The last decade witnessed a gradual shift from cloudbased computing towards ubiquitous computing, which has put at a greater security risk every element of the computing ecosystem including devices, data, network, and decision making. Indeed, emerging pervasive computing paradigms have introduced an uncharted territory of security vulnerabilities and a wider attack surface, mainly due to network openness, the underlying mechanics that enable intelligent functions, and the deeply integrated physical and cyber spaces. Furthermore, interconnected computing environments now enjoy many unconventional characteristics that mandate a radical change in security engineering tools. This need is further exacerbated by the rapid emergence of new Advanced Persistent Threats (APTs) that target critical infrastructures and aim to stealthily undermine their operations in innovative and intelligent ways. To enable system and network designers to be prepared to face this new wave of dangerous threats, this paper overviews recent APTs in emerging computing systems and proposes a new approach to APTs that is more tailored towards such systems compared to traditional IT infrastructures. The proposed APT lifecycle will inform security decisions and implementation choices in future pervasive networked systems.

Traditional Web application category recognition is implemented by fingerprint rule matching, which is difficult to extract fingerprint rules and has limited coverage. At present, many improved identification methods semi-automatically extract fingerprints through certain rules and identify Web application categories through clustering or classification algorithms, but still rely on fingerprint rules and human intervention, and the time complexity of classification is too high to process a large amount of data. This paper proposes Multi-layer Simhash Algorithm and combines DBSCAN clustering to realize intelligent identification of Web application types, pioneering the complete automation of fingerprint identification of Web applications. This method has the function of discovering unknown Web applications and predicting unknown application types, and solves the problems of fingerprint rule extraction and manual dependence of Web applications. This paper through the TF-IDF algorithm to extract the Web page text key words and weight, Then, Multi-layer Simhash Algorithm is used to transform text feature words and weights into binary characteristic hash value, at last, the hamming distance between the input Web page and the characteristic hash value of the known category is compared with the radius of the base class, which determines the category of the input Web application. The experimental results show that the accuracy of Web application category recognition and prediction is more than 97\% and 93\% respectively.

Providing security to the IoT system is very essential to protect them from various attacks. Such security features include credential management to avoid hard-coding of credentials in web applications, key management for secure inter-device communication and assignment of trust score to the devices based on various parameters. This work contains the design and implementation details of an open source simulation environment with credential management, key management and trust score calculation features. In credential management, credentials are sent to the target device which is then stored in a JSON file. Web application in the device makes use of these credentials for authentication. In key management, X.509 certificate and private key file are generated. They are used for secure message communication using a session key that is secretly exchanged between the devices. For trust score calculation, parameters are collected from the device. Feedback parameters given by other devices are also sent to the centralised server. The dynamic weighted average model is applied to the trust values derived from these parameters to get the trust score of the device. In addition to the design, the source code of our simulation environment is also made publicly available so that researchers can alter and extend its capabilities.

Web technologies have created a worldwide web of problems and cyber risks for individuals and organizations. In this paper, we evaluate web technologies and present the different technologies and their positive impacts on individuals and business sectors. Also, we present a cyber-criminals metrics engine for attack determination on web technologies platforms’ weaknesses. Finally, this paper offers a cautionary note to protect Small and Medium Businesses (SMBs) and make recommendations to help minimize cyber risks and save individuals and organizations from cyberattack distress.

With the advancement in computing power and speed, the Internet is being transformed from screen-based information to immersive and extremely low latency communication environments in web 3.0 and the Metaverse. With the emergence of the Metaverse technology, more stringent demands are required in terms of connectivity such as secure access and data privacy. Future technologies such as 6G, Blockchain, and Artificial Intelligence (AI) can mitigate some of these challenges. The Metaverse is now on the verge where security and privacy concerns are crucial for the successful adaptation of such disruptive technology. The Metaverse and web 3.0 are to be decentralized, anonymous, and interoperable. Metaverse is the virtual world of Digital Twins and nonfungible tokens (NFTs).The control and possession of users’ data on centralized servers are the cause of numerous security and privacy concerns.This paper proposes a solution for the security and interoperability challenges using Self-Sovereign Identity (SSI) integrated with blockchain. The philosophy of Self-Sovereign Identity, where the users are the only holders and owners of their identity, comes in handy to solve the questions of decentralization, trust, and interoperability in the Metaverse. This work also discusses the vision of a single, open standard, trustworthy, and interoperable Metaverse with initial design and implementation of SSI concepts.

The internet has made everything convenient. Through the world wide web it has almost single-handily transformed the way we live our lives. In doing so, we have become so fuelled by cravings for fast and cheap web connections that we find it difficult to take in the bigger picture. It is widely documented that we need a safer and more trusting internet, but few know or agree on what this actually means. This paper introduces a new body of research that explores whether there needs to be a fundamental shift in how we design and deliver these online spaces. In detail, the authors suggest the need for an internet security aesthetic that opens up the internet (from end to end) to fully support the people that are using it. Going forward, this research highlights that social trust needs to be a key concern in defining the future value of the internet.

Current and future networks must tackle identity management to authenticate and authorise users to access services. Identity management solutions are widely employed nowadays, where one authenticates in third-party services using account information stored securely in identity providers. Solutions like OpenID Connect relying on OAuth 2.0 are employed to support Single-Sign-On, facilitating users’ login process, which does not need to manage multiple accounts in several services. Despite their wide usage in several domains (enterprise, web applications), they only consider entities like persons. Thus, trust information regarding the levels of trust a person can perceive when accessing services with its devices in specific environments (e.g. untrusted networks like public hotspots) can be employed to protect access to data. OIDC-TCI is an approach to convey context information reflecting the trust relations between endusers, the applications/services running in devices, and a specific environment where access to sensitive resources needs to be authorised. The results demonstrate OIDC-TCI as a feasible solution to convey trust with minimal impact, in compliance with OpenID Connect, in a web service - TeaStore.

COVID-19 has taught us the need of practicing social distancing. In the year 2020 because of sudden lockdown across the globe, E-commerce websites and e-shopping were the only escape to fulfill our basic needs and with the advancement of technology putting your websites online has become a necessity. Be it food, groceries, or our favorite outfit, all these things are now available online. It was noticed during the lockdown period that the businesses that had no social presence suffered heavy losses. On the other hand, people who had established their presence on the internet saw a sudden boom in their overall sales. This project discusses how the recent advancement in the field of Machine Learning and Artificial Intelligence has led to an increase in the sales of various businesses. The machine learning model analyses the pattern of customer’s behavior which affects the sales builds a dataset after many observations and finally helps generate an algorithm which is an efficient recommendation system. This project also discusses how cyber security helps us have secured and authenticated transactions which have aided ecommerce business growth by building customer s trust.

We are adopting blockchain-based security features for the usage in web service applications \& platforms. These technology concepts allow us to enhance the level of trustworthiness for any kind of public web service platform. Related platforms are using simple user registration and validation procedures, which provide huge potential for illegal activities. In contrast, more secure live video identity checks are binding massive resources for the individual, staff-intensive validation tasks. Our approach combines traditional web-based service platform features with blockchain-based security enhancements. The concepts are used on two layers, for the user identification procedures as well as the entire process history on the web service platform.

To improve the security and reliability of remote terminals under trusted cloud platform, an identity authentication model based on DAA optimization is proposed. By introducing a trusted third-party CA, the scheme issues a cross domain DAA certificate to the trusted platform that needs cross domain authentication. Then, privacy CA isolation measures are taken to improve the security of the platform, so that the authentication scheme can be used for identity authentication when ordinary users log in to the host equipped with TPM chip. Finally, the trusted computing platform environment is established, and the performance load distribution and total performance load of each entity in the DAA protocol in the unit of machine cycle can be acquired through experimental analysis. The results show that the scheme can take into account the requirements of anonymity, time cost and cross domain authentication in the trusted cloud computing platform, and it is a useful supplement and extension to the existing theories of web service security.

Multifactor Authentication - Cloud computing is a breakthrough advancement that provides ubiquitous services over the internet in an easy way to distribute information offering various advantages to both society and individuals. Recently, cloud technology has eased everyone’s life more favorable. However, privacy-preservation is an important issue to be tackled effectively in cloud environment while retrieving data services. Numerous techniques have been developed so far to verify user identity by exploiting authentication factor, whereas such techniques are inefficient and they are easily susceptible to unknown users and attacks. In order to address such problems, a multifactor authentication scheme is proposed using Hashing, Chebyshev polynomial, Key and OneTime Token (HCK-OTT) based multifactor authentication scheme for privacy-preserved data security in cloud. The entities involved in this proposed approach for effective authentication are user, cloud server, and data owner. The model is developed by considering various functionalities, such as encryption, Elliptic Curve Cryptography (ECC), XOR, and hashing function. The proposed HCK-OTT-based multifactor authentication scheme has achieved a minimum value of 22.654s for computational time, 70.5MB for memory usage, and 21.543s for communication cost with 64 bit key length.

Information Centric Networks - The 6G wireless communication networks are being studied to build a powerful networking system with global coverage, enhanced spectral/energy/cost efficiency, better intelligent level and security. This paper presents a four-in-one networking paradigm named 3CL-Net that would broaden and strengthen the capabilities of current networking by introducing ubiquitous computing, caching, and intelligence over the communication connection to build 6G-required capabilities. To evaluate the practicability of 3CL-Net, this paper designs a platform based on the 3CL-Net architecture. The platform adopts leader-followers structure that could support all functions of 3CL-Net, but separate missions of 3CL-Net into two parts. Moreover, this paper has implemented part of functions as a prototype, on which some experiments are carried out. The results demonstrate that 3CL-Net is potential to be a practical and effective network paradigm to meet future requirements, meanwhile, 3CL-Net could motivate designs of related platforms as well.

Vehicle Ad-Hoc Networks (VANETs) are a special type of Mobile Ad-Hoc Network (MANETs). In VANETs, a group of vehicles communicates with each other to transfer data without a need for a fixed infrastructure. In this paper, we compare the performance of two routing protocols: Ad-hoc on Demand Distance Vector protocol (AODV) and Destination-Sequenced Distance Vector protocol (DSDV) in VANETs. We measure the reliability of each protocol in the packet delivery.

The era of technology has seen many rising inventions and with that rise, comes the need to secure our systems. In this paper we have discussed how the old generation of people are falling behind at being updated in tandem with technology, and losing track of the knowledge required to process the same. In addition this factor leads to leakage of critical personal information. This paper throws light upon the steps taken in order to exploit the pre-existing operating system, Windows 7, Ultimate, using a ubiquitous framework used by everyone, i.e. Metasploit. It involves installation of a backdoor on the victim machine, from a remote setup, mostly Kali Linux operating machine. This backdoor allows the attackers to create executable files and deploy them in the windows system to gain access on the machine, remotely. After gaining access, manipulation of sensitive data becomes easy. Access to the admin rights of any system is a red alert because it means that some outsider has intense access to personal information of a human being and since data about someone explains a lot of things about them. It basically is exposing and human hate that. It depraves one of their personal identity. Therefore security is not something that should be taken lightly. It is supposed to be dealt with utmost care.

Firewalls are security devices that perform network traffic filtering. They are ubiquitous in the industry and are a common method used to enforce organizational security policy. Security policy is specified on a high level of abstraction, with statements such as "web browsing is allowed only on workstations inside the office network", and needs to be translated into low-level firewall rules to be enforceable. There has been a lot of work regarding optimization, analysis and platform independence of firewall rules, but an area that has seen much less success is automatic translation of high-level security policies into firewall rules. In addition to improving rules’ readability, such translation would make it easier to detect errors.This paper surveys of over twenty papers that aim to generate firewall rules according to a security policy specified on a higher level of abstraction. It also presents an overview of similar features in modern firewall systems. Most approaches define specialized domain languages that get compiled into firewall rule sets, with some of them relying on formal specification, ontology, or graphical models. The approaches’ have improved over time, but there are still many drawbacks that need to be solved before wider application.

Ubiquitous environment embedded with artificial intelligent consist of heterogenous smart devices communicating each other in several context for the computation of requirements. In such environment the trust among the smart users have taken as the challenge to provide the secure environment during the communication in the ubiquitous region. To provide the secure trusted environment for the users of ubiquitous system proposed approach aims to extract behavior of smart invisible entities by retrieving their behavior of communication in the network and applying the recommendation-based filters using Deep learning (RBF-DL). The proposed model adopts deep learning-based classifier to classify the unfair recommendation with fair ones to have a trustworthy ubiquitous system. The capability of proposed model is analyzed and validated by considering different attacks and additional feature of instances in comparison with generic recommendation systems.

Intelligent, smart, Cloud, reconfigurable manufac-turing, and remote monitoring, all intersect in modern industry and mark the path toward more efficient, effective, and sustain-able factories. Many obstacles are found along the path, including legacy machineries and technologies, security issues, and software that is often hard, slow, and expensive to adapt to face unforeseen challenges and needs in this fast-changing ecosystem. Light-weight, portable, loosely coupled, easily monitored, variegated software components, supporting Edge, Fog and Cloud computing, that can be (re)created, (re)configured and operated from remote through Web requests in a matter of milliseconds, and that rely on libraries of ready-to-use tasks also extendable from remote through sub-second Web requests, constitute a fertile technological ground on top of which fourth-generation industries can be built. In this demo it will be shown how starting from a completely virgin Docker Engine, it is possible to build, configure, destroy, rebuild, operate, exclusively from remote, exclusively via API calls, computation networks that are capable to (i) raise alerts based on configured thresholds or trained ML models, (ii) transform Big Data streams, (iii) produce and persist Big Datasets on the Cloud, (iv) train and persist ML models on the Cloud, (v) use trained models for one-shot or stream predictions, (vi) produce tabular visualizations, line plots, pie charts, histograms, at real-time, from Big Data streams. Also, it will be shown how easily such computation networks can be upgraded with new functionalities at real-time, from remote, via API calls.