In the present work, we intend to present a thorough study developed on a digital library, called HAT corpus, for a purpose of authorship attribution. Thus, a dataset of 300 documents that are written by 100 different authors, was extracted from the web digital library and processed for a task of author style analysis. All the documents are related to the travel topic and written in Arabic. Basically, three important rules in stylometry should be respected: the minimum document size, the same topic for all documents and the same genre too. In this work, we made a particular effort to respect those conditions seriously during the corpus preparation. That is, three lexical features: Fixed-length words, Rare words and Suffixes are used and evaluated by using a centroid based Manhattan distance. The used identification approach shows interesting results with an accuracy of about 0.94.

This research evaluates the accuracy of two methods of authorship prediction: syntactical analysis and n-gram, and explores its potential usage. The proposed algorithm measures n-gram, and counts adjectives, adverbs, verbs, nouns, punctuation, and sentence length from the training data, and normalizes each metric. The proposed algorithm compares the metrics of training samples to testing samples and predicts authorship based on the correlation they share for each metric. The severity of correlation between the testing and training data produces significant weight in the decision-making process. For example, if analysis of one metric approximates 100% positive correlation, the weight in the decision is assigned a maximum value for that metric. Conversely, a 100% negative correlation receives the minimum value. This new method of authorship validation holds promise for future innovation in fraud protection, the study of historical documents, and maintaining integrity within academia.

The range of text analysis methods in the field of natural language processing (NLP) has become more and more extensive thanks to the increasing computational resources of the 21st century. As a result, many deep learning-based solutions have been proposed for the purpose of authorship attribution, as they offer more flexibility and automated feature extraction compared to traditional statistical methods. A number of solutions have appeared for the attribution of English texts, however, the number of methods designed for Hungarian language is extremely small. Hungarian is a morphologically rich language, sentence formation is flexible and the alphabet is different from other languages. Furthermore, a language specific POS tagger, pretrained word embeddings, dependency parser, etc. are required. As a result, methods designed for other languages cannot be directly applied on Hungarian texts. In this paper, we review deep learning-based authorship attribution methods for English texts and offer techniques for the adaptation of these solutions to Hungarian language. As a part of the paper, we collected a new dataset consisting of Hungarian literary works of 15 authors. In addition, we extensively evaluate the implemented methods on the new dataset.

The globalization of the integrated circuit (IC) manufacturing industry has lured the adversary to come up with numerous malicious activities in the IC supply chain. Logic locking has risen to prominence as a proactive defense strategy against such threats. CAS-Lock (proposed in CHES'20), is an advanced logic locking technique that harnesses the concept of single-point function in providing SAT-attack resiliency. It is claimed to be powerful and efficient enough in mitigating existing state-of-the-art attacks against logic locking techniques. Despite the security robustness of CAS-Lock as claimed by the authors, we expose a serious vulnerability and by exploiting the same we devise a novel attack algorithm against CAS-Lock. The proposed attack can not only reveal the correct key but also the exact AND/OR structure of the implemented CAS-Lock design along with all the key gates utilized in both the blocks of CAS-Lock. It simply relies on the externally observable Distinguishing Input Patterns (DIPs) pertaining to a carefully chosen key simulation of the locked design without the requirement of structural analysis of any kind of the locked netlist. Our attack is successful against various AND/OR cascaded-chain configurations of CAS-Lock and reports 100% success rate in recovering the correct key. It has an attack complexity of \$\textbackslashmathcalO(m)\$, where \$m\$ denotes the number of DIPs obtained for an incorrect key simulation.

Sample-then-lock construction is a reusable fuzzy extractor for low-entropy sources. When applied on iris recognition scenarios, many subsets of an iris-code are used to lock the cryptographic key. The security of this construction relies on the entropy of subsets of iris codes. Simhadri et al. reported a security level of 32 bits on iris sources. In this paper, we propose two kinds of attacks to crack existing sample-then-lock schemes. Exploiting the low-entropy subsets, our attacks can break the locked key and the enrollment iris-code respectively in less than 220 brute force attempts. To protect from these proposed attacks, we design an improved sample-then-lock scheme. More precisely, our scheme employs stability and discriminability to select high-entropy subsets to lock the genuine secret, and conceals genuine locker by a large amount of chaff lockers. Our experiment verifies that existing schemes are vulnerable to the proposed attacks with a security level of less than 20 bits, while our scheme can resist these attacks with a security level of more than 100 bits when number of genuine subsets is 106.

The rapid complexity growth of electronic systems nowadays increases their vulnerability to hacking, such as fault injection, including insertion of glitches into the system clock to corrupt internal state through timing errors. As a countermeasure, a frequency locked loop (FLL) based clock glitch detector is proposed in this paper. Regulated from an external supply voltage, this FLL locks at 16-36X of the system clock, creating four phases to measure the system clock by oversampling at 64-144X. The samples are then used to sense the frequency and close the frequency locked loop, as well as to detect glitches through pattern matching. Implemented in a 5nm FINFET process, it can detect the glitches or pulse width variations down to 3.125% of the input 40MHz clock cycle with the supply varying from 0.5 to 1.0V.

Lock design is an important mechanism for scheduling management and security protection in operating systems. However, there is no effective way to identify the differences and connections among lock models, and users need to spend considerable time to understand different lock architectures. In this paper, we propose a classification scheme that abstracts lock design into three types of models: basic spinlock, semaphore amount extension, lock chain structure, and verify the effectiveness of these three types of lock models in the context of current mainstream applications. We also investigate the specific details of applying this classification method, which can be used as a reference for developers to design lock models, thus shorten the software development cycle.

The burglary of a safe in the city of Jombang, East Java, lost valuables belonging to the Cemerlang Multipurpose Trading Cooperative. Therefore, a security system tool was created in the safe that serves as a place to store valuables and important assets. Change the security system using the security system with a private unique method with modulo arithmetic pattern. The security system of the safe is designed in layers which are attached with the RFID tag by registering and then verifying it on the card. Entering the password on the card cannot be read or is not performed, then the system will refuse to open it. arduino mega type 256 components, RFID tag is attached to the RFID reader, only one validated passive tag can open access to the security system, namely number B9 20 E3 0F. Meanwhile, of the ten passwords entered, only three match the modulo arithmetic format and can open the security system, namely password numbers 22540, 51324 and 91032. The circuit system on the transistor in the solenoid driver circuit works after the safety system opens. The servo motor can rotate according to the input of the open 900 servo angle rotation program.

Network Intrusion Detection Systems (IDSs) have been used to increase the level of network security for many years. The main purpose of such systems is to detect and block malicious activity in the network traffic. Researchers have been improving the performance of IDS technology for decades by applying various machine-learning techniques. From the perspective of academia, obtaining a quality dataset (i.e. a sufficient amount of captured network packets that contain both malicious and normal traffic) to support machine learning approaches has always been a challenge. There are many datasets publicly available for research purposes, including NSL-KDD, KDDCUP 99, CICIDS 2017 and UNSWNB15. However, these datasets are becoming obsolete over time and may no longer be adequate or valid to model and validate IDSs against state-of-the-art attack techniques. As attack techniques are continuously evolving, datasets used to develop and test IDSs also need to be kept up to date. Proven performance of an IDS tested on old attack patterns does not necessarily mean it will perform well against new patterns. Moreover, existing datasets may lack certain data fields or attributes necessary to analyse some of the new attack techniques. In this paper, we argue that academia needs up-to-date high-quality datasets. We compare publicly available datasets and suggest a way to provide up-to-date high-quality datasets for researchers and the security industry. The proposed solution is to utilize the network traffic captured from the Locked Shields exercise, one of the world’s largest live-fire international cyber defence exercises held annually by the NATO CCDCOE. During this three-day exercise, red team members consisting of dozens of white hackers selected by the governments of over 20 participating countries attempt to infiltrate the networks of over 20 blue teams, who are tasked to defend a fictional country called Berylia. After the exercise, network packets captured from each blue team’s network are handed over to each team. However, the countries are not willing to disclose the packet capture (PCAP) files to the public since these files contain specific information that could reveal how a particular nation might react to certain types of cyberattacks. To overcome this problem, we propose to create a dedicated virtual team, capture all the traffic from this team’s network, and disclose it to the public so that academia can use it for unclassified research and studies. In this way, the organizers of Locked Shields can effectively contribute to the advancement of future artificial intelligence (AI) enabled security solutions by providing annual datasets of up-to-date attack patterns.

We propose TaintLock, a lightweight dynamic scan data authentication and encryption scheme that performs per-pattern authentication and encryption using taint and signature bits embedded within the test pattern. To prevent IP theft, we pair TaintLock with truly random logic locking (TRLL) to ensure resilience against both Oracle-guided and Oracle-free attacks, including scan deobfuscation attacks. TaintLock uses a substitution-permutation (SP) network to cryptographically authenticate each test pattern using embedded taint and signature bits. It further uses cryptographically generated keys to encrypt scan data for unauthenticated users dynamically. We show that it offers a low overhead, non-intrusive secure scan solution without impacting test coverage or test time while preventing IP theft.

Security is a key concern across the world, and it has been a common thread for all critical sectors. Nowadays, it may be stated that security is a backbone that is absolutely necessary for personal safety. The most important requirements of security systems for individuals are protection against theft and trespassing. CCTV cameras are often employed for security purposes. The biggest disadvantage of CCTV cameras is their high cost and the need for a trustworthy individual to monitor them. As a result, a solution that is both easy and cost-effective, as well as secure has been devised. The smart door lock is built on Raspberry Pi technology, and it works by capturing a picture through the Pi Camera module, detecting a visitor's face, and then allowing them to enter. Local binary pattern approach is used for Face recognition. Remote picture viewing, notification, on mobile device are all possible with an IOT based application. The proposed system may be installed at front doors, lockers, offices, and other locations where security is required. The proposed system has an accuracy of 89%, with an average processing time is 20 seconds for the overall process.

With the advent of technology and owing to mankind’s reliance on technology, it is of utmost importance to safeguard people’s data and their identity. Biometrics have for long played an important role in providing that layer of security ranging from small scale uses such as house locks to enterprises using them for confidentiality purposes. In this paper we will provide an insight into behavioral biometrics that rely on identifying and measuring human characteristics or behavior. We review different types of behavioral parameters such as keystroke dynamics, gait, footstep pressure signals and more.

Energy trading in small groups or microgrids is interesting to study. The energy market may overgrow in the future, so accessing the energy market by small prosumers may not be difficult anymore. This paper has modeled a decentralized P2P energy trading and exchange system in a microgrid group. The Islanded microgrid system is simulated to create a small energy producer and consumer trading situation. The simulation results show the increasing energy transactions and profit when including V2G as an energy storage device. In addition, blockchain is used for system security because a peer-to-peer marketplace has no intermediary control.

Financial technology (Fintech) is an amalgamation of financial management using a technology system. Fintech has become a public concern because this service provides many service features to make it easier from the financial side, such as being used in cooperative financial institutions, banking and insurance. This paper will analyze the opportunities and challenges of Fintech sharia in Indonesia. By exploring the existing literature, this article will try to answer that question. This research is carried out using a literature review approach and comparative qualitative method which will determined the results of the SWOT analysis of sharia financial technology in indonesia. It is needed to mitigate risk of funding in a peer to peer method in overcoming the security of funds and data from investors, firstly companies can perform transparency on the clarity of investor funds. This is done as one of the facilities provided to investors in the Fintech application. In the future, it is hoped that in facing competition, sharia-based fintech companies must be able to provide targeted services through the socialization of sharia fintech to the public, both online and offline. Investors are expected to be more careful before investing in choosing Fintech Peer to Peer (P2P) Lending services by checking the list of Fintech lending and lending companies registered and found by the Financial Services Authority (OJK).

There is momentous attention from researchers and practitioners all over the world towards one of the most advanced trends in the world, Smart cities. A smart city is an efficient and sustainable city that offers a superior life quality to all human beings through the optimum management of all its resources. Optimum energy management technique within the smart city is a challenging environment that needs a full focus on basic important needs and supports of the smart city. This includes Smart Grid (SG) infrastructure, Distributed Generation (DG) technology, Smart Home Energy Management System (HEMS), Smart Transportation System (STS), and Energy Storage System (ESS). Out of these five taxonomies, there have been some disputes addressed in profitability and security due to the major involvement of electromobility in the smart transportation system. It creates a big impact on the smart city environment. The disputes in profitability can be effectively handled with the use of dynamic pricing techniques and peer-to-peer (P2P) energy trading mechanisms. On the other hand, security disputes can be overwhelmed by the use of blockchain technology. This paper reviews the energy management-related work on smart cities with the consideration of these basic important needs and supports.

In many scenarios, Internet connectivity may not be available. In such situations, device-to-device (D2D) communication may be utilized to establish a peer-to-peer (P2P) network among mobile users in the vicinity. However, this raises a fundamental question as is how to ensure secure communication in such an infrastructure-less network. In this paper, we present an approach that enables connectivity between mobile devices in the vicinity and supports secure communication between users in Internet-isolated locations. Specifically, the proposed solution uses Wi-Fi Aware for establishing a P2P network and the mTLS (mutual Transport Layer Security) protocol to provide mutually authenticated and encrypted message transfer. Besides, a novel decentralized peer authentication (DPA) scheme compatible with Wi-Fi Aware and TLS is proposed, which enables peers to verify other peers to join the network. A proof-of-concept instant messaging application has been developed to test the proposed DPA scheme and to evaluate the performance of the proposed overall approach. Experimental results, which validate the proposed solution, are presented with findings and limitations discussed.

Nowadays, the messaging system is one of the most popular mobile applications, and therefore the authentication between clients is essential. Various kinds of such mobile applications are using encryption-based security protocols, but they are facing many security threat issues. It clearly defines the necessity for a trustful security procedure. Therefore, a blockchain-based messaging system could be an alternative to this problem. That is why, we have developed a secured peer-to-peer messaging system supported by blockchain. This proposed mechanism provides data security among the users. In a blockchain-based framework, all the information can be verified and controlled automatically and all the transactions are recorded that have been created already. In our paper, we have explained how the users can communicate through a blockchain-based messaging system that can maintain a secured network. We explored why blockchain would improve communication security in this post, and we proposed a model architecture for blockchain-based messaging that retains the performance and security of data stored on the blockchain. Our proposed architecture is completely decentralized and enables users to send and receive messages in an acceptable and secure manner.

The architecture and functioning of the electricity markets are rapidly evolving in favour of solutions based on real-time data sharing and decentralised, distributed, renewable energy generation. Peer-to-peer (P2P) energy markets allow two individuals to transact with one another without the need of intermediaries, reducing the load on the power grid during peak hours. However, such a P2P energy market is prone to various cyber attacks. Blockchain technology has been proposed to implement P2P energy trading to support this change. One of the most crucial components of blockchain technology in energy trading is the consensus mechanism. It determines the effectiveness and security of the blockchain for energy trading. However, most of the consensus used in energy trading today are traditional consensus such as Proof-of-Work (PoW) and Practical Byzantine Fault Tolerance (PBFT). These traditional mechanisms cannot be directly adopted in P2P energy trading due to their huge computational power, low throughput, and high latency. Therefore, we propose the Block Alliance Consensus (BAC) mechanism based on Hashgraph. In a massive P2P energy trading network, BAC can keep Hashgraph's throughput while resisting Sybil attacks and supporting the addition and deletion of energy participants. The high efficiency and security of BAC and the blockchain-based energy trading platform are verified through experiments: our improved BAC has an average throughput that is 2.56 times more than regular BFT, 5 times greater than PoW, and 30% greater than the original BAC. The improved BAC has an average latency that is 41% less than BAC and 81% less than original BFT. Our energy trading blockchain (ETB)'s READ performance can achieve the most outstanding throughput of 1192 tps at a workload of 1200 tps, while WRITE can achieve 682 tps at a workload of 800 tps with a success rate of 95% and 0.18 seconds of latency.

Nowadays Osmotic Computing is emerging as one of the paradigms used to guarantee the Cloud Continuum, and this popularity is strictly related to the capacity to embrace inside it some hot topics like containers, microservices, orchestration and Function as a Service (FaaS). The Osmotic principle is quite simple, it aims to create a federated heterogeneous infrastructure, where an application's components can smoothly move following a concentration rule. In this work, we aim to solve two big constraints of Osmotic Computing related to the incapacity to manage dynamic access rules for accessing the applications inside the Osmotic Infrastructure and the incapacity to keep alive and secure the access to these applications even in presence of network disconnections. For overcoming these limits we designed and implemented a new Osmotic component, that acts as an eventually consistent distributed peer to peer access management system. This new component is used to keep a local Identity and Access Manager (IAM) that permits at any time to access the resource available in an Osmotic node and to update the access rules that allow or deny access to hosted applications. This component has been already integrated inside a Kubernetes based Osmotic Infrastructure and we presented two typical use cases where it can be exploited.

The distributed energy resources (DERs) have significantly stimulated the development of decentralized energy system and changed the way how the energy system works. In recent years, peer-to-peer (P2P) trading has drawn attention as a promising alternative for prosumers to engage with the energy market more actively, particular by using the emerging blockchain technology. Blockchain can securely hold critical information and store data in blocks linking with chain, providing a desired platform for the P2P energy trading. This paper provides a detailed description of blockchain-enabled P2P energy trading, its essential components, and how it can be implemented within the local energy market An analysis of potential threats during blockchain-enabled P2P energy trading is also performed, which subsequently results in a list of operation and privacy requirements suggested to be implemented in the local energy market.

The marine and maritime domain is well represented in the Sustainable Development Goals (SDG) envisaged by the United Nations, which aim at conserving and using the oceans, seas and their resources for sustainable development. At the same time, there is a need for improved safety in navigation, especially in coastal areas. Up to date, there exist operational services based on advanced technologies, including remote sensing and in situ monitoring networks which provide aid to the navigation and control over the environment for its preservation. Yet, the possibilities offered by crowdsensing have not yet been fully explored. This paper addresses this issue by presenting an app based on a crowdsensing approach for improved safety and awareness at sea. The app can be integrated into more comprehensive systems and frameworks for environmental monitoring as envisaged in our future work.

With billions of devices already connected to the network's edge, the Internet of Things (IoT) is shaping the future of pervasive computing. Nonetheless, IoT applications still cannot escape the need for the computing resources available at the fog layer. This becomes challenging since the fog nodes are not necessarily secure nor reliable, which widens even further the IoT threat surface. Moreover, the security risk appetite of heterogeneous IoT applications in different domains or deploy-ment contexts should not be assessed similarly. To respond to this challenge, this paper proposes a new approach to optimize the allocation of secure and reliable fog computing resources among IoT applications with varying security risk level. First, the security and reliability levels of fog nodes are quantitatively evaluated, and a security risk assessment methodology is defined for IoT services. Then, an online, incentive-compatible mechanism is designed to allocate secure fog resources to high-risk IoT offloading requests. Compared to the offline Vickrey auction, the proposed mechanism is computationally efficient and yields an acceptable approximation of the social welfare of IoT devices, allowing to attenuate security risk within the edge network.

With their variety of application verticals, smart cities represent a killer scenario for Cloud-IoT computing, e.g. fog computing. Such applications require a management capable of satisfying all their requirements through suitable service placements, and of balancing among QoS-assurance, operational costs, deployment security and, last but not least, energy consumption and carbon emissions. This keynote discusses these aspects over a motivating use case and points to some open challenges.

With the development of 5G networking technology on the Internet of Vehicle (IoV), there are new opportunities for numerous cyber-attacks, such as in-vehicle attacks like hijacking occurrences and data theft. While numerous attempts have been made to protect against the potential attacks, there are still many unsolved problems such as developing a fine-grained access control system. This is reflected by the granularity of security as well as the related data that are hosted on these platforms. Among the most notable trends is the increased usage of smart devices, IoV, cloud services, emerging technologies aim at accessing, storing and processing data. Most popular authentication protocols rely on knowledge-factor for authentication that is infamously known to be vulnerable to subversions. Recently, the zero-trust framework has drawn huge attention; there is an urgent need to develop further the existing Continuous Authentication (CA) technique to achieve the zero-trustiness framework. In this paper, firstly, we develop the static authentication process and propose a secured protocol to generate the smart key for user to unlock the vehicle. Then, we proposed a novel and secure continuous authentication system for IoVs. We present the proof-of-concept of our CA scheme by building a prototype that leverages the commodity fingerprint sensors, NFC, and smartphone. Our evaluations in real-world settings demonstrate the appropriateness of CA scheme and security analysis of our proposed protocol for digital key suggests its enhanced security against the known attack-vector.

Connected devices are being deployed at a steady rate, providing services like data collection. Pervasive applications rely on those edge devices to seamlessly provide services to users. To connect applications and edge devices, using a middleware has been a popular approach. The research is active on the subject as there are many open challenges. The secure management of the edge devices and the security of the middleware are two of them. As security is a crucial requirement for pervasive environment, we propose a middleware architecture easing the secure use of edge devices for pervasive applications, while supporting the heterogeneity of communication protocols and the dynamism of devices. Because of the heterogeneity in protocols and security features, not all edge devices are equally secure. To allow the pervasive applications to gain control over this heterogeneous security, we propose a model to describe edge devices security. This model is accessible by the applications through our middleware. To validate our work, we developed a demonstrator of our middleware and we tested it in a concrete scenario.