Biblio

A recently emerged cellular network based One-Tap Authentication (OTAuth) scheme allows app users to quickly sign up or log in to their accounts conveniently: Mobile Network Operator (MNO) provided tokens instead of user passwords are used as identity credentials. After conducting a first in-depth security analysis, however, we have revealed several fundamental design flaws among popular OTAuth services, which allow an adversary to easily (1) perform unauthorized login and register new accounts as the victim, (2) illegally obtain identities of victims, and (3) interfere OTAuth services of legitimate apps. To further evaluate the impact of our identified issues, we propose a pipeline that integrates both static and dynamic analysis. We examined 1,025/894 Android/iOS apps, each app holding more than 100 million installations. We confirmed 396/398 Android/iOS apps are affected. Our research systematically reveals the threats against OTAuth services. Finally, we provide suggestions on how to mitigate these threats accordingly.

When it comes to cryptographic random number generation, poor understanding of the security requirements and “mythical aura” of black-box statistical testing frequently leads it to be used as a substitute for cryptanalysis. To make things worse, a seemingly standard document, NIST SP 800–22, describes 15 statistical tests and suggests that they can be used to evaluate random and pseudorandom number generators in cryptographic applications. The Chi-nese standard GM/T 0005–2012 describes similar tests. These documents have not aged well. The weakest pseudorandom number generators will easily pass these tests, promoting false confidence in insecure systems. We strongly suggest that SP 800–22 be withdrawn by NIST; we consider it to be not just irrelevant but actively harmful. We illustrate this by discussing the “reference generators” contained in the SP 800–22 document itself. None of these generators are suitable for modern cryptography, yet they pass the tests. For future development, we suggest focusing on stochastic modeling of entropy sources instead of model-free statistical tests. Random bit generators should also be reviewed for potential asymmetric backdoors via trapdoor one-way functions, and for security against quantum computing attacks.

Cloud computing is preferred because of its numerous improvements, such as data security, low maintenance cost, unlimited storage capacity and consistent backups. However, legitimate users take advantage of cloud storage services for storing a considerable amount of sensitive data. After storing data on the cloud, data users pass on control over data to cloud administrators. Although for assuring data security, sensitive information needs to be encrypted before deploying it on the cloud server. In traditional searchable encryption, encrypted data can be searched using keywords on a cloud server without knowing data details, and users can retrieve certain specific files of interest after authentication. However, the results are only related to the exact matching keyword searches. This drawback affects system usability and efficiency, due to which existing encryption methods are unsuitable in cloud computing. To avoid the above problems, this study includes as follows: Firstly, we analyze all fuzzy keyword search techniques that are wildcard based, gram based and trie-traverse. Secondly, we briefly describe certificateless cryptography and suggest a certificateless searchable encryption scheme. Finally, this study gives easy access to developing a fuzzy keyword searchable system for a new researcher to combine the above two points. It provides easy access and efficient search results.

Ferroelectric capacitor memory devices with carbon-free Hf0.5Zr0.5O2 (HZO) ferroelectric films are fabricated and characterized. The HZO ferroelectric films are deposited by ALD at temperatures from 225 to 300°C, with HfCl4 and ZrCl4 as the precursors. Residual chlorine from the precursors is measured and studied systematically with various process temperatures. 10nm HZO films with optimal ALD growth temperature at 275°C exhibit remanent polarization of 25µC/cm2 and cycle endurance of 5×1011. Results will be compared with those from HZO films deposited with carbon containing metal-organic precursors.

Classification problems have been part of numerous real-life applications in fields of security, medicine, agriculture, and more. Due to the wide range of applications, there is a constant need for more accurate and efficient methods. Besides more efficient and better classification algorithms, the optimal feature set is a significant factor for better classification accuracy. In general, more features can better describe instances, but besides showing differences between instances of different classes, it can also capture many similarities that lead to wrong classification. Determining the optimal feature set can be considered a hard optimization problem for which different metaheuristics, like swarm intelligence algorithms can be used. In this paper, we propose an adaptation of hybridized swarm intelligence (SI) algorithm for feature selection problem. To test the quality of the proposed method, classification was done by k-means algorithm and it was tested on 17 benchmark datasets from the UCI repository. The results are compared to similar approaches from the literature where SI algorithms were used for feature selection, which proves the quality of the proposed hybridized SI method. The proposed method achieved better classification accuracy for 16 datasets. Higher classification accuracy was achieved while simultaneously reducing the number of used features.

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.

The increasing data generation rate and the proliferation of deep learning applications have led to the development of machine learning-as-a-service (MLaaS) platforms by major Cloud providers. The existing MLaaS platforms, however, fall short in protecting the clients’ private data. Recent distributed MLaaS architectures such as federated learning have also shown to be vulnerable against a range of privacy attacks. Such vulnerabilities motivated the development of privacy-preserving MLaaS techniques, which often use complex cryptographic prim-itives. Such approaches, however, demand abundant computing resources, which undermine the low-latency nature of evolving applications such as autonomous driving.To address these challenges, we propose SCLERA–an efficient MLaaS framework that utilizes trusted execution environment for secure execution of clients’ workloads. SCLERA features a set of optimization techniques to reduce the computational complexity of the offloaded services and achieve low-latency inference. We assessed SCLERA’s efficacy using image/video analytic use cases such as scene detection. Our results show that SCLERA achieves up to 23× speed-up when compared to the baseline secure model execution.

With the development of Industrial Internet identification analysis, various encryption methods have been widely used in identification analysis to ensure the security of identification encoding and data. However, the past encryption methods failed to consider the problem of encryption efficiency in the case of high concurrency, so it will reduce the identification resolution efficiency and increase the computational pressure of secondary nodes when applying these methods to the identification analysis. In this paper, in order to improve the efficiency of identification analysis under the premise of ensuring information security, a safe and efficient analytical encryption method for industrial Internet identification based on Secure Hash Algorithm 256 (SHA-256), and Rivest-Shamir-Adleman (RSA) is presented. Firstly, by replacing the secret key in the identification encoding encryption with the SHA-256 function, the number of secret keys is reduced, which is beneficial to improve the efficiency of identification analysis. Secondly, by replacing the large prime number of the RSA encryption algorithm with multiple small prime numbers, the generation speed of RSA key pair is improved, which is conducive to reduce the computation of secondary nodes. Finally, by assigning a unique RSA private key to the identification code during the identification registration phase, SHA-256 and RSA are associated, the number of key exchanges is reduced during the encryption process, which is conducive to improve the security of encryption. The experiment verifies that the proposed method can improve security of encryption and efficiency of identification analysis, by comparing the complexity of ciphertext cracking and the identification security analysis time between the traditional encryption method and this method.

In the era of Internet usage growth, storage services are widely used where users' can store their data, while hackers techniques pose massive threats to users' data security. The proposed system introduces multiple layers of security where data confidentiality, integrity and availability are achieved using honey encryption, hashed random passwords as well as detecting intruders and preventing them. The used techniques can ensure security against brute force and denial of service attacks. Our proposed methodology proofs the efficiency for storing and retrieving data using honey words and password hashing with less execution time and more security features achieved compared with other systems. Other systems depend on user password leading to easily predict it, we avoid this approach by making the password given to the user is randomly generated which make it unpredictable and hard to break. Moreover, we created a simple user interface to interact with users to take their inputs and store them along with the given password in true database, if an adversary detected, he will be processed as a normal user but with fake information taken from another database called false database, after that, the admin will be notified about this illegitimate access by providing the IP address. This approach will make the admin have continuous detection and ensure availability and confidentiality. Our execution time is efficient as the encryption process takes 244 ms and decryption 229 ms.

Vehicular Ad-hoc Networks (VANET) are capable of offering inter and intra-vehicle wireless communication among mobility aware computing systems. Nodes are linked by applying concepts of mobile ad hoc networks. VANET uses cases empower vehicles to link to the network to aggregate and process messages in real-time. The proposed paper addresses a security vulnerability known as Sybil attack, in which numerous fake nodes broadcast false data to the neighboring nodes. In VANET, mobile nodes continuously change their network topology and exchange location sensor-generated data in real time. The basis of the presented technique is source testing that permits the scalable identification of Sybil nodes, without necessitating any pre-configuration, which was conceptualized from a comparative analysis of preceding research in the literature.

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.

Static analyzers have become increasingly popular both as developer tools and as subjects of empirical studies. Whereas static analysis tools exist for disparate programming languages, the bulk of the empirical research has focused on the popular Java programming language. In this paper, we investigate to what extent some known results about using static analyzers for Java change when considering C\#-another popular object-oriented language. To this end, we combine two replications of previous Java studies. First, we study which static analysis tools are most widely used among C\# developers, and which warnings are more commonly reported by these tools on open-source C\# projects. Second, we develop and empirically evaluate EagleRepair: a technique to automatically fix code in response to static analysis warnings; this is a replication of our previous work for Java [20]. Our replication indicates, among other things, that 1) static code analysis is fairly popular among C\# developers too; 2) Re-Sharper is the most widely used static analyzer for C\#; 3) several static analysis rules are commonly violated in both Java and C\# projects; 4) automatically generating fixes to static code analysis warnings with good precision is feasible in C\#. The EagleRepair tool developed for this research is available as open source.

In this paper, we tried to summarize the practical experience of information security audits of nuclear power plants' automated process control system (I&C). The article presents a methodology for auditing the information security of instrumentation and control systems for nuclear power plants. The methodology was developed taking into account international and national Russian norms and rules and standards. The audit taxonomy, classification lifecycle are described. The taxonomy of information security audits shows that form, objectives of the I&C information security audit, and procedures can vary widely. A conceptual program is considered and discussed in details. The distinctive feature of the methodology is the mandatory consideration of the impact of information security on nuclear safety.

In recent years, the epidemic of speculative side channels significantly increases the difficulty in enforcing domain isolation boundaries in a virtualized cloud environment. Although mitigations exist, the approach taken by the industry is neither a long-term nor a scalable solution, as we target each vulnerability with specific mitigations that add up to substantial performance penalties. We propose a different approach to secret isolation: guaranteeing that the hypervisor is Secret-Free (SF). A Secret-Free design partitions memory into secrets and non-secrets and reconstructs hypervisor isolation. It enforces that all domains have a minimal and secret-free view of the address space. In contrast to state-of-the-art, a Secret-Free hypervisor does not identify secrets to be hidden, but instead identifies non-secrets that can be shared, and only grants access necessary for the current operation, an allow-list approach. SF designs function with existing hardware and do not exhibit noticeable performance penalties in production workloads versus the unmitigated baseline, and outperform state-of-the-art techniques by allowing speculative execution where secrets are invisible. We implement SF in Xen (a Type-I hypervisor) to demonstrate that the design applies well to a commercial hypervisor. Evaluation shows performance comparable to baseline and up to 37% improvement in certain hypervisor paths compared with Xen default mitigations. Further, we demonstrate Secret-Free is a generic kernel isolation infrastructure for a variety of systems, not limited to Type-I hypervisors. We apply the same model in Hyper-V (Type-I), bhyve (Type-II) and FreeBSD (UNIX kernel) to evaluate its applicability and effectiveness. The successful implementations on these systems prove the generality of SF, and reveal the specific adaptations and optimizations required for each type of kernel.

HTTP flood DDoS (Distributed Denial of Service) attacks send illegitimate HTTP requests to the targeted site or server. These kinds of attacks corrupt the networks with the help of massive attacking nodes thus blocking incoming traffic. Computer network connected devices are the major source to distributed denial of service attacks (or) botnet attacks. The computer manufacturers rapidly increase the network devices as per the requirement increases in the different environmental needs. Generally the manufacturers cannot ship computer network products with high level security. Those network products require additional security to prevent the DDoS attacks. The present technology is filled with 4G that will impact DDoS attacks. The million DDoS attacks had experienced in every year by companies or individuals. DDoS attack in a network would lead to loss of assets, data and other resources. Purchasing the new equipment and repair of the DDoS attacked network is financially becomes high in the value. The prevention mechanisms like CAPTCHA are now outdated to the bots and which are solved easily by the advanced bots. In the proposed work a secured botnet prevention mechanism provides network security by prevent and mitigate the http flooding based DDoS attack and allow genuine incoming traffic to the application or server in a network environment with the help of integrating invisible challenge and Resource Request Rate algorithms to the application. It offers double security layer to handle malicious bots to prevent and mitigate.

We introduce the notion of an application-based covert channel—or ABCC—which provides a formal syntax for describing covert channels that tunnel messages through existing protocols. Our syntax captures many recent systems, including DeltaShaper (PETS 2017) and Protozoa (CCS 2020). We also define what it means for an ABCC to be secure against a passive eavesdropper, and prove that suitable abstractions of existing censorship circumvention systems satisfy our security notion. In doing so, we define a number of important non-cryptographic security assumptions that are often made implicitly in prior work. We believe our formalisms may be useful to censorship circumvention developers for reasoning about the security of their systems and the associated security assumptions required.

In this paper, we studies secure wireless transmission using polar codes which based on self-coupling encryption for relay-wiretap channel. The coding scheme proposed in this paper divide the confidential message into two parts, one part used to generate key through a specific extension method, and then use key to perform coupling encryption processing on another part of the confidential message to obtain the ciphertext. The ciphertext is transmitted in the split-channels which are good for relay node, legitimate receiver and eavesdropper at the same time. Legitimate receiver can restore key with the assistance of relay node, and then uses the joint successive cancellation decoding algorithm to restore confidential message. Even if eavesdropper can correctly decode the ciphertext, he still cannot restore the confidential message due to the lack of key. Simulation results show that compared with the previous work, our coding scheme can increase the average code rate to some extent on the premise of ensuring the reliability and security of transmission.

In the recent years, we have witnessed quite notable cyber-attacks targeting industrial automation control systems. Upgrading their cyber security is a challenge, not only due to long equipment lifetimes and legacy protocols originally designed to run in air-gapped networks. Even where multiple data sources are available and collection established, data interpretation usable across the different data sources remains a challenge. A modern hydro power plant contains the data sources that range from the classical distributed control systems to newer IoT- based data sources, embedded directly within the plant equipment and deeply integrated in the process. Even abundant collected data does not solve the security problems by itself. The interpretation of data semantics is limited as the data is effectively siloed. In this paper, the relevance of semantic integration of diverse data sources is presented in the context of a hydro power plant. The proposed semantic integration would increase the data interoperability, unlocking the data siloes and thus allowing ingestion of complementary data sources. The principal target of the data interoperability is to support the data-enhanced cyber security in an operational hydro power plant context. Furthermore, the opening of the data siloes would enable additional usage of the existing data sources in a structured semantically enriched form.

The Internet of Things (IoT) continuously grows as applications require connectivity and sensor networks are being deployed in multiple application domains. With the increased applicability demand, the need for testing and development frameworks also increases. This paper presents a novel simulation framework for testing IPv6 over Low Power Wireless Personal Networks (6LoWPAN) networks using the Mininet-WiFi simulator. The goal of the simulation framework is to allow easier automation testing of large-scale networks and to also allow easy configuration. This framework is a starting point for many development scenarios targeting traffic management, Quality of Service (QoS) or security network features. A basic smart city simulation is presented which demonstrates the working principles of the framework.

The new paradigm software-defined networking (SDN) supports network innovation and makes the control of network operations more agile. The flow table is the main component of SDN switch which contains a set of flow entries that define how new flows are processed. Low-rate distributed denial-of-service (LR-DDoS) attacks are difficult to detect and mitigate because they behave like legitimate users. There are many detection methods for LR DDoS attacks in the literature, but none of these methods detect single-packet LR DDoS attacks. In fact, LR DDoS attackers exploit vulnerabilities in the mechanism of congestion control in TCP to either periodically retransmit burst attack packets for a short time period or to continuously launch a single attack packet at a constant low rate. In this paper, the proposed scheme detects LR-DDoS by examining all incoming packets and filtering the single packets sent from different source IP addresses to the same destination at a constant low rate. Sending single packets at a constant low rate will increase the number of flows at the switch which can make it easily overflowed. After detecting the single attack packets, the proposed scheme prevents LR-DDoS at its early stage by deleting the flows created by these packets once they reach the threshold. According to the results of the experiment, the scheme achieves 99.47% accuracy in this scenario. In addition, the scheme has simple logic and simple calculation, which reduces the overhead of the SDN controller.

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 future 6G era, spiking neural networks (SNNs) can be powerful processing tools in various areas due to their strong artificial intelligence (AI) processing capabilities, such as biometric recognition, AI robotics, autonomous drive, and healthcare. However, within Cyber Physical System (CPS), SNNs are surprisingly vulnerable to adversarial examples generated by benign samples with human-imperceptible noise, this will lead to serious consequences such as face recognition anomalies, autonomous drive-out of control, and wrong medical diagnosis. Only by fully understanding the principles of adversarial attacks with adversarial samples can we defend against them. Nowadays, most existing adversarial attacks result in a severe accuracy degradation to trained SNNs. Still, the critical issue is that they only generate adversarial samples by randomly adding, deleting, and flipping spike trains, making them easy to identify by filters, even by human eyes. Besides, the attack performance and speed also can be improved further. Hence, Spike Probabilistic Attack (SPA) is presented in this paper and aims to generate adversarial samples with more minor perturbations, greater model accuracy degradation, and faster iteration. SPA uses Poisson coding to generate spikes as probabilities, directly converting input data into spikes for faster speed and generating uniformly distributed perturbation for better attack performance. Moreover, an objective function is constructed for minor perturbations and keeping attack success rate, which speeds up the convergence by adjusting parameters. Both white-box and black-box settings are conducted to evaluate the merits of SPA. Experimental results show the model's accuracy under white-box attack decreases by 9.2S% 31.1S% better than others, and average success rates are 74.87% under the black-box setting. The experimental results indicate that SPA has better attack performance than other existing attacks in the white-box and better transferability performance in the black-box setting,

Physical-layer key (PLK) generation scheme is a new key generation scheme based on wireless channel reciprocity. However, the security of physical layer keys still lacks sufficient theoretical support in the presence of eavesdropping attacks until now, which affects the promotion in practical applications. By analyzing the propagation mode of multipath signals under non-line-of-sight (nLoS), an improved spatial cross-correlation model is constructed, where the spatial cross-correlation is between eavesdropping channel and legitimate channel. Results show that compared with the multipath and obstacle distribution of the channel, the azimuth and distance between the eavesdropper and the eavesdropped user have a greater impact on the cross-correlation.

Today, many internet-based applications, especially e-commerce and banking applications, require the transfer of personal data and sensitive data such as credit card information, and in this process, all operations are carried out over the Internet. Users frequently perform these transactions, which require high security, on web sites they access via web browsers. This makes the browser one of the most basic software on the Internet. The security of the communication between the user and the website is provided with SSL certificates, which is used for server authentication. Certificates issued by Certificate Authorities (CA) that have passed international audits must meet certain conditions. The criteria for the issuance of certificates are defined in the Baseline Requirements (BR) document published by the Certificate Authority/Browser (CA/B) Forum, which is accepted as the authority in the WEB Public Key Infrastructure (WEB PKI) ecosystem. Issuing the certificates in accordance with the defined criteria is not sufficient on its own to establish a secure SSL connection. In order to ensure a secure connection and confirm the identity of the website, the certificate validation task falls to the web browsers with which users interact the most. In this study, a comprehensive SSL certificate public key infrastructure (SSL Test Suite) was established to test the behavior of web browsers against certificates that do not comply with BR requirements. With the designed test suite, it is aimed to analyze the certificate validation behaviors of web browsers effectively.

Since the advent of the Software Defined Networking (SDN) in 2011 and formation of Open Networking Foundation (ONF), SDN inspired projects have emerged in various fields of computer networks. Almost all the networking organizations are working on their products to be supported by SDN concept e.g. openflow. SDN has provided a great flexibility and agility in the networks by application specific control functions with centralized controller, but it does not provide security guarantees for security vulnerabilities inside applications, data plane and controller platform. As SDN can also use third party applications, an infected application can be distributed in the network and SDN based systems may be easily collapsed. In this paper, a security threats assessment model has been presented which highlights the critical areas with security requirements in SDN. Based on threat assessment model a proposed Security Threats Assessment and Diagnostic System (STADS) is presented for establishing a reliable SDN framework. The proposed STADS detects and diagnose various threats based on specified policy mechanism when different components of SDN communicate with controller to fulfil network requirements. Mininet network emulator with Ryu controller has been used for implementation and analysis.