attacks means that typical anomaly detection approaches are unsuitable for addressing these difficulties since they are simply overwhelmed by the volume of data and the necessity for domain-specific knowledge. The various attacks like DoS, DDoS need to be avoided that impact the network performance. In this paper, an effective Network Cluster Reliability Model with enhanced security and privacy levels for the data in IoT for Anomaly Detection (NSRM-AD) using deep learning model is proposed. The security levels of the proposed model are contrasted with the proposed model and the results represent that the proposed model performance is accurate

In control systems, the operation of the system after an incident occurs is important. This paper proposes to design a whitelist model that can detect anomalies and identify locations of anomalous actuators using finite automata during multiple actuators attack. By applying this model and comparing the whitelist model with the operation data, the monitoring system detects anomalies and identifies anomaly locations of actuator that deviate from normal operation. We propose to construct a whitelist model focusing on the order of the control system operation using binary search trees, which can grasp the state of the system when anomalies occur. We also apply combinatorial compression based on BDD (Binary Decision Diagram) to the model to speed up querying and identification of abnormalities. Based on the model designed in this study, we aim to construct a secured control system that selects and executes an appropriate fallback operation based on the state of the system when anomaly is detected.

The emergence of CPSs leads to modernization of critical infrastructures and improving flexibility and efficiency from one point of view. However, from another point of view, this modernization has subjected them to cyber threats. This paper provides a modeling approach for evaluating the security of CPSs. The main idea behind the presented model is to study the attacker and the system behaviors in the penetration and attack phases with exploiting some defensive countermeasures such as redundant components and attack detection strategies. By using the proposed approach, we can investigate how redundancy factor of sensors, controllers and actuators and intrusion detection systems can improve the system security and delay the system security failure.

This study addresses the coordination issue of multi-agent systems under complicated actuator faults and cyber attacks. Distributed fault-tolerant design is developed with the estimated and output neighboring information in decentralized estimation observer. Criteria of reaching the exponential coordination of multi-agent systems with cyber attacks is obtained with average dwelling time and chattering bound method. Simulations validate the efficiency of the anti-attack fault-tolerant design.

Security is an essential requirement of Industrial Control System (ICS) environments and its underlying communication infrastructure. Especially the lowest communication level within Supervisory Control and Data Acquisition (SCADA) systems - the field level - commonly lacks security measures.Since emerging wireless technologies within field level expose the lowest communication infrastructure towards potential attackers, additional security measures above the prevalent concept of air-gapped communication must be considered.Therefore, this work analyzes security aspects for the wireless communication protocol IO-Link Wireless (IOLW), which is commonly used for sensor and actuator field level communication. A possible architecture for an IOLW safety layer has already been presented recently [1].In this paper, the overall attack surface of IOLW within its typical environment is analyzed and attack preconditions are investigated to assess the effectiveness of different security measures. Additionally, enhanced security measures are evaluated for the communication systems and the results are summarized. Also, interference of security measures and functional safety principles within the communication are investigated, which do not necessarily complement one another but may also have contradictory requirements.This work is intended to discuss and propose enhancements of the IOLW standard with additional security considerations in future implementations.

The development of industrial robots, as a carrier of artificial intelligence, has played an important role in promoting the popularisation of artificial intelligence super automation technology. The paper introduces the system structure, hardware structure, and software system of the mobile robot climber based on computer big data technology, based on this research background. At the same time, the paper focuses on the climber robot's mechanism compound method and obstacle avoidance control algorithm. Smart home computing focuses on “home” and brings together related peripheral industries to promote smart home services such as smart appliances, home entertainment, home health care, and security monitoring in order to create a safe, secure, energy-efficient, sustainable, and comfortable residential living environment. It's been twenty years. There is still no clear definition of “intelligence at home,” according to Philips Inc., a leading consumer electronics manufacturer, which once stated that intelligence should comprise sensing, connectedness, learning, adaption, and ease of interaction. S mart applications and services are still in the early stages of development, and not all of them can yet exhibit these five intelligent traits.

Several excellent devices can communicate without the need for human intervention. It is one of the fastest-growing sectors in the history of computing, with an estimated 50 billion devices sold by the end of 2020. On the one hand, IoT developments play a crucial role in upgrading a few simple, intelligent applications that can increase living quality. On the other hand, the security concerns have been noted to the cross-cutting idea of frameworks and the multidisciplinary components connected with their organization. As a result, encryption, validation, access control, network security, and application security initiatives for gadgets and their inherent flaws cannot be implemented. It should upgrade existing security measures to ensure that the ML environment is sufficiently protected. Machine learning (ML) has advanced tremendously in the last few years. Machine insight has evolved from a research center curiosity to a sensible instrument in a few critical applications.

Artificial intelligence is a subfield of computer science that refers to the intelligence displayed by machines or software. The research has influenced the rapid development of smart devices that have a significant impact on our daily lives. Science, engineering, business, and medicine have all improved their prediction powers in order to make our lives easier in our daily tasks. The quality and efficiency of regions that use artificial intelligence has improved, as shown in this study. It successfully handles data organisation and environment difficulties, allowing for the development of a more solid and rigorous model. The pace of life is quickening in the digital age, and the PC Internet falls well short of meeting people’s needs. Users want to be able to get convenient network information services at any time and from any location

In recent years, the detection of illegal and harmful messages which plays an significant role in Internet service is highly valued by the government and society. Although artificial intelligence technology is increasingly applied to actual operating systems, it is still a big challenge to be applied to systems that require high real-time performance. This paper provides a real-time detection system solution based on artificial intelligence technology. We first introduce the background of real-time detection of illegal and harmful messages. Second, we propose a complete set of intelligent detection system schemes for real-time detection, and conduct technical exploration and innovation in the media classification process including detection model optimization, traffic monitoring and automatic configuration algorithm. Finally, we carry out corresponding performance verification.

In today's society, with the continuous development of artificial intelligence, artificial intelligence technology plays an increasingly important role in social and economic development, and hass become the fastest growing, most widely used and most influential high-tech in the world today one. However, at the same time, information technology has also brought threats to network security to the entire network world, which makes information systems also face huge and severe challenges, which will affect the stability and development of society to a certain extent. Therefore, comprehensive analysis and research on information system security is a very necessary and urgent task. Through the security assessment of the information system, we can discover the key hidden dangers and loopholes that are hidden in the information source or potentially threaten user data and confidential files, so as to effectively prevent these risks from occurring and provide effective solutions; at the same time To a certain extent, prevent virus invasion, malicious program attacks and network hackers' intrusive behaviors. This article adopts the experimental analysis method to explore how to apply the most practical, advanced and efficient artificial intelligence theory to the information system security assessment management, so as to further realize the optimal design of the information system security assessment management system, which will protect our country the information security has very important meaning and practical value. According to the research results, the function of the experimental test system is complete and available, and the security is good, which can meet the requirements of multi-user operation for security evaluation of the information system.

The achievable bandwidth in ladder acoustic filters is strictly limited by the electromechanical coupling coefficient (k;) in conventional ladder-acoustic filters. Furthermore, their out-of-band rejection is inherently weak due to the frequency responses of the shunt or series-connected acoustic resonators. This work proposes a coupling-matrix-based solution for both issues by employing acoustic and electromagnetic resonators within the same filter prototype using prescribed Chebyshev responses. It has been shown that significantly much wider bandwidths, that cannot be achieved with acoustic-only filters, can be obtained. An important strength of the proposed method is that a filter with a particular FBW can be designed with a wide range of acoustic resonators with different k; values. An 14 % third-order asymmetrical-response filter is designed and fabricated using electromagnetic resonators and an acoustic resonator with a k; of 3.5 %.

The main limitation of acoustic particle separation for microfluidic application is its low sorting efficiency. This is due to the weak coupling of surface acoustic waves (SAWs) into the microchannel. In this work, we demonstrate bulk acoustic wave (BAW) particle sorting using capacitive micromachined ultrasonic transducers (CMUTs) for the first time. A collapsed mode CMUT was driven in air to generate acoustic pressure within the silicon substrate in the in-plane direction of the silicon die. This acoustic pressure was coupled into a water droplet, positioned at the side of the CMUT die, and measured with an optical hydrophone. By using a beam steering approach, the ultrasound generated from 32 CMUT elements were added in-phase to generate a maximum peak-to-peak pressure of 0.9 MPa. Using this pressure, 10 µm latex beads were sorted almost instantaneously.

SummaryIn this study, the propagation and resonance properties of shear-horizontal surface acoustic waves (SH SAWs) on a rotated Y-cut 90°X propagating Ca3TaGa3Si2O14 (CTGS) with a Au- or Al-interdigital transducer (IDT) were investigated theoretically and experimentally. It was found that not only a high-density Au-IDT but also a conventional Al-IDT enables the energy trapping of SH SAW in the vicinity of the surface. For both IDTs, the effective electromechanical coupling factor of about 1.2% and the zero temperature coefficient of frequency can be simultaneously obtained by adjusting the cut angle of CTGS and the electrode film thickness.

The Internet of Things (IoT) is a technology that has evolved to make day-to-day life faster and easier. But with the increase in the number of users, the IoT network is prone to various security and privacy issues. And most of these issues/attacks occur during the routing of the data in the IoT network. Therefore, for secure routing among resource-constrained nodes of IoT, the RPL protocol has been standardized by IETF. But the RPL protocol is also vulnerable to attacks based on resources, topology formation and traffic flow between nodes. The attacks like DoS, Blackhole, eavesdropping, flood attacks and so on cannot be efficiently defended using RPL protocol for routing data in IoT networks. So, defense mechanisms are used to protect networks from routing attacks. And are classified into Secure Routing Protocols (SRPs) and Intrusion Detection systems (IDs). This paper gives an overview of the RPL attacks and the defense mechanisms used to detect or mitigate the RPL routing attacks in IoT networks.