Reduce Security Risks Research Articles

Security Attitude Prediction Model of Secret-Related Computer Information System Based on Distributed Parallel Computing Programming

In recent years, there has been an upward trend in the number of leaked secrets. Among them, secret-related computers or networks are connected to the Internet in violation of regulations, cross-use of mobile storage media, and poor security management of secret-related intranets, which are the main reasons for leaks. Therefore, it is of great significance to study the physical isolation and protection technology of classified information systems. Physical isolation is an important part of the protection of classified information systems, which cuts off the possibility of unauthorized outflow of information from the network environment. To achieve the physical isolation of the network environment and build a safe and reliable network, it is necessary to continuously improve the level of network construction and strengthen network management capabilities. At present, the realization of physical isolation technology mainly relies on security products such as firewall, intrusion detection, illegal outreach, host monitoring, and auditing. This study analyzes network security systems such as intrusion detection, network scanning, and firewall. Establishing a model based on network security vulnerabilities and making up for network security hidden dangers caused by holes are generally a passive security system. In a network, the leader of network behavior—human behavior—needs to be constrained according to the requirements of the security management system and monitoring. Accordingly, this study proposes a security monitoring system for computer information network involving classified computer. The system can analyze, monitor, manage, and process the network behavior of the terminal computer host in the local area network, to achieve the purpose of reducing security risks in the network system. Based on the evaluation value sequence, the initial prediction value sequence is obtained by sliding adaptive triple exponential smoothing method. The time-varying weighted Markov chain is used for error prediction, the initial prediction value is corrected, and the accuracy of security situation prediction is improved. According to the security protection requirements of secret-related information systems, a complete, safe, reliable, and controllable security protection system for secret-related information systems is constructed, and the existing security risks and loopholes in secret-related information systems are eliminated to the greatest extent possible. This enables the confidentiality, integrity, and availability of confidential data and information in the computer information system to be reliably protected.

Building the hospital intelligent twins for all-scenario intelligence health care.

The COVID-19 pandemic has accelerated a long-term trend of smart hospital development. However, there is no consistent conceptualization of what a smart hospital entails. Few hospitals have genuinely reached being “smart,” primarily failing to bring systems together and consider implications from all perspectives. Hospital Intelligent Twins, a new technology integration powered by IoT, AI, cloud computing, and 5G application to create all-scenario intelligence for health care and hospital management. This communication presented a smart hospital for all-scenario intelligence by creating the hospital Intelligent Twins. Intelligent Twins is widely involved in medical activities. However, solving the medical ethics, protecting patient privacy, and reducing security risks involved are significant challenges for all-scenario intelligence applications. This exploration of creating hospital Intelligent Twins that can be a worthwhile endeavor to assess how to inform evidence-based decision-making better and enhance patient satisfaction and outcomes.

A Novel Glowworm Swarm Optimization Driven Gated Recurrent Unit Enabled Botnet Detection in IIoT Environment

Accurate and prompt detection of security attacks in the Industrial Internet of Things (IIoT) is important to reduce security risks. Since a massive number of IoT devices are placed over the globe and the quantity gets increased, an effective security solution is necessary. A botnet is a computer network comprising numerous hosts executing on standalone software. In this view, this article develops a novel Glowworm Swarm Optimization Driven Gated Recurrent Unit Enabled Botnet Detection (GSOGRU-BD) model in IIoT Environment. The presented GSOGRU-BD model intends to effectually identify the presence of botnet attacks in the IIoT environment. To do so, the GSOGRU-BD model initially pre-processed the input data to get rid of missing values. In addition, the GSOGRU-BD model involves the GRU model for the effective recognition and classification of botnets. Besides, the GSO algorithm is used for optimal hyperparameter tuning of the GRU model. Comparative experimental validation of the GSOGRU-BD model is tested using a benchmark dataset and the results reported the better outcomes for the GSOGRU-BD model.

Security Risk and Influencing Factors of Agro-Products in Farmland Soil Around a Typical Mining Smelter

The security risks of heavy metal pollution in agro-products are becoming increasingly serious. This paper investigated the heavy metal contamination of farmland soils and agro-products around a typical mining smelter in Hunan province, and explored the influencing factors based on principal component and correlation analyses. The results showed that the soils were significantly contaminated by heavy metals, with a mean concentrations of Cd, Cu, Pb, and Zn of 9.12, 358, 303, and 185 mg·kg-1, respectively, pH range from 4.67 to 7.22. All the sites included were under strict control. With regards to the agro-products, the concentration of heavy metal elements were different, and the order of heavy metal concentrations was Zn>Cu>Pb>Cd, with an order of biological enrichment factor(BCF) of Cd>Zn>Cu>Pb. Over-the-standard elements in agro-products included Pb and Cd at 78% and 41%, respectively, which indicated a higher security risk from these products. The accumulation of the same heavy metals in leaf vegetables were generally higher than sweet potatoes and solanaceous vegetables. The heavy metal concentrations in soils corresponded to the first principal component(P<0.01), with the variance reaching 88.0%, which dominated the sources of Cd, Cu, Pb, and Zn in agro-products. The enrichment characteristics were mainly affected by the type of crops, and was also regulated by the soil pH, cation exchange capacity, and soil organic matter(the correlation coefficients of r were -0.407- -0.641, P<0.05). In conclusion, there was a combined heavy metal pollution and high risk in soils and agro-products. Therefore, the planting of crops in the study area should be avoided, and soil remediation measures should be implemented to reduce security risks.

Information Security Risk Assessment

Information security risk assessment is an important part of enterprises’ management practices that helps to identify, quantify, and prioritize risks against criteria for risk acceptance and objectives relevant to the organization. Risk management refers to a process that consists of identification, management, and elimination or reduction of the likelihood of events that can negatively affect the resources of the information system to reduce security risks that potentially have the ability to affect the information system, subject to an acceptable cost of protection means that contain a risk analysis, analysis of the “cost-effectiveness” parameter, and selection, construction, and testing of the security subsystem, as well as the study of all aspects of security.

A Comprehensive Survey of Internet of Things Security Challenges and possible Solutions

The Internet of Things (IoT) is considered as one of the greatest significant fields of future technology. It is aimed to join anyone with anything at anywhere. IoT will play a critical role and will change our ways of life, aspirations, and business models. It is vulnerable to numerous security threats. IoT security should move towards in perceiving threats and reacting to attacks. In this research we intent to surveys recent research in the field of IoT security. Another goal of this work is to promote IoT security solutions to reduce security risks that affect IoT users.

高空抛物犯罪化的合理性及其边界

近些年来，高空抛掷物品的行为在社会中时有发生，给人民的安全以及社会的稳定带来了极大的隐患。2021年1月13日，《中华人民共和国刑法修正案(十一)》中国人大网上公布，将高空抛物行为作为一项新的立法罪名加以规定。客观地讲，立法机关出台的这项规定有助于更好地规制类似的行为，减少社会中的安全隐患。然而，修正案公布以来，高空抛物行为的犯罪化问题在理论界与实务界引发了巨大的讨论，社会公众对此也给予了极大的关注。为了更好地去界定这一行为，笔者试图从这一行为犯罪化的合理性角度出发，通过对其社会危害性与相关法律的探讨，得出这一行为犯罪化评判需要的合理边界，从而更好地将这一罪名适用于现实生活之中。 In recent years, the act of throwing objects at high altitude has occurred in the society, which has brought great danger to people’s safety and social stability. On January 13, 2021, the Amendment to the Criminal Law of the People’s Republic of China (Eleven) was published on www.npc.gov.cn, mak-ing the high-altitude parabolic type a new legislative offense. Objectively speaking, this provision introduced by the legislature will help to better regulate similar behavior and reduce security risks in society. However, since the publication of the amendment, the crime of high-altitude parabola has aroused great discussion in the theoretical and practical circles, and the public has paid great at-tention to it. In order to better define this behavior, the author tries to get the reasonable boundary of the criminalization judgment of this behavior from the point of view of the rationality of the criminalization of this behavior, and through the discussion of its social harm and relevant laws, so as to better apply this crime to real life.

An Improved Delegated Proof of Stake Consensus Algorithm

Aiming at the problems of the existing DPoS(Delegated Proof of Stake) consensus algorithm, such as low enthusiasm of voting nodes and difficulties in dealing with malicious nodes, we improve the traditional DPoS consensus algorithm and propose a reputation-based delegated proof of stake consensus algorithm, called Reputation-DPoS. In our Reputation-DPoS, the reputation model is introduced. By evaluating the behavior of nodes, nodes are divided into different trusted states, and high-quality nodes in the network are selected as consensus nodes to reduce security risks and improve efficiency. Besides, incentive methods of reputation and token are used to improve the enthusiasm of nodes to participate in voting. Simulation results show that our Reputation-DPoS can reduce the probability of malicious nodes being selected and optimize the state of nodes in DPoS. Nodes with good behavior will get more votes and rewards, which will motivate nodes and improve the security of the system. Insert here your abstract text.

Mogućnosti naše države u zaštiti svojih interesa u postojećoj migrantskoj krizi sa osvrtom na probleme sa migrantima koji su u sukobu sa zakonom

In the modern world, there are many challenges that rightly create anxiety for the future of humanity. There are security challenges in our country, as well as in the Balkans, Europe and beyond. The problem that has been current for several years is the migrant crisis and how to deal with it. No matter how much we try to bring order to this issue, to reduce security risks for our country, given that these are people of other customs, cultures, habits, lifestyles, etc., there is a threat in this regard, especially from potential terrorist attacks. In the paper, we have pointed out only a few, while paying special attention to the problems with migrants who have come into conflict with the law. It also pointed out the dilemmas and problems that our judicial authorities encounter in criminal proceedings and the possibilities of how to overcome them, bearing in mind that for these migrants we are only a transit route to the countries of Western Europe.

AI hardware oriented neural network physical unclonable function and its evaluation

AbstractAI techniques are required for realizing society 5.0. For the issues of societal implementation for AI, an AI hardware, which is enhanced security performances including authentication, and so on, is needed in order to reduce security risks. This study proposes a new physical unclonable function (PUF) based on neural network (NN) called NN PUF. The proposed NN PUF uses a difference of calculation time in NN due to production variations of semiconductor. Evaluation experiments using a field programmable gate array (FPGA) prove the effectiveness of the proposed NN PUF.

Build with intrinsic security: Trusted autonomy security system

Security of Internet of things network is difficult to manage because Internet of things devices are heterogeneous and always deployed in remote places. Based on these features, attacks against Internet of things network like distributed denial-of-service and system intrusion are easier than traditional network. In order to enhance Internet of things network’s security, in this article we propose the concept of intrinsic security to establish a trusted and autonomy Internet of things network. Intrinsic security emphasizes that network itself must be trusted and security autonomous to address the security problems which are caused by remote and heterogeneous. Based on this thought, we designed the architecture of Trusted Autonomy Security System. Trusted Autonomy Security System maintains a LAN characterized by trusted and security autonomy, in which all Internet of things network gateways formed a decentralized autonomy system to evaluate if other gateways or Internet of things devices are secure. Compared to traditional Internet of things networks, this architecture uses trusted computing technique to build the basic of security, and makes Internet of things network available to manage security automatically. In addition, the decentralized architecture could reduce security risks caused by compromise of single node in Internet of things network. With these advantages, it can be expected that this novel idea will have more development in Internet of things scenarios with high security requirements.

Multistation coordinated and dynamic passenger inflow control for a metro line

Passenger inflow control is an efficient way to relieve peak passenger flow and reduce security risks in metro networks. However, station operators develop passenger inflow control strategies independently, thus ignore the interactions among stations and lines in the actual operation. Subsequently, the single-fixed control intensity usually fails to satisfy dynamic temporal passenger demand, resulting in great stranded passengers. To address this problem, a coordinated and dynamic inflow control method is proposed to generate an optimal demand-driven control pattern in metro systems. First, a mixed integer programming model with the concept of the equivalent time interval is formulated to minimise the total number of stranded passengers on one line. Second, special consideration is paid to the transfer passengers with the aim of ensuring the safety of transfer stations. Finally, an actual passenger flow and train operation data in Beijing Batong line is conducted to test the performance of the approach. Compared with the non-coordinated and dynamic inflow control method, results show that the proposed model can balance the utilisation of transportation capacity and reduce the total number of stranded passengers by 20.6%. Sensitivity analysis results indicate that both transportation capacity and transfer capability are the main factors affecting the inflow control.

Federated and secure cloud services for building medical image classifiers on an intercontinental infrastructure

Medical data processing has found a new dimension with the extensive use of machine-learning techniques to classify and extract features. Machine learning strongly benefits from computing accelerators. However, such accelerators are not easily available at hospital premises, although they can be easily found on public cloud infrastructures or research centers. Nevertheless, the sensitivity of medical data poses several challenges on the access to such data, requiring security guarantees and isolation. In this paper we present an architecture that addresses this problem. It keeps critical data encrypted in memory and disk, which can only be accessed inside trusted execution environments protected by hardware extensions. Data is anonymized inside these environments and securely transferred to external sites that host accelerator devices, keeping the same network space and reducing security risks even in untrusted cloud backends. Results on the processing of data in different scenarios are presented and discussed. The results are demonstrated on a geographically-wide deployment provided by the ATMOSPHERE project.

Penerapan Privileged Access Management Menggunakan One Identity Pada Sebuah Perusahaan

&lt;p&gt;&lt;em&gt;One Identity Priveged Access Management (PAM) is a solution for a series of efforts to reduce security risks and help companies secure, control, monitor, analyze, and regulate privileged access rights to data and applications from very important organizations. The PAM solution allows companies to provide full credentials such as Administrators on Windows, Root on UNIX, Cisco Enable on Cisco devices, and embedded passwords found in applications and scripts or restricting access to ordinary users. All privileged account activities are recorded by analyzing real time activities and data. Password sharing activities can be eliminated, so security can be improved and compliance with privileges of privileged access rights is more efficient and manageable. Problems that can be explained when the user privileges password access rights do not have regular rules to change the password periodically in accordance with the security policy (password policy) even to obtain information that has accessed the network device using a special account or other permitted account . The purpose of this study is (i) to obtain information about changes in passwords periodically based on the configuration that has been set in the PAM system and adjusted to the password policy rules, (ii) get information about who is accessing the network device and the account accessed. The research method that is carried out is (i) collecting data from the system that will be implemented, (ii) directly accessing the system that has data and viewing information thoroughly into the system, (iii) matching the type of system with the system supported by the PAM application system then integrate it. Testing is done by accessing the target system using privileged access rights through the PAM application system. The results obtained (i) can facilitate password users not to remember passwords too often, (ii) can avoid sharing password information, (iii) change passwords regularly, (iv) find out all user password activities against a set of targets network systems that are permitted to be accessed, (v) record all access activities in the form of videos.&lt;/em&gt;&lt;/p&gt;

Performance Trade-Offs of an Optical Wireless Communication Network Deployed in an Aircraft Cockpit

In this article, we explore the performance of optical wireless technology for ensuring audio communications inside an aircraft cockpit. One advantage is that, unlike radio frequencies, opaque objects block optical signals and, therefore, signals cannot pass through walls. This can reduce security risks against eavesdropping and hacking of the physical layer, which is one of the main concerns in the aviation environment. However, optical wireless technology faces some issues, including range limitation and sensitivity to blockages. To study the achievable performances, we propose a modeling of the channels for the uplink and the downlink between the headsets of the four pilots of an Airbus A350 and the access point at the cockpit ceiling. A ray-tracing approach associated with a Monte-Carlo method takes into account the 3D geometric model of the cockpit, the presence of the pilots and their movements. We show that using spatial diversity for headset transceivers can improve performance. Using IEEE 802.11 medium access control mechanism to ensure multi-user communication, the approach highlights the trade-offs between power and delay for a successful communication, linked to the maximum achievable data rate for a given performance level.

Trusting artificial intelligence in cybersecurity is a double-edged sword

Applications of artificial intelligence (AI) for cybersecurity tasks are attracting greater attention from the private and the public sectors. Estimates indicate that the market for AI in cybersecurity will grow from US$1 billion in 2016 to a US$34.8 billion net worth by 2025. The latest national cybersecurity and defence strategies of several governments explicitly mention AI capabilities. At the same time, initiatives to define new standards and certification procedures to elicit users’ trust in AI are emerging on a global scale. However, trust in AI (both machine learning and neural networks) to deliver cybersecurity tasks is a double-edged sword: it can improve substantially cybersecurity practices, but can also facilitate new forms of attacks to the AI applications themselves, which may pose severe security threats. We argue that trust in AI for cybersecurity is unwarranted and that, to reduce security risks, some form of control to ensure the deployment of ‘reliable AI’ for cybersecurity is necessary. To this end, we offer three recommendations focusing on the design, development and deployment of AI for cybersecurity. Current national cybersecurity and defence strategies of several governments mention explicitly the use of AI. However, it will be important to develop standards and certification procedures, which involves continuous monitoring and assessment of threats. The focus should be on the reliability of AI-based systems, rather than on eliciting users’ trust in AI.

Design and implementation of forecast and early warning system for offshore platform based on GIS

A forecast and early warning system for offshore platform was developed to reduce security risks of offshore operations. The tool uses an ArcGIS Server as electronic chart display and system platform, in combination with Silverlight, WCF Service and AIS. The system incorporates management of offshore platforms, subsea pipelines and warning zones, as well as real-time monitoring and early warning for typhoon and ships around the platform. This system has been put into use on offshore platforms, and the system’s powerful early warning capabilities, excellent experience and performance have been recognized by the user.

Online voting as an element of cybersecurity of megacities

The subject. The author explores the possibility of online voting during the elections from the perspective of urban security.The purpose of the paper is to confirm or disprove hypothesis that introduction of online voting in the elections in large cities contributes to the growth of the electorate’s confidence and reduction of absenteeism, but only if cybersecurity of metropolises is ensured.The methodology of the study includes general scientific methods (analysis, synthesis, description) and the method of comparative law.The main results and scope of their application. The very essence of online voting involves the use of a dedicated Internet platform and digital devices. This method has many advantages, including the ability to attract many people, the convenience and reliability of the whole process, as well as the automatic calculation of results. However, the issue of online voting in large cities directly affects the problem of ensuring their cybersecurity. Electronic voting can be subject to certain risks like any Internet procedure. Some of them have their own offline counterparts, such as the sale of votes. Others are unique to the digital environment, such as cyber violations and DDoS-attacks.Conclusions. Electronic voting helps to solve the problem of low voters’ turnout, unites communities, universities, companies and people. This new process must be protected from any potential threats to security.An inefficient voter authentication procedure can adversely affect the reliability of the entire online voting system. Hacking the authentication system can lead to fraud and theft of data and votes. The blockchain system provides effective protection against such hacks and cyberattacks. It would be effective if it was possible to download a special anti-virus program from the election commission website to clean the user's computer from malicious content or at least check the presence of viral content. The license key of such a program may be valid only for the period of the elections. The decision against forcing an electronic vote for a particular candidate can be made by an online voting system that allows you to change your choice several times. We need well-thought-out training and advanced training programmes for state and municipal employees, including programmes for initial technical training, to reduce security risks. It is necessary to train possible users of the online voting system, since the security of a computer or smartphone, the absence of virus programs, as well as the timeliness of voting are in the area of responsibility of online voters. Online voting may not be the only way a voter can express his or her will. It is always necessary to keep the possibility of classical voting by paper ballots.

Reducing Security Risks of Suspicious Data and Codes Through a Novel Dynamic Defense Model

A remarkable characteristic of the modern operating system is open, which means that we can download data or execute codes from any Internet sources whether they are trusted or not. Therefore, there is a contradict situation when we want to use these data or codes as well as keep the system secured. Despite decades of studies and experiences on this problem, it is still assumed as a great challenge. This paper presents a novel dynamic defense model (DDM) to reduce security risks brought by these suspicious data or codes for the open operating systems. DDM is a high-level security defense abstraction with four key components: dynamic label marking, dynamic label tracking, dynamic label modulating, and run-time controlling. With these components, DDM achieves the full, dynamic, and real-time security protection in the whole life cycle of the operating system. We also practically implemented a prototype system named DDDroid on Android. We constructed a mixed experimental dataset with 30 malware samples and 970 benign applications to test the defense effects of DDDroid. DDDroid detects 97% of the malware samples that have malicious actions and blocks these actions with a negligible false positive on legal actions. We also demonstrated that DDDroid is an effective system, which prevents sensitive data from being leaked by suspicious applications deliberately or by users unintentionally through some sample experiments. What is more, with extensive evaluations, DDDroid is proved to be a system with low-performance overhead and limited memory consumption.

Agent-based modelling and analysis of security and efficiency in airport terminals

Both security and efficiency are important performance areas of air transport systems. Several methods have been proposed to assess security risks and estimate efficiency independently, but only few of these methods identify relationships between security risks and efficiency performance indicators. To analyze security, efficiency, and the relationships relations between them, an agent-based methodology was proposed in this work. This methodology combines an agent-based security risk assessment approach with agent-based efficiency estimation. The methodology was applied to a case study that analyzes security regarding an Improvised Explosive Device (IED) attack, different commonly used efficiency performance indicators in the aviation domain, such as queuing time for passengers, and the relationships between them. Results showed that reducing security risks and improving efficiency were not always conflicting objectives. Reducing the number of passengers before the security checkpoint was found to be an effective measure to reduce security risks and improve efficiency aspects. Furthermore, results showed that airports should attempt to spread passengers across the available space as much as possible to reduce the impact of an IED attack.