Countermeasure Mechanism Research Articles

A Novel Hybrid Reconfigurable Architecture for Prediction of Side Channel Attacks with Its Countermeasure Mechanism

The Internet of Things (IoT) has pushed everyone‘s normal life zone to their comfort zone by making them use embedded IoT devices for controlling and monitoring their daily gadgets. IoT devices find their applications in health care, agriculture, industrial automation, and even vehicles. Since IoT involves numerous devices’ data sharing, which causes network traffic and makes them vulnerable to security breaches, especially Side-Channel Attacks (SCA), it creates demand for an intelligent framework. As of now, many secured cryptoengines are integrated into embedded chips, but still, SCAs play a very vital role in IoT networks. As a result, the paper proposes a novel reconfigurable architecture as Field Programmable Gate Arrays (FPGA) that integrates deep learning models for effective SCA prediction as well as a countermeasure mechanism based on chaotic maps. Finally, the experimentation results prove the excellence of the proposed framework in terms of prediction accuracy (99%), sensitivity (98.9%), and specificity (98.9%) in comparison with LSTM, ELM SVM, RF, NB, and ANN. The results also demonstrated that the proposed framework requires only 50% of the total energy for network operation.

AI-enabled digital forgery analysis and crucial interactions monitoring in smart communities

Digital forgery has become one of the attractive research fields in today’s technology. There are several types of forgery in digital media transmission, especially digital image transmission. A common type of forgery is copy-move forgery (CMF). The CMF may be encountered in streets, railway stations, underground stations, or festivals. This type of forgery may lead to hugger-mugger in some cases. Therefore, there is a need to find a sufficient countermeasure mechanism to detect image forgeries. This paper presents a new CMFD approach that depends on deep learning for IoT based smart cities. Two well-known deep learning models, namely CNN and ConvLSTM, are adopted for CMFD. The proposed models are tested on MICC-220, MICC-600 and MICC 2000 datasets for validation. Several tests are performed to verify the effectiveness of the proposed models. The simulation results reveal that the testing accuracy reaches 95%, 73%, and 94% for MICC-F220, MICC-F600 and MICC-F2000 datasets. In addition, the proposed approach achieves an accuracy of 85% for a combined set of all datasets.

An Intelligent Music Production Technology Based on Generation Confrontation Mechanism.

In recent years, with the development of deep neural network becoming more and more mature, especially after the proposal of generative confrontation mechanism, academia has made many achievements in the research of image, video and text generation. Therefore, scholars began to use similar attempts in the research of music generation. Therefore, based on the existing theoretical technology and research work, this paper studies music production, and then proposes an intelligent music production technology based on generation confrontation mechanism to enrich the research in the field of computer music generation. This paper takes the music generation method based on generation countermeasure mechanism as the research topic, and mainly studies the following: after studying the existing music generation model based on generation countermeasure network, a time structure model for maintaining music coherence is proposed. In music generation, avoid manual input and ensure the interdependence between tracks. At the same time, this paper studies and implements the generation method of discrete music events based on multi track, including multi track correlation model and discrete processing. The lakh MIDI data set is studied. On this basis, the lakh MIDI is pre-processed to obtain the LMD piano roll data set, which is used in the music generation experiment of MCT-GAN. When studying the multi track music generation based on generation countermeasure network, this paper studies and analyzes three models, and puts forward the multi track music generation method based on CT-GAN, which mainly improves the existing music generation model based on GAN. Finally, the generation results of MCT-GAN are compared with those of Muse-GAN, so as to reflect the improvement effect of MCT-GAN. Select 20 auditees to listen to the generated music and real music and distinguish them. Finally, analyze them according to the evaluation results. After evaluation, it is concluded that the research effect of multi track music generation based on CT-GAN is improved.

Construction and Application of Online “Golden Course” Teaching Performance Evaluation Index System from the Perspective of Connectivism

Taking the teaching evaluation of the online “golden course” as the research object, taking Connectivism as the theoretical basis, and from the perspective of the construction and improvement of the index system, the characteristics of the primary and secondary indicators are deeply analyzed. On this basis, we introduce the theoretical analysis of performance evaluation, design the online “golden class” teaching performance evaluation index system, and use the analytic hierarchy process to build an online “golden class” teaching performance evaluation model. The research results will be used to improve the quality of online teaching. The research on the countermeasure mechanism provides theoretical and methodological reference.

A modified genetic algorithm for task assignment of heterogeneous unmanned aerial vehicle system

This study deals with the task assignment problem of heterogeneous unmanned aerial vehicle (UAV) system with the limited resources and task priority constraints. The optimization model which comprehensively considers the resource consumption, task completion effect, and workload balance is formulated. Then, a concept of fuzzy elite degree is proposed to optimize and balance the transmission of good genes and the variation strength of population during the operations of algorithm. Based on the concept, we propose the fuzzy elite strategy genetic algorithm (FESGA) to efficiently solve the complex task assignment problem. In the proposed algorithm, two unlock methods are presented to solve the deadlock problem in the random optimization process; a sudden threat countermeasure (STC) mechanism is presented to help the algorithm quickly respond to the change of task environment caused by sudden threats. The simulation results demonstrate the superiority of the proposed algorithm. Meanwhile, the effectiveness and feasibility of the algorithm in workload balance and task priority constraints are verified.

An Approach of Linear Regression‐Based UAV GPS Spoofing Detection

A prominent security threat to unmanned aerial vehicle (UAV) is to capture it by GPS spoofing, in which the attacker manipulates the GPS signal of the UAV to capture it. This paper introduces an anti‐spoofing model to mitigate the impact of GPS spoofing attack on UAV mission security. In this model, linear regression (LR) is used to predict and model the optimal route of UAV to its destination. On this basis, a countermeasure mechanism is proposed to reduce the impact of GPS spoofing attack. Confrontation is based on the progressive detection mechanism of the model. In order to better ensure the flight security of UAV, the model provides more than one detection scheme for spoofing signal to improve the sensitivity of UAV to deception signal detection. For better proving the proposed LR anti‐spoofing model, a dynamic Stackelberg game is formulated to simulate the interaction between GPS spoofer and UAV. In particular, for GPS spoofer, it is worth mentioning that for the scenario that the UAV is cheated by GPS spoofing signal in the mission environment of the designated route is simulated in the experiment. In particular, UAV with the LR anti‐spoofing model, as the leader in this game, dynamically adjusts its response strategy according to the deception’s attack strategy when upon detection of GPS spoofer’s attack. The simulation results show that the method can effectively enhance the ability of UAV to resist GPS spoofing without increasing the hardware cost of the UAV and is easy to implement. Furthermore, we also try to use long short‐term memory (LSTM) network in the trajectory prediction module of the model. The experimental results show that the LR anti‐spoofing model proposed is far better than that of LSTM in terms of prediction accuracy.

Drones in Distress: A Game-Theoretic Countermeasure for Protecting UAVs Against GPS Spoofing

One prominent security threat that targets unmanned aerial vehicles (UAVs) is the capture via global positioning system (GPS) spoofing in which an attacker manipulates a UAV’s GPS signals in order to capture it. Given the anticipated widespread deployment of UAVs for various purposes, it is imperative to develop new security solutions against such attacks. In this article, a mathematical framework is introduced for analyzing and mitigating the effects of GPS spoofing attacks on UAVs. In particular, system dynamics are used to model the optimal routes that the UAVs will adopt to reach their destinations. The GPS spoofer’s effect on each UAV’s route is also captured by the model. To this end, the spoofer’s optimal imposed locations on the UAVs, are analytically derived; allowing the UAVs to predict their traveling routes under attack. Then, a countermeasure mechanism is developed to mitigate the effect of the GPS spoofing attack. The countermeasure is built on the premise of cooperative localization, in which a UAV can determine its location using nearby UAVs instead of the possibly compromised GPS locations. To better utilize the proposed defense mechanism, a dynamic Stackelberg game is formulated to model the interactions between a GPS spoofer and a drone operator. In particular, the drone operator acts as the leader that determines its optimal strategy in light of the spoofer’s expected response strategy. The equilibrium strategies of the game are then analytically characterized and studied through a novel proposed algorithm. The simulation results show that, when combined with the Stackelberg strategies, the proposed defense mechanism will outperform baseline strategy selection techniques in terms of reducing the possibility of UAV capture.

Spatial production and spatial dialectic: Evidence from the New Urban Districts in China

New Urban Districts (NUDs) are the important spatial carriers to promote urban expansion or transformation. Since the 1990s, they have been playing a more and more crucial role in China’s urbanization. For NUDs in the strict sense we found that: 96% to the east of Hu Line; 56% within the municipal districts; 64% within 36 km from their every city center and below the area of 423 km2. The regional distribution follows significant spatial difference as “Eastern Region (50%) - Central Region (42%) - Western Region (8%)”, and the provinces with the largest number of NUDs are Guangdong, Henan, Zhejiang, Liaoning, and Ji-angsu. Furthermore, their interesting constructed process highlights the typical characteristics of spatial production and spatial dialectic. This paper uses the theory of the production of space, and discovers that the growth of NUDs is a rapid ternary dialectical process of spatial production: “representations of space” is guided by the top-down governmental power; “spatial practice” is reflected in the hierarchical and regional difference of spatial elements, such as the type, pattern, distance and area of NUD; “spaces of representation” embodies the tension between governmental power and urban development rights, as well as the coun-termeasure mechanism. The extensibility of spatiotemporal sequences ensures the unity and continuity of spatial (re)production of NUDs. However, this is also facing a series of challenges like the management coordination of administrative division and the increasing unbalanced or inadequate development. Thus, critically rethinking the evolution of NUD is the key basis for achieving sustainable urban renewal and regional orderly development in the new era.

High-Speed Humanoid Robot Arm for Badminton Using Pneumatic-Electric Hybrid Actuators

We describe the development of a robot configured to play badminton, a dynamic sport that requires high accuracy. We used pneumatic-electric hybrid actuators, each combining a pneumatic actuator, with high-speed and lightweight attributes, and an electric motor with good controllability. Our first objective was to develop hybrid actuators that are lightweight and compact and with integrated sections. Using parts made of lightweight materials such as plastics and aluminum coils, and using wire for power transmission, we made actuators much lighter and smaller than previous ones. In addition, for high accuracy and power, tension sensor units and a heat countermeasure mechanism were also incorporated. As practice partners, we consider badminton robots to be more useful if they were humanoid in appearance and have a variety of shots. We, therefore, developed a humanoid robot arm. By incorporating actuators as link structures, the overall weight was reduced, and both complex degrees of freedom (DoFs) and a large range of motion were realized. Subsequently, we developed a robot with seven DoFs, three DoFs for the shoulder, two for the elbow, and two for the wrist, similar to the configuration of human arms. The robot, therefore, roughly reproduces human movements. At 19 m/s, the maximum speed of the racket was quite fast. The hybrid control reduced the motion variance, allowing improvements in accuracy of more than three times that of motions with only pneumatic control. In addition, performing path planning and tracking control with high precision was possible, tasks that are difficult for conventional pneumatic dynamic robots.

Suing Foreign States Before U.S. Courts: Non-Recognition of State Immunity as a Response to Internationally Wrongful Acts

The lawsuits that the survivors and families of the victims of the 9/11 terrorist attacks filed against Saudi Arabia and other foreign defendants have brought to the fore a controversial issue: whether the international law of state immunity can be infringed to ensure accountability for the most serious assaults on fundamental values of the international community. This paper focuses on this and other cases of denial of foreign state immunity before U.S. courts and purports to investigate whether the assertion of jurisdiction in these instances can be considered a justified response to prior internationally wrongful acts. The first part of the paper examines a number of U.S. judgments denying state immunity pursuant to certain exceptions under the Foreign Sovereign Immunities Act: the Anti-Terrorism and Effective Death Penalty Act, the ‘international taking’ exception, the territorial tort exception, implied waiver, and the Justice Against Sponsors of Terrorism Act. This analysis concludes that the assertion of jurisdiction in these cases cannot be considered lawful in the light of the existing rules of state immunity under international law. The paper highlights however that these cases are premised on the existence of prior wrongful acts on part of the state whose immunity is denied. The second part assesses whether these prima facie unlawful assertions of jurisdiction can be justified as countermeasures under the international law of state responsibility. By distinguishing according to the organs that participate in the adoption of these potential countermeasures, three categories are identified: executive, judicial, and mixed countermeasures. Following some considerations on the compatibility of the rules of state immunity with the countermeasure mechanism, the paper shows that neither the law of state immunity nor the law of state responsibility contain any limitation in this respect. Finally, this paper evaluates how domestic courts can comply with the procedural and substantive requirements for the adoption of lawful countermeasures in the form of non-recognition of sate immunity. It concludes with some reflection on the prospective legality of the Justice Against Sponsors of Terrorism Act (JASTA).

NEDAC: A worm countermeasure mechanism

This article presents an Internet worm countermeasure mechanism that uses DNS activities as a behavioural technique to detect worm propagation. The mechanism also uses a data-link containment solution to block traffic from an infected host. The concept has been demonstrated using a developed prototype and tested in a virtualised network environment. An empirical analysis of network worm propagation has been conducted to test the capabilities of the developed countermeasure mechanism. The results show that the developed mechanism is sensitive in containing Internet worms. Keywords : Worm Detection, Malware, cyber defense

Active Countermeasure Mechanism to Waste Dump Based on Spatial Effect

Due to the difficulty of expropriation, dump technology is experiencing the tendency of higher bench, heavier dumping intensity and larger dumping equipment. Therefore, accidents of dump bench instability or general shear failure on foundation soar rapidly. The capacity decreases because of reducing the heap height, and the high cost would be unacceptable if the soft layers of foundation were strengthened or cleared up. The practicality of passive control measures, such as rockfill dams and retaining walls locating at slope toe is analyzed; the validity of catch drains is evaluated, based on the interacting characteristics between the waste dump and the foundation. The design principles, permission of deformation and moderate failure, are submitted with considering consequence to surroundings. Active countermeasure mechanism is established according to spatial effect, reasonably using dumping-site space and adjusting time-space relation during dumping.

Study on Countermeasure Mechanism by Baffle Plate for Self-Sustained Tone Generated in Boiler Tube Banks

The insertion of baffle plates in a duct is one of some countermeasures of the self-sustained tone generated from the duct with two tube banks. However the use of the baffle plate in the tube banks with cavity has unclear points in the baffle plate length and the insertion conditions. Then the aim of this study is to establish the best insertion condition of the baffle plate in the tube banks with the cavity. And the new idea has been verified by experiments that the suppression mechanism of the self-sustained tone is due to the decrease of the particle velocity and the Karman vortex. In the present experiments, the suppression effect of the baffle plate on the self-sustained tone has been examined. As a result, it was clarified that two peaks of fluctuation velocities appeared when the self-sustained tone occurred and one of them, which has a steep peak, was due to the occurrence of the self-sustained tone. It was also clarified that the self-sustained tone was occurred also by the selected resonance.