Biblio

In case of deploying additional network security equipment in a new location, network service providers face difficulties such as precise management of large number of network security equipment and expensive network operation costs. Accordingly, there is a need for a method for security-aware network service provisioning using the existing network security equipment. In order to solve this problem, there is an existing reinforcement learning-based routing decision method fixed for each node. This method performs repeatedly until a routing decision satisfying end-to-end security constraints is achieved. This generates a disadvantage of longer network service provisioning time. In this paper, we propose security constraints reinforcement learning based routing (SCRR) algorithm that generates routing decisions, which satisfies end-to-end security constraints by giving conditional reward values according to the agent state-action pairs when performing reinforcement learning.

Cloud computing is a model of service provisioning in heterogeneous distributed systems that encourages many researchers to explore its benefits and drawbacks in executing workflow applications. Recently, high-quality security protection has been a new challenge in workflow allocation. Different tasks may and may not have varied security demands, security overhead may vary for different virtual machines (VMs) at which the task is assigned. This paper proposes a Security Oriented Deadline-Aware workflow allocation (SODA) strategy in an IaaS cloud environment to minimize the risk probability of the workflow tasks while considering the deadline met in a deterministic environment. SODA picks out the task based on the highest security upward rank and assigns the selected task to the trustworthy VMs. SODA tries to simultaneously satisfy each task’s security demand and deadline at the maximum possible level. The simulation studies show that SODA outperforms the HEFT strategy on account of the risk probability of the cloud system on scientific workflow, namely CyberShake.

Cooperative secure computing based on the relationship between numerical value and numerical interval is not only the basic problems of secure multiparty computing but also the core problems of cooperative secure computing. It is of substantial theoretical and practical significance for information security in relation to scientific computing to continuously investigate and construct solutions to such problems. Based on the Goldwasser-Micali homomorphic encryption scheme, this paper propose the Morton rule, according to the characteristics of the interval, a double-length vector is constructed to participate in the exclusive-or operation, and an efficient cooperative decision-making solution for integer and integer interval security is designed. This solution can solve more basic problems in cooperative security computation after suitable transformations. A theoretical analysis shows that this solution is safe and efficient. Finally, applications that are based on these protocols are presented.

A huge number of cloud users and cloud providers are threatened of security issues by cloud computing adoption. Cloud computing is a hub of virtualization that provides virtualization-based infrastructure over physically connected systems. With the rapid advancement of cloud computing technology, data protection is becoming increasingly necessary. It's important to weigh the advantages and disadvantages of moving to cloud computing when deciding whether to do so. As a result of security and other problems in the cloud, cloud clients need more time to consider transitioning to cloud environments. Cloud computing, like any other technology, faces numerous challenges, especially in terms of cloud security. Many future customers are wary of cloud adoption because of this. Virtualization Technologies facilitates the sharing of recourses among multiple users. Cloud services are protected using various models such as type-I and type-II hypervisors, OS-level, and unikernel virtualization but also offer a variety of security issues. Unfortunately, several attacks have been built in recent years to compromise the hypervisor and take control of all virtual machines running above it. It is extremely difficult to reduce the size of a hypervisor due to the functions it offers. It is not acceptable for a safe device design to include a large hypervisor in the Trusted Computing Base (TCB). Virtualization is used by cloud computing service providers to provide services. However, using these methods entails handing over complete ownership of data to a third party. This paper covers a variety of topics related to virtualization protection, including a summary of various solutions and risk mitigation in VMM (virtual machine monitor). In this paper, we will discuss issues possible with a malicious virtual machine. We will also discuss security precautions that are required to handle malicious behaviors. We notice the issues of investigating malicious behaviors in cloud computing, give the scientific categorization and demonstrate the future headings. We've identified: i) security specifications for virtualization in Cloud computing, which can be used as a starting point for securing Cloud virtual infrastructure, ii) attacks that can be conducted against Cloud virtual infrastructure, and iii) security solutions to protect the virtualization environment from DDOS attacks.

With the advent of cloud storage services many users tend to store their data in the cloud to save storage cost. However, this has lead to many security concerns, and one of the most important ones is ensuring data integrity. Public verification schemes are able to employ a third party auditor to perform data auditing on behalf of the user. But most public verification schemes are vulnerable to procrastinating auditors who may not perform auditing on time. These schemes do not have fair arbitration also, i.e. they lack a way to punish the malicious Cloud Service Provider (CSP) and compensate user whose data has been corrupted. On the other hand, CSP might be storing redundant data that could increase the storage cost for the CSP and computational cost of data auditing for the user. In this paper, we propose a Blockchain-based public auditing and deduplication scheme with a fair arbitration system against procrastinating auditors. The key idea requires auditors to record each verification using smart contract and store the result into a Blockchain as a transaction. Our scheme can detect and punish the procrastinating auditors and compensate users in the case of any data loss. Additionally, our scheme can detect and delete duplicate data that improve storage utilization and reduce the computational cost of data verification. Experimental evaluation demonstrates that our scheme is provably secure and does not incur overhead compared to the existing public auditing techniques while offering an additional feature of verifying the auditor’s performance.

Supervisory control and data acquisition (SCADA) systems play pivotal role in the operation of modern critical infrastructures (CIs). Technological advancements, innovations, economic trends, etc. have continued to improve SCADA systems effectiveness and overall CIs’ throughput. However, the trends have also continued to expose SCADA systems to security menaces. Intrusions and attacks on SCADA systems can cause service disruptions, equipment damage or/and even fatalities. The use of conventional intrusion detection models have shown trends of ineffectiveness due to the complexity and sophistication of modern day SCADA attacks and intrusions. Also, SCADA characteristics and requirement necessitate exceptional security considerations with regards to intrusive events’ mitigations. This paper explores the viability of supervised learning algorithms in detecting intrusions specific to SCADA systems and their communication protocols. Specifically, we examine four supervised learning algorithms: Random Forest, Naïve Bayes, J48 Decision Tree and Sequential Minimal Optimization-Support Vector Machines (SMO-SVM) for evaluating SCADA datasets. Two SCADA datasets were used for evaluating the performances of our approach. To improve the classification performances, feature selection using principal component analysis was used to preprocess the datasets. Using prominent classification metrics, the SVM-SMO presented the best overall results with regards to the two datasets. In summary, results showed that supervised learning algorithms were able to classify intrusions targeted against SCADA systems with satisfactory performances.

Supervisory Control and Data Acquisition (SCADA) systems are used to control and monitor components within the energy grid, playing a significant role in the stability of the system. As a part of critical infrastructures, components in these systems have to fulfill a variety of different requirements regarding their dependability and must also undergo strict audit procedures in order to comply with all relevant standards. This results in a slow adoption of new functionalities. Due to the emerged threat of cyberattacks against critical infrastructures, extensive security measures are needed within these systems to protect them from adversaries and ensure a stable operation. In this work, a solution is proposed to integrate extensive security measures into current systems. By deploying additional security-gateways into the communication path between two nodes, security features can be integrated transparently for the existing components. The developed security-gateway is compliant to all regulatory requirements and features an internal architecture based on the separation-of-concerns principle to increase its security and longevity. The viability of the proposed solution has been verified in different scenarios, consisting of realistic field tests, security penetration tests and various performance evaluations.

Malicious software (malware) poses a significant threat to the security of our networks and users. In the ever-evolving malware landscape, Excel 4.0 Office macros (XL4) have recently become an important attack vector. These macros are often hidden within apparently legitimate documents and under several layers of obfuscation. As such, they are difficult to analyze using static analysis techniques. Moreover, the analysis in a dynamic analysis environment (a sandbox) is challenging because the macros execute correctly only under specific environmental conditions that are not always easy to create. This paper presents SYMBEXCEL, a novel solution that leverages symbolic execution to deobfuscate and analyze Excel 4.0 macros automatically. Our approach proceeds in three stages: (1) The malicious document is parsed and loaded in memory; (2) Our symbolic execution engine executes the XL4 formulas; and (3) Our Engine concretizes any symbolic values encountered during the symbolic exploration, therefore evaluating the execution of each macro under a broad range of (meaningful) environment configurations. SYMBEXCEL significantly outperforms existing deobfuscation tools, allowing us to reliably extract Indicators of Compromise (IoCs) and other critical forensics information. Our experiments demonstrate the effectiveness of our approach, especially in deobfuscating novel malicious documents that make heavy use of environment variables and are often not identified by commercial anti-virus software.

Emails are widely used as a form of communication and sharing files in an organization. However, email is widely used by cybercriminals to spread malware and carrying out cyber-attacks. We implemented an open-source email gateway in conjunction with a security sandbox for securing emails against malicious attachments. The email gateway scans all incoming and outgoing emails and stops emails containing suspicious files. An automated python script would then send the suspected email to the sandboxing element through sandbox API for further analysis, while the script is used also for the prevention of duplicate results. Moreover, the mail server administrator receives notifications from the email gateway about suspicious attachments. If detected attachment is a true positive based on the sandbox analysis result, email is deleted, otherwise, the email is delivered to the recipient. The paper describes in an empirical way the steps followed during the implementation, results, and conclusions of our research.

This paper presents a definition of a secure system and design principles, which help govern security policies within an embedded system. By understanding a secure system, a common system on chip (SoC) architecture is evaluated and their vulnerabilities explored. This effort helped define requirements for a framework for a secure and isolated SoC architecture for users to develop in. Throughout this paper, a SoC architecture framework for isolated domains has been proposed and its robustness verified against different attack scenarios. To support different levels of criticality and complexity in developing user applications, three computing domains were proposed: security and safety critical (SSC) domain, high performance (HP) domain, and sandbox domain. These domains allow for complex applications to be realized with varying levels of security. Isolation between different computing domains is established using consumer off the shelf (COTS) techniques and architectural components provided by the Zynq Ultrascale+ (ZU+) multiprocessor SoC (MPSoC). To the best of our knowledge, this is the first work that implements a secure system design on the ZU+ platform. There have been many other implementations in hardware security to mitigate certain attack scenarios such as side channel attacks, temporal attacks, hardware trojans, etc. However, our work is different than others, as it establishes the framework for isolated computing domains for secure applications and also verifies system security by attacking one domain from the others.

Using multi-UAV systems to accomplish both civil and military missions is becoming a popular trend. With the development of software and hardware technologies, Unmanned aerial vehicles (UAVs) are now able to operate autonomously at edge. However, the remote control of manned systems, e.g., ground control station (GCS), remains essential to mission success, and the system's control and non-payload communication (CNPC) are facing severe cyber threats caused by smart attacks. To avoid hijacking, in this paper, we propose a secure mechanism that reduces such security risks for multi-UAV systems. We introduce friendly jamming from UAVs to block eavesdropping on the remote control channel. The trade-off between security and energy consumption is optimized by three approaches designed for UAV and GCS under algorithms of different complexities. Numerical results show the approach efficiency under different mission conditions and security demands, and demonstrate the features of the proposed mechanism for various scenarios.

ROS 2 is rapidly becoming a standard in the robotics industry. Built upon DDS as its default communication middleware and used in safety-critical scenarios, adding secu-rity to robots and ROS computational graphs is increasingly becoming a concern. The present work introduces SROS2, a series of developer tools and libraries that facilitate adding security to ROS 2 graphs. Focusing on a usability-centric approach in SROS2, we present a methodology for securing graphs systematically while following the DevSecOps model. We also demonstrate the use of our security tools by presenting an application case study that considers securing a graph using the popular Navigation2 and SLAM Toolbox stacks applied in a TurtieBot3 robot. We analyse the current capabilities of SROS2 and discuss the shortcomings, which provides insights for future contributions and extensions. Ultimately, we present SROS2 as usable security tools for ROS 2 and argue that without usability, security in robotics will be greatly impaired.

The Robotic Operating System (ROS) is a popular framework for robotics research and development. It's a system that provides hardware abstraction with low-level device management to handle communications and services. ROS is a distributed system, which allows various nodes in a network to communicate using a method such as message passing. When integrating systems using ROS, it is vital to consider the security and privacy of the data and information shared across ROS nodes, which is considered to be one of the most challenging aspects of ROS systems. The goal of this study is to examine the ROS architecture, primary components, and versions, as well as the types of vulnerabilities that might compromise the system. In order to achieve the CIA's three fundamental security criteria on a ROS-based platform, we categorized these vulnerabilities and looked into various security solutions proposed by researchers. We provide a comparative analysis of the ROS-related security solutions, the security threats and issues they addressed, the targeted architecture of the protection or defense system, the solution's evaluation methodology and the evaluation metric, and the limitations that might be viewed as unresolved issues for the future course of action. Finally, we look into future possibilities and open challenges to assist researchers to develop more secure and efficient ROS systems.

Mobile small cells that are enabled with Network Coding (NC) are seen as a potentially useful technique for Fifth Generation (5G) networks, since they can cover an entire city and can be put up on demand anywhere, any time, and on any device. Despite numerous advantages, significant security issues arise as a result of the fact that the NC-enabled mobile small cells are vulnerable to attacks. Intrusions are a severe security threat that exploits the inherent vulnerabilities of NC. In order to make NC-enabled mobile small cells to realize their full potential, it is essential to implement intrusion detection systems. When compared to homomorphic signature or hashing systems, homomorphic message authentication codes (MACs) provide safe network coding techniques with relatively smaller overheads. A number of research studies have been conducted with the goal of developing mobile small cells that are enabled with secure network coding and coming up with integrity protocols that are appropriate for such crowded situations. However, the intermediate nodes alter packets while they are in transit and hence the integrity of the data cannot be confirmed by using MACs and checksums. This research study has analyzed numerous intrusion detection models for NC enabled small cells. This research helps the scholars to get a brief idea about various intrusion detection models.

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.

Proving secure compilation of partial programs typically requires back-translating an attack against the compiled program to an attack against the source program. To prove back-translation, one can syntactically translate the target attacker to a source one-i.e., syntax-directed back-translation-or show that the interaction traces of the target attacker can also be emitted by source attackers—i.e., trace-directed back-translation. Syntax-directed back-translation is not suitable when the target attacker may use unstructured control flow that the source language cannot directly represent. Trace-directed back-translation works with such syntactic dissimilarity because only the external interactions of the target attacker have to be mimicked in the source, not its internal control flow. Revealing only external interactions is, however, inconvenient when sharing memory via unforgeable pointers, since information about shared pointers stashed in private memory is not present on the trace. This made prior proofs unnecessarily complex, since the generated attacker had to instead stash all reachable pointers. In this work, we introduce more informative data-flow traces, combining the best of syntax- and trace-directed back-translation in a simpler technique that handles both syntactic dissimilarity and memory sharing well, and that is proved correct in Coq. Additionally, we develop a novel turn-taking simulation relation and use it to prove a recomposition lemma, which is key to reusing compiler correctness in such secure compilation proofs. We are the first to mechanize such a recomposition lemma in the presence of memory sharing. We use these two innovations in a secure compilation proof for a code generation compiler pass between a source language with structured control flow and a target language with unstructured control flow, both with safe pointers and components.

One of the key topics in network security research is the autonomous COA (Couse-of-Action) attack search method. Traditional COA attack search methods that passively search for attacks can be difficult, especially as the network gets bigger. To address these issues, new autonomous COA techniques are being developed, and among them, an intelligent spatial algorithm is designed in this paper for efficient operations in scalable networks. On top of the spatial search, a Monte-Carlo (MC)-based temporal approach is additionally considered for taking care of time-varying network behaviors. Therefore, we propose a spatio-temporal attack COA search algorithm for scalable and time-varying networks.

Cloud computing provides customers with enormous compute power and storage capacity, allowing them to deploy their computation and data-intensive applications without having to invest in infrastructure. Many firms use cloud computing as a means of relocating and maintaining resources outside of their enterprise, regardless of the cloud server's location. However, preserving the data in cloud leads to a number of issues related to data loss, accountability, security etc. Such fears become a great barrier to the adoption of the cloud services by users. Cloud computing offers a high scale storage facility for internet users with reference to the cost based on the usage of facilities provided. Privacy protection of a user's data is considered as a challenge as the internal operations offered by the service providers cannot be accessed by the users. Hence, it becomes necessary for monitoring the usage of the client's data in cloud. In this research, we suggest an effective cloud storage solution for accessing patient medical records across hospitals in different countries while maintaining data security and integrity. In the suggested system, multifactor authentication for user login to the cloud, homomorphic encryption for data storage with integrity verification, and integrity verification have all been implemented effectively. To illustrate the efficacy of the proposed strategy, an experimental investigation was conducted.

Public Key Infrastructure (PKI) as a techno-policy ecosystem for establishing electronic trust has survived for several decades and evolved as the de-facto model for centralized trust in electronic transactions. In this paper, we study the PKI ecosystem that are prevailing in the South Asian and Oceanic countries and brief them. We also look at how PKI has coped up with the rapid technological changes and how policies have been realigned or formulated to strengthen the PKI ecosystem in these countries.

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.

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.

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.

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.

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.

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.