Biblio

Intel SGX provides a new method to protect software privacy data, but it faces the security risk of side channel attack. In our opinion, SGX side channel attack depend on the implicit mapping between control flow and data flow to infer privacy data indirectly with control flow. For this reason, we propose code reuse to construct dynamic control flow software. In this method, by loading a large number of related gadgets in advance, the software reset the software control data according to the original software semantics at runtime, so that the software control flow can change dynamically heavily. Based on code reuse, we make the software control flow change dynamically, and the mapping between control flow and data flow more complex and difficult to determine, which can increase the difficulty of SGX side channel attack.

Smart grid monitoring, automation and control will completely rely on PMU based sensor data soon. Accordingly, a high throughput, low latency Information and Communication Technology (ICT) infrastructure should be opted in this regard. Due to the low cost, low power profile, dynamic nature, improved accuracy and scalability, wireless sensor networks (WSNs) can be a good choice. Yet, the efficiency of a WSN depends a lot on the network design and the routing technique. In this paper a new design of the ICT network for smart grid using WSN is proposed. In order to understand the interactions between different entities, detect their operational levels, design the routing scheme and identify false data injection by particular ICT entities, a new model of interdependency called the Multi State Implicative Interdependency Model (MSIIM) is proposed in this paper, which is an updated version of the Modified Implicative Interdependency Model (MIIM) [1]. MSIIM considers the data dependency and operational accuracy of entities together with structural and functional dependencies between them. A multi-path secure routing technique is also proposed in this paper which relies on the MSIIM model for its functioning. Simulation results prove that MSIIM based False Data Injection (FDI) detection and mitigation works better and faster than existing methods.

In order to guarantee the normal operation of the power Internet of things devices, the zero-trust idea was used for studying the security protection strategies of devices from four aspects: user authentication, equipment trust, application integrity and flow baselines. Firstly, device trust is constructed based on device portrait; then, verification of device application integrity based on MD5 message digest algorithm to achieve device application trustworthiness. Next, the terminal network traffic baselines are mined from OpenFlow, a southbound protocol in SDN. Finally, according to the dynamic user trust degree attribute access control model, the comprehensive user trust degree was obtained by weighting the direct trust degree. It obtained from user authentication and the trust degree of user access to terminal communication traffic. And according to the comprehensive trust degree, users are assigned the minimum authority to access the terminal to realize the security protection of the terminal. According to the comprehensive trust degree, the minimum permissions for users to access the terminal were assigned to achieve the security protection of the terminal. The research shows that the zero-trust mechanism is applied to the terminal security protection of power Internet of Things, which can improve the reliability of the safe operation of terminal equipment.

In this work, a novel approach to detect and diagnose single and combined faults in the Induction Motor (IM) is proposed. In Condition Monitoring Systems (CMS) based on the Motor Current Signature Analysis (MCSA), the simultaneous occurrence of multiple faults is a major challenge. An innovative technique called Multiple Windowed Harmonic Wavelet Packet Transform (MWHWPT) is used in order to discriminate between the faulty components of the IM, even during compound faults. Thus, each motor component is monitored by a specific Fault Index (FI) which allows the fault diagnosis without the need for a classifier. The tests carried on Rotor and Bearing faults show high fault diagnosis rate even during compound faults and proves the competitive performance of the proposed approach with literature works.

Cloud Computing is a technology which provides flexibility through scalability. Like, Cloud computing, nowadays, Fog computing is considered more revolutionary and dynamic technology. But the main problem with the Fog computing is to take care of its security as in this also person identification is done by single Sign-In system. To come out from the security problem raised in Fog computing, an innovative approach has been suggested here. In the present paper, an approach has been proposed that combines different biometric techniques to verify the authenticity of a person and provides a complete model that will be able to provide a necessary level of verification and security in fog computing. In this model, several biometric techniques have been used and each one of them individually helps extract out more authentic and detailed information after every step. Further, in the presented paper, different techniques and methodologies have been examined to assess the usefulness of proposed technology in reducing the security threats. The paper delivers a capacious technique for biometric authentication for bolstering the fog security.

Multi-stage Proof-of-Work is a recently proposed protocol which extends the Proof-of-Work protocol used in Bitcoin. It splits Proof-of-Work into multiple stages, to achieve a more efficient block generation and a fair reward distribution. In this paper we study some of the Multi-stage Proof-of-Work security vulnerabilities. Precisely, we present two attacks: a Selfish Mining attack and a Selfish Stage-Withholding attack. We show that Multi-stage Proof-of-Work is not secure against a selfish miner owning more than 25% of the network hashing power. Moreover, we show that Selfish Stage-Withholding is a complementary strategy to boost a selfish miner's profitability.

To improve the security and reliability of the system in case of sensor failure, a fault diagnosis algorithm based on neural network is proposed to locate the fault quickly and reconstruct the control system in this paper. Firstly, the typical airborne sensors are introduced and their common failure modes are analyzed. Then, a new method of complex feature extraction using wavelet packet is put forward to extract the fault characteristics of UAV sensors. Finally, the observer method based on BP neural network is adopted to train and acquire data offline, and to detect and process single or multiple sensor faults online. Matlab simulation results show that the algorithm has good diagnostic accuracy and strong generalization ability, which also has certain practicability in engineering.

Perimeter models, which provide access control for protecting resources on networks, make authorization decisions using the source network of access requests as one of critical factors. However, such models are problematic because once a network is intruded, the attacker gains access to all of its resources. To overcome the above problem, a Zero Trust Network (ZTN) is proposed as a new security model in which access control is performed by authenticating users who request access and then authorizing such requests using various information about users and devices called contexts. To correctly make authorization decisions, this model must take a large amount of various contexts into account. However, in some cases, an access control mechanism cannot collect enough context to make decisions, e.g., when an organization that enforces access control joins the identity federation and uses systems operated by other organizations. This is because the contexts collected using the systems are stored in individual systems and no federation exists for sharing contexts. In this study, we propose the concept of a Zero Trust Federation (ZTF), which applies the concept of ZTN under the identity federation, and a method for sharing context among systems of organizations. Since context is sensitive to user privacy, we also propose a mechanism for sharing contexts under user control. We also verify context sharing by implementing a ZTF prototype.

Cloud storage is a low-cost and convenient storage method, but the nature of cloud storage determines the existence of security risks for data uploaded by users. In order to ensure the security of users' data in third-party cloud platforms, a zero trust security platform for data trusteeship is proposed. The platform introduces the concept of zero trust, which meets the needs of users to upload sensitive data to untrusted third-party cloud platforms by implementing multiple functional modules such as sensitivity analysis service, cipher index service, attribute encryption service.

As IoT systems would have an economic impact, they are gaining growing interest. Millions of IoT devices are expected to join the internet of things, which will carny both major benefits and significant security threats to consumers. For IoT systems that secure data and preserve privacy of users, trust management is an essential component. IoT objects carry on the ownership settings of their owners, allowing them to interact with each other. Social relationships are believed to be important in confidence building. In this paper, we explain how to compute trust in social IoT environments using a cloud-based approach.

This paper aims to address the problem of Deepfake Detection using a Two-Stream Capsule Network. First we review methods used to create Deepfake content, as well as methods proposed in the literature to detect such Deepfake content. We then propose a novel architecture to detect Deepfakes, which consists of a two-stream Capsule network running in parallel that takes in both RGB images/frames as well as Error Level Analysis images. Results show that the proposed approach exhibits the detection accuracy of 73.39 % and 57.45 % for the Deepfake Detection Challenge (DFDC) and the Celeb-DF datasets respectively. These results are, however, from a preliminary implementation of the proposed approach. As part of future work, population-based optimization techniques such as Particle Swarm Optimization (PSO) will be used to tune the hyper parameters for better performance.

Deep learning has been used in a wide range of applications like computer vision, natural language processing and image detection. The advancement in deep learning algorithms in image detection and manipulation has led to the creation of deepfakes, deepfakes use deep learning algorithms to create fake images that are at times very hard to distinguish from real images. With the rising concern around personal privacy and security, Many methods to detect deepfake images have emerged, in this paper the use of deep learning for creating as well as detecting deepfakes is explored, this paper also propose the use of deep learning image enhancement method to improve the quality of deepfakes created.

Over the last two decades, software development has moved away from centralized, plan-based management toward agile methodologies such as Scrum. Agile methodologies are founded on a shared set of core principles, including self-organizing software development teams. Such teams are promoted as a way to increase both developer productivity and team morale, which is echoed by academic research. However, recent works on agile neglect to consider strategic behavior among developers, particularly during task assignment-one of the primary functions of a self-organizing team. This paper argues that self-organizing software teams could be readily modeled using game theory, providing insight into how agile developers may act when behaving strategically. We support our argument by presenting a general model for self-assignment of development tasks based on and extending concepts drawn from established game theory research. We further introduce the software engineering community to two metrics drawn from game theory-the price-of-stability and price-of-anarchy-which can be used to gauge the efficiencies of self-organizing teams compared to centralized management. We demonstrate how these metrics can be used in a case study evaluating the hypothesis that smaller teams self-organize more efficiently than larger teams, with conditional support for that hypothesis. Our game-theoretic framework provides new perspective for the software engineering community, opening many avenues for future research.

Context: The technical debt (TD) metaphor helps to conceptualize the pending issues and trade-offs made during software development. Knowing TD causes can support in defining preventive actions and having information about effects aids in the prioritization of TD payment. Goal: To investigate the impact of the experience level on how practitioners perceive the most likely causes that lead to TD and the effects of TD that have the highest impacts on software projects. Method: We approach this topic by surveying 227 practitioners. Results: While experienced software developers focus on human factors as TD causes and external quality attributes as TD effects, low experienced developers seem to concentrate on technical issues as causes and internal quality issues and increased project effort as effects. Missing any of these types of causes could lead a team to miss the identification of important TD, or miss opportunities to preempt TD. On the other hand, missing important effects could hamper effective planning or erode the effectiveness of decisions about prioritizing TD items. Conclusion: Having software development teams composed of practitioners with a homogeneous experience level can erode the team's ability to effectively manage TD.

Historically, attackers have sought to manipulate programs through the corruption of return addresses, function pointers, and other control flow data. However, as protections like ASLR, stack canaries, and no-execute bits have made such attacks more difficult, data-oriented exploits have received increasing attention. Such exploits try to subvert a program by reading or writing non-control data, without introducing any foreign code or violating the program’s legitimate control flow graph. Recently, a data-oriented exploitation technique called memory cartography was introduced, in which an attacker navigates between allocated memory regions using a precompiled map to disclose sensitive program data. The efficacy of memory cartography is dependent on inter-region pointers being located at constant offsets within memory regions; thus, cartographic attacks are difficult to launch against memory regions like heaps and stacks that have nondeterministic layouts. In this paper, we lower the barrier to successful attacks against nondeterministic memory, demonstrating that pointers between regions of memory often possess unique “signatures” that allow attackers to identify them with high accuracy. These signatures are accurate even when the pointers reside in non-deterministic memory areas. In many real-world programs, this allows an attacker that is capable of reading bytes from a single heap to access all of process memory. Our findings underscore the importance of memory isolation via separate address spaces.

With the rise of the cloud computing and services, the network environments tend to be more complex and enormous. Security control becomes more and more hard due to the frequent and various access and requests. There are a few techniques to solve the problem which developed separately in the recent years. Network Micro-Segmentation provides the system the ability to keep different parts separated. Zero Trust Model ensures the network is access to trusted users and business by applying the policy that verify and authenticate everything. With the combination of Segmentation and Zero Trust Model, a system will obtain the ability to control the access to organizations' or industrial valuable assets. To implement the cooperation, the paper designs a strategy named light verification to help the process to be painless for the cost of inspection. The strategy was found to be effective from the perspective of the technical management, security and usability.

Under the background of increasingly severe security situation, the new working mode of power mobile internet business anytime and anywhere has greatly increased the complexity of network interaction. At the same time, various means of breaking through the boundary protection and moving laterally are emerging in an endless stream. The existing boundary-based mobility The security protection architecture is difficult to effectively respond to the current complex and diverse network attacks and threats, and faces actual combat challenges. This article first analyzes the security risks faced by the existing power mobile Internet services, and conducts a collaborative analysis of the key points of zero-trust based security protection from multiple perspectives such as users, terminals, and applications; on this basis, from identity security authentication, continuous trust evaluation, and fine-grained access The dimension of control, fine-grained access control based on identity trust, and the design of a zero-trust-based power mobile interconnection business security protection framework to provide theoretical guidance for power mobile business security protection.

Recently deep learning has demonstrated much success within the fields of image and natural language processing, facial recognition, and computer vision. The success is attributed to large, accessible databases and deep learning's ability to learn highly accurate models. Thus, deep learning is being investigated as a viable end-to-end approach to digital communications design. This work investigates the use of adversarial deep learning to ensure that a radio can communicate covertly, via Direct Sequence Spread Spectrum (DSSS), with another while a third (the adversary) is actively attempting to detect, intercept and exploit their communications. The adversary's ability to detect and exploit the DSSS signals is hindered by: (i) generating a set of spreading codes that are balanced and result in low side lobes as well as (ii) actively adapting the encoding scheme. Lastly, DSSS communications performance is assessed using energy constrained devices to accurately portray IoT and IoBT device limitations.

This paper mainly studies an attack effectiveness evaluation method for AD hoc networks based on rough set theory. Firstly, we use OPNET to build AD hoc network simulation scenario, design and develop attack module, and obtain network performance parameters before and after the attack. Then the rough set theory is used to evaluate the attack effectiveness. The results show that this method can effectively evaluate the performance of AD hoc networks before and after attacks.

This paper investigates an asymptotically stable fault tolerant control (FTC) method for nonlinear continuous-time systems (NCTS) with actuator failures via differential game theory (DGT). Based on DGT, the FTC problem can be regarded as a two-player differential game problem with control player and fault player, which is solved by utilizing adaptive dynamic programming technique. Using a critic-only neural network, the cost function is approximated to obtain the solution of the Hamilton-Jacobi-Isaacs equation (HJIE). Then, the FTC strategy can be obtained based on the saddle point of HJIE, and ensures the satisfactory control performance for NCTS. Furthermore, the closed-loop NCTS can be guaranteed to be asymptotically stable, rather than ultimately uniformly bounded in corresponding existing methods. Finally, a simulation example is provided to verify the safe and reliable fault tolerance performance of the designed control method.

The paper proposes ways to solve the problem of secure remote access to telecommunications’ equipment. The purpose of the study is to develop a set of procedures to ensure secure interaction while working remotely with Cisco equipment using the SSH protocol. This set of measures is a complete list of measures which ensures security of remote connection to a corporate computer network using modern methods of cryptography and network administration technologies. It has been tested on the GNS3 software emulator and Cisco telecommunications equipment and provides a high level of confidentiality and integrity of remote connection to a corporate computer network. In addition, the study detects vulnerabilities in the IOS operating system while running SSH service and suggests methods for their elimination.

Cyber deception plays an important role in both proactive and reactive defense systems. Internet of Battlefield things connecting smart devices of any military tactical network is of great importance. The goal of cyber deception is to provide false information regarding the network state, and topology to protect the IoBT's network devices. In this paper, we propose a novel deceptive approach based on game theory that takes into account the topological aspects of the network and the criticality of each device. To find the optimal deceptive strategy, we formulate a two-player game to study the interactions between the network defender and the adversary. The Nash equilibrium of the game model is characterized. Moreover, we propose a scalable game-solving algorithm to overcome the curse of dimensionality. This approach is based on solving a smaller in-size subgame per node. Our numerical results show that the proposed deception approach effectively reduced the impact and the reward of the attacker

In this paper, internet is among the basic necessities of life. Internet has changed each and everybody's lives. So confidentiality of messages is very important over the internet. Steganography is the science of sending secret messages between the sender and intended receiver. It is such a technique that makes the exchange of covert messages possible. Each time a carrier is to be used for achieving steganography. The carrier plays a major role in establishing covert communication channel. This survey paper introduces steganography and its carriers. This paper concentrates on network protocols to be used as a carrier of steganograms. There are a number of protocols available to do so in the networks. Network steganography describes various methods used for transmitting data over a network without it being detected. Most of the methods proposed for hiding data in a network do not offer an additional protection to the covert data as it is sent as plain text. This paper presents a framework that offers the protection to the covert data by encrypting it and compresses it for gain in efficiency.

As a fundamental departure from the IP design which encodes source and destination addresses in each packet, Named Data Networking (NDN) directly uses application-defined data names for network layer communications. While bringing important data-centric benefits, the semantic richness of NDN names has also raised confidentiality and privacy concerns. In this paper, we first define the problem of name confidentiality, and then investigate the solution space through a comprehensive examination of all the proposed solutions up to date. Our work shows that the proposed solutions are simply different means to hide the actual data names via a layer of translation; they differ in where and how the translation takes place, which lead to different trade-offs in feasibility, efficiency, security, scalability, and different degrees of adherence to NDN's data-centric communications. Our investigation suggests the feasibility of a systematic design that can enable NDN to provide stronger name confidentiality and user privacy as compared to today's TCP/IP Internet.

With the advent of the era of big data, information technology has been rapidly developed and the application of computers has been popularized. However, network technology is a double-edged sword. While providing convenience, it also faces many problems, among which there are many hidden dangers of network information security. Based on this, based on the era background of big data, the network information security analysis, explore the main network security problems, and elaborate computer information network security matters needing attention, to strengthen the network security management, and put forward countermeasures, so as to improve the level of network security.