The hedging problem for insiders is very important in the financial market.The locally risk minimizing hedging was adopted to solve this problem.Since the market was incomplete,the minimal martingale measure was chose...The hedging problem for insiders is very important in the financial market.The locally risk minimizing hedging was adopted to solve this problem.Since the market was incomplete,the minimal martingale measure was chosen as the equivalent martingale measure.By the F-S decomposition,the expression of the locally risk minimizing strategy was presented.Finally,the local risk minimization was applied to index tracking and its relationship with tracking error variance (TEV)-minimizing strategy was obtained.展开更多
From the perspective of the insiders and outsiders,this study explores the influence of differential leadership on employees’affective commitment and the moderating effect of leader’s self-enhancing humor and indivi...From the perspective of the insiders and outsiders,this study explores the influence of differential leadership on employees’affective commitment and the moderating effect of leader’s self-enhancing humor and individual traditionality.The results show that the differential leadership has a positive impact on the organizational affective commitment of employees,the leader’s self-enhancing humor and the employees’traditionality play a positive regulatory role respectively.Moreover,compared with the outsiders,the low traditionality has a stronger influence on the relationship between differential leadership and organizational affective commitment of the insiders.This paper enriches the research on the influence of leadership style on employee’s affective commitment,proposes and verifies the moderation of leader’s self-enhancing humor and employee’s traditionality,which complements the boundary conditions for the effectiveness of differential leadership style.展开更多
Chic Beijing:An Insider’s Guide to Unique New Places Compiled by Beijing Radio and Television Station Price:RMB 138 Paperback,307 pages Published by Foreign Languages Press&Beijing Publishing Group If you’re pla...Chic Beijing:An Insider’s Guide to Unique New Places Compiled by Beijing Radio and Television Station Price:RMB 138 Paperback,307 pages Published by Foreign Languages Press&Beijing Publishing Group If you’re planning a trip to Beijing,prepare to be swept up in a living mosaic–more than 3,000 years of history,vibrant contemporary culture,and skyline-defining architecture all fusing and flowing across a vast canvas.This book,Chic Beijing:An Insider’s Guide to Unique New Places,allows readers to take a breathtaking journey through Beijing,the majestic metropolitan capital of China.It also unlocks doors that usually stay closed:rooftop gardens overlooking palace rooftops,micro-galleries tucked into 300-year-old courtyards,and cocktail labs where baijiu meets coffee.展开更多
This study examined the relationship between leader-employee calling congruence on employees’voice behaviour.Participants were 173 leader-employee dyads from the Chinese service industry.They completed online surveys...This study examined the relationship between leader-employee calling congruence on employees’voice behaviour.Participants were 173 leader-employee dyads from the Chinese service industry.They completed online surveys on calling,perceived insider status,and voice behaviour.Results from polynomial regression and response surface analysis showed that employees perceived insider status to be weaker with the low leader-low subordinate calling congruence,and stronger with high leader and high subordinate calling congruence.Employees perceived insider status is stronger in low leader and high subordinate calling incongruence compared with high leader and low subordinate calling incongruence.Perceived insider status plays a mediating role among calling congruence and voice behaviour.This study’sfindings suggest pathways of calling congruence on voice behaviour,which are important for promoting employee voice behaviour and guiding organisational recruitment in the workplace.展开更多
Background Not long ago, I shared my ideas with the insiders during a brand growth forum. At the time, not surprisingly, I received many questions that were often asked: Without financing nor big money, how can a bran...Background Not long ago, I shared my ideas with the insiders during a brand growth forum. At the time, not surprisingly, I received many questions that were often asked: Without financing nor big money, how can a brand grow rapidly? The repurchase is not bad, but it is not working to attract new customers. Can CRM grow only depending on the regular customer? A lot of brands put in hundreds of thousands of money on beauty influencers on internets every month. Why the conversion rate is so bad? My company?s scale is large, basically speaking, but the profit rate is not good. How to improve efficiency? I have no problem with growth, but inventory management is too difficult. It seems to make money. In fact, it is all in stock. How to enhance the uniqueness of my brand? If I?m unique enough, will my brand grow?展开更多
Software-Defined Networking(SDN)is an emerging architecture that enables a computer network to be intelligently and centrally controlled via software applications.It can help manage the whole network environment in a ...Software-Defined Networking(SDN)is an emerging architecture that enables a computer network to be intelligently and centrally controlled via software applications.It can help manage the whole network environment in a consistent and holistic way,without the need of understanding the underlying network structure.At present,SDN may face many challenges like insider attacks,i.e.,the centralized control plane would be attacked by malicious underlying devices and switches.To protect the security of SDN,effective detection approaches are indispensable.In the literature,challenge-based collaborative intrusion detection networks(CIDNs)are an effective detection framework in identifying malicious nodes.It calculates the nodes'reputation and detects a malicious node by sending out a special message called a challenge.In this work,we devise a challenge-based CIDN in SDN and measure its performance against malicious internal nodes.Our results demonstrate that such a mechanism can be effective in SDN environments.展开更多
In the information era,the core business and confidential information of enterprises/organizations is stored in information systems.However,certain malicious inside network users exist hidden inside the organization;t...In the information era,the core business and confidential information of enterprises/organizations is stored in information systems.However,certain malicious inside network users exist hidden inside the organization;these users intentionally or unintentionally misuse the privileges of the organization to obtain sensitive information from the company.The existing approaches on insider threat detection mostly focus on monitoring,detecting,and preventing any malicious behavior generated by users within an organization’s system while ignoring the imbalanced ground-truth insider threat data impact on security.To this end,to be able to detect insider threats more effectively,a data processing tool was developed to process the detected user activity to generate information-use events,and formulated a Data Adjustment(DA)strategy to adjust the weight of the minority and majority samples.Then,an efficient ensemble strategy was utilized,which applied the extreme gradient boosting(XGBoost)model combined with the DA strategy to detect anomalous behavior.The CERT dataset was used for an insider threat to evaluate our approach,which was a real-world dataset with artificially injected insider threat events.The results demonstrated that the proposed approach can effectively detect insider threats,with an accuracy rate of 99.51%and an average recall rate of 98.16%.Compared with other classifiers,the detection performance is improved by 8.76%.展开更多
Purpose: This study takes advantage of newly released journal metrics to investigate whether local journals with more qualified boards have lower acceptance rates, based on data from 219 Turkish national journals and ...Purpose: This study takes advantage of newly released journal metrics to investigate whether local journals with more qualified boards have lower acceptance rates, based on data from 219 Turkish national journals and 2,367 editorial board members.Design/methodology/approach: This study argues that journal editors can signal their scholarly quality by publishing in reputable journals. Conversely, editors publishing inside articles in affiliated national journals would send negative signals. The research predicts that high(low) quality editorial boards will conduct more(less) selective evaluation and their journals will have lower(higher) acceptance rates. Based on the publication strategy of editors, four measures of board quality are defined: Number of board inside publications per editor(INSIDER), number of board Social Sciences Citation Index publications per editor(SSCI), inside-to-SSCI article ratio(ISRA), and board citation per editor(CITATION). Predictions are tested by correlation and regression analysis.Findings: Low-quality board proxies(INSIDER, ISRA) are positively, and high-quality board proxies(SSCI, CITATION) are negatively associated with acceptance rates. Further, we find that receiving a larger number of submissions, greater women representation on boards, and Web of Science and Scopus(WOSS) coverage are associated with lower acceptance rates. Acceptance rates for journals range from 12% to 91%, with an average of 54% and a median of 53%. Law journals have significantly higher average acceptance rate(68%) than other journals, while WOSS journals have the lowest(43%). Findings indicate some of the highest acceptance rates in Social Sciences literature, including competitive Business and Economics journals that traditionally have low acceptance rates. Limitations: Research relies on local context to define publication strategy of editors. Findings may not be generalizable to mainstream journals and core science countries where emphasis on research quality is stronger and editorial selection is based on scientific merit.Practical implications: Results offer useful insights into editorial management of national journals and allow us to make sense of local editorial practices. The importance of scientific merit for selection to national journal editorial boards is particularly highlighted for sound editorial evaluation of submitted manuscripts.Originality/value: This is the first attempt to document a significant relation between acceptance rates and editorial board publication behavior.展开更多
As nearly half of the incidents in enterprise security have been triggered by insiders,it is important to deploy a more intelligent defense system to assist enterprises in pinpointing and resolving the incidents cause...As nearly half of the incidents in enterprise security have been triggered by insiders,it is important to deploy a more intelligent defense system to assist enterprises in pinpointing and resolving the incidents caused by insiders or malicious software(malware)in real-time.Failing to do so may cause a serious loss of reputation as well as business.At the same time,modern network traffic has dynamic patterns,high complexity,and large volumes that make it more difficult to detect malware early.The ability to learn tasks sequentially is crucial to the development of artificial intelligence.Existing neurogenetic computation models with deep-learning techniques are able to detect complex patterns;however,the models have limitations,including catastrophic forgetfulness,and require intensive computational resources.As defense systems using deep-learning models require more time to learn new traffic patterns,they cannot perform fully online(on-the-fly)learning.Hence,an intelligent attack/malware detection system with on-the-fly learning capability is required.For this paper,a memory-prediction framework was adopted,and a simplified single cell assembled sequential hierarchical memory(s.SCASHM)model instead of the hierarchical temporal memory(HTM)model is proposed to speed up learning convergence to achieve onthe-fly learning.The s.SCASHM consists of a Single Neuronal Cell(SNC)model and a simplified Sequential Hierarchical Superset(SHS)platform.The s.SCASHMis implemented as the prediction engine of a user behavior analysis tool to detect insider attacks/anomalies.The experimental results show that the proposed memory model can predict users’traffic behavior with accuracy level ranging from 72%to 83%while performing on-the-fly learning.展开更多
The security problems of wireless sensor networks (WSN) have attracted people’s wide attention. In this paper, after we have summarized the existing security problems and solutions in WSN, we find that the insider at...The security problems of wireless sensor networks (WSN) have attracted people’s wide attention. In this paper, after we have summarized the existing security problems and solutions in WSN, we find that the insider attack to WSN is hard to solve. Insider attack is different from outsider attack, because it can’t be solved by the traditional encryption and message authentication. Therefore, a reliable secure routing protocol should be proposed in order to defense the insider attack. In this paper, we focus on insider selective forwarding attack. The existing detection mechanisms, such as watchdog, multipath retreat, neighbor-based monitoring and so on, have both advantages and disadvantages. According to their characteristics, we proposed a secure routing protocol based on monitor node and trust mechanism. The reputation value is made up with packet forwarding rate and node’s residual energy. So this detection and routing mechanism is universal because it can take account of both the safety and lifetime of network. Finally, we use OPNET simulation to verify the performance of our algorithm.展开更多
Purpose:This study investigated the publication behaviour of 573 chief editors managing 432 Social Sciences journals in Turkey.Direct inquiries into editorial qualifications are rare,and this research aims to shed lig...Purpose:This study investigated the publication behaviour of 573 chief editors managing 432 Social Sciences journals in Turkey.Direct inquiries into editorial qualifications are rare,and this research aims to shed light on editors’scientific leadership capabilities.Design/methodology/approach:This study contrasts insider publication behaviour in national journals with international articles in journals indexed by the Web of Science(WOS)and Scopus.It argues that editors demonstrating a consistent ability to publish in competitive WOS and Scopus indexed journals signal high qualifications,while editors with persistent insider behaviour and strong local orientation signal low qualification.Scientific leadership capability is measured by first-authored publications.Correlation and various regression tests are conducted to identify significant determinants of publication behaviour.Findings:International publications are rare and concentrated on a few individuals,while insider publications are endemic and constitute nearly 40%of all national articles.Editors publish 3.2 insider papers and 8.1 national papers for every SSCI article.62%(58%)of the editors have no SSCI(Scopus)article,53%(63%)do not have a single lead-authored WOS(Scopus)article,and 89%publish at least one insider paper.Only a minority consistently publish in international journals;a fifth of the editors have three or more SSCI publications,and a quarter have three or more Scopus articles.Editors with foreign Ph.D.degrees are the most qualified and internationally oriented,whereas non-mobile editors are the most underqualified and underperform other editors by every measure.Illustrating the overall lack of qualification,nearly half of the professor editors and the majority of the WOS and Scopus indexed journal editors have no record of SSCI or Scopus publications.Research limitations:This research relies on local settings that encourage national publications at the expense of international journals.Findings should be evaluated in light of this setting and bearing in mind that narrow localities are more prone to peer favouritism.Practical implications:Incompetent and nepotistic editors pose an imminent threat to Turkish national literature.A lasting solution would likely include the dismissal and replacement of unqualified editors,as well as delisting and closure of dozens of journals that operate in questionable ways and serve little scientific purpose.Originality/value:To my knowledge,this is the first study to document the publication behaviour of national journal chief editors.展开更多
Using data from the Bucharest Stock Exchange,we examine the factors influencing the probability of informed trading(PIN)during February—October 2020,a COVID-19 pandemic period.Based on an unconditional quantile regre...Using data from the Bucharest Stock Exchange,we examine the factors influencing the probability of informed trading(PIN)during February—October 2020,a COVID-19 pandemic period.Based on an unconditional quantile regression approach,we show that PIN exhibit asymmetric dependency with liquidity and trading costs.Furthermore,building a customized database that contains all insider transactions on the Bucharest Stock Exchange,we reveal that these types of orders monotonically increase the infor-mation asymmetry from the 50th to the 90th quantile throughout the PIN distribution.Finally,we bring strong empirical evidence associating the level of information asym-metry to the level of fake news related to the COVID-19 pandemic.This novel result suggests that during episodes when the level of PIN is medium to high(between 15 and 50%),any COVID-19 related news classified as misinformation released during the lockdown period,is discouraging informed traders to place buy or sell orders condi-tioned by their private information.展开更多
Previous empirical evidence on the liquidity effect to the lockup expiration is mixed. A sample from Chinese listed firms is adopted and contributes to better understand this effect in emerging markets. The spread and...Previous empirical evidence on the liquidity effect to the lockup expiration is mixed. A sample from Chinese listed firms is adopted and contributes to better understand this effect in emerging markets. The spread and illiquidity significantly increases around lockup expiration in China. Furthermore, the liquidity reaction to firms' disclosure quality is explicitly related. The results confirm that higher disclosure quality is significantly associated with lower abnormal spread and illiquidity impact. The effect of lockup expiration shares on liquidity proxies differs in firm disclosure quality. Identifying the factors affecting liquidity around such events may help regulators develop policies to provide investors with greater confidence in their investments.展开更多
A model of continuous-time insider trading in which a risk-neutral in-sider possesses two imperfect correlated signals of a risky asset is studied.By conditional expectation theory and filtering theory,we first establ...A model of continuous-time insider trading in which a risk-neutral in-sider possesses two imperfect correlated signals of a risky asset is studied.By conditional expectation theory and filtering theory,we first establish three lemmas:normal corre-lation,equivalent pricing and equivalent profit,which can guarantee to turn our model into a model with insider knowing full information.Then we investigate the impact of the two correlated signals on the market equilibrium consisting of optimal insider trading strategy and semi-strong pricing rule.It shows that in the equilibrium,(1)the market depth is constant over time;(2)if the two noisy signals are not linerly correlated,then all private information of the insider is incorporated into prices in the end while the whole information on the asset value can not incorporated into prices in the end;(3)if the two noisy signals are linear correlated such that the insider can infer the whole information of the asset value,then our model turns into a model with insider knowing full information;(4)if the two noisy signals are the same then the total ex ant profit of the insider is increasing with the noise decreasing,while down to O as the noise going up to infinity;(5)if the two noisy signals are not linear correlated then with one noisy signal fixed,the total ex ante profit of the insider is single-peaked with a unique minimum with respect to the other noisy signal value,and furthermore as the noisy value going to O it gets its maximum,the profit in the case that the real value is observed.展开更多
Cloud computing is a high network infrastructure where users,owners,third users,authorized users,and customers can access and store their information quickly.The use of cloud computing has realized the rapid increase ...Cloud computing is a high network infrastructure where users,owners,third users,authorized users,and customers can access and store their information quickly.The use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing efficiently.This cloud is nowadays highly affected by internal threats of the user.Sensitive applications such as banking,hospital,and business are more likely affected by real user threats.An intruder is presented as a user and set as a member of the network.After becoming an insider in the network,they will try to attack or steal sensitive data during information sharing or conversation.The major issue in today's technological development is identifying the insider threat in the cloud network.When data are lost,compromising cloud users is difficult.Privacy and security are not ensured,and then,the usage of the cloud is not trusted.Several solutions are available for the external security of the cloud network.However,insider or internal threats need to be addressed.In this research work,we focus on a solution for identifying an insider attack using the artificial intelligence technique.An insider attack is possible by using nodes of weak users’systems.They will log in using a weak user id,connect to a network,and pretend to be a trusted node.Then,they can easily attack and hack information as an insider,and identifying them is very difficult.These types of attacks need intelligent solutions.A machine learning approach is widely used for security issues.To date,the existing lags can classify the attackers accurately.This information hijacking process is very absurd,which motivates young researchers to provide a solution for internal threats.In our proposed work,we track the attackers using a user interaction behavior pattern and deep learning technique.The usage of mouse movements and clicks and keystrokes of the real user is stored in a database.The deep belief neural network is designed using a restricted Boltzmann machine(RBM)so that the layer of RBM communicates with the previous and subsequent layers.The result is evaluated using a Cooja simulator based on the cloud environment.The accuracy and F-measure are highly improved compared with when using the existing long short-term memory and support vector machine.展开更多
Unlike external attacks,insider threats arise from legitimate users who belong to the organization.These individuals may be a potential threat for hostile behavior depending on their motives.For insider detection,many...Unlike external attacks,insider threats arise from legitimate users who belong to the organization.These individuals may be a potential threat for hostile behavior depending on their motives.For insider detection,many intrusion detection systems learn and prevent known scenarios,but because malicious behavior has similar patterns to normal behavior,in reality,these systems can be evaded.Furthermore,because insider threats share a feature space similar to normal behavior,identifying them by detecting anomalies has limitations.This study proposes an improved anomaly detection methodology for insider threats that occur in cybersecurity in which a discrete wavelet transformation technique is applied to classify normal vs.malicious users.The discrete wavelet transformation technique easily discovers new patterns or decomposes synthesized data,making it possible to distinguish between shared characteristics.To verify the efficacy of the proposed methodology,experiments were conducted in which normal users and malicious users were classified based on insider threat scenarios provided in Carnegie Mellon University’s Computer Emergency Response Team(CERT)dataset.The experimental results indicate that the proposed methodology with discrete wavelet transformation reduced the false-positive rate by 82%to 98%compared to the case with no wavelet applied.Thus,the proposed methodology has high potential for application to similar feature spaces.展开更多
Most of the articles about insider trading assume that there is only one risky asset in the market. On the basis of these papers, this thesis is mainly divided into three parts to study the situation of multiple risky...Most of the articles about insider trading assume that there is only one risky asset in the market. On the basis of these papers, this thesis is mainly divided into three parts to study the situation of multiple risky assets in the market. In the first part, the situation of multiple risky assets in the market when two transactions are in progress is studied and then, the equilibrium when the market requires the internal traders to disclose the trading volume after each transaction is analyzed. In the second part, the equilibrium of multi-period based on the two phases of transaction is derived. The third part is the summary of the paper.展开更多
基金National Natural Science Foundations of China (No. 11071076,No. 11126124)
文摘The hedging problem for insiders is very important in the financial market.The locally risk minimizing hedging was adopted to solve this problem.Since the market was incomplete,the minimal martingale measure was chosen as the equivalent martingale measure.By the F-S decomposition,the expression of the locally risk minimizing strategy was presented.Finally,the local risk minimization was applied to index tracking and its relationship with tracking error variance (TEV)-minimizing strategy was obtained.
文摘From the perspective of the insiders and outsiders,this study explores the influence of differential leadership on employees’affective commitment and the moderating effect of leader’s self-enhancing humor and individual traditionality.The results show that the differential leadership has a positive impact on the organizational affective commitment of employees,the leader’s self-enhancing humor and the employees’traditionality play a positive regulatory role respectively.Moreover,compared with the outsiders,the low traditionality has a stronger influence on the relationship between differential leadership and organizational affective commitment of the insiders.This paper enriches the research on the influence of leadership style on employee’s affective commitment,proposes and verifies the moderation of leader’s self-enhancing humor and employee’s traditionality,which complements the boundary conditions for the effectiveness of differential leadership style.
文摘Chic Beijing:An Insider’s Guide to Unique New Places Compiled by Beijing Radio and Television Station Price:RMB 138 Paperback,307 pages Published by Foreign Languages Press&Beijing Publishing Group If you’re planning a trip to Beijing,prepare to be swept up in a living mosaic–more than 3,000 years of history,vibrant contemporary culture,and skyline-defining architecture all fusing and flowing across a vast canvas.This book,Chic Beijing:An Insider’s Guide to Unique New Places,allows readers to take a breathtaking journey through Beijing,the majestic metropolitan capital of China.It also unlocks doors that usually stay closed:rooftop gardens overlooking palace rooftops,micro-galleries tucked into 300-year-old courtyards,and cocktail labs where baijiu meets coffee.
基金supported by the Major Research Project of Philosophy and Social Sciences in Universities of Henan Province(2025-JCZD-10)the Natural Science Foundation of Henan Province(242300421311).
文摘This study examined the relationship between leader-employee calling congruence on employees’voice behaviour.Participants were 173 leader-employee dyads from the Chinese service industry.They completed online surveys on calling,perceived insider status,and voice behaviour.Results from polynomial regression and response surface analysis showed that employees perceived insider status to be weaker with the low leader-low subordinate calling congruence,and stronger with high leader and high subordinate calling congruence.Employees perceived insider status is stronger in low leader and high subordinate calling incongruence compared with high leader and low subordinate calling incongruence.Perceived insider status plays a mediating role among calling congruence and voice behaviour.This study’sfindings suggest pathways of calling congruence on voice behaviour,which are important for promoting employee voice behaviour and guiding organisational recruitment in the workplace.
文摘Background Not long ago, I shared my ideas with the insiders during a brand growth forum. At the time, not surprisingly, I received many questions that were often asked: Without financing nor big money, how can a brand grow rapidly? The repurchase is not bad, but it is not working to attract new customers. Can CRM grow only depending on the regular customer? A lot of brands put in hundreds of thousands of money on beauty influencers on internets every month. Why the conversion rate is so bad? My company?s scale is large, basically speaking, but the profit rate is not good. How to improve efficiency? I have no problem with growth, but inventory management is too difficult. It seems to make money. In fact, it is all in stock. How to enhance the uniqueness of my brand? If I?m unique enough, will my brand grow?
基金This work was supported by National Natural Science Foundation of China(No.61802080 and 61802077)Guangdong General Colleges and Universities Research Project(2018GkQNCX105)+1 种基金Zhongshan Public Welfare Science and Technology Research Project(2019B2044)Keping Yu was supported in part by the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(KAKENHI)under Grant JP18K18044.
文摘Software-Defined Networking(SDN)is an emerging architecture that enables a computer network to be intelligently and centrally controlled via software applications.It can help manage the whole network environment in a consistent and holistic way,without the need of understanding the underlying network structure.At present,SDN may face many challenges like insider attacks,i.e.,the centralized control plane would be attacked by malicious underlying devices and switches.To protect the security of SDN,effective detection approaches are indispensable.In the literature,challenge-based collaborative intrusion detection networks(CIDNs)are an effective detection framework in identifying malicious nodes.It calculates the nodes'reputation and detects a malicious node by sending out a special message called a challenge.In this work,we devise a challenge-based CIDN in SDN and measure its performance against malicious internal nodes.Our results demonstrate that such a mechanism can be effective in SDN environments.
基金This work was financially supported by“the National Key R&D Program of China”(No.2018YFB0803602)exploration and practice on the education mode for engineering students based on technology,literature and art interdisciplinary integration with the Internet+background(No.022150118004/001)。
文摘In the information era,the core business and confidential information of enterprises/organizations is stored in information systems.However,certain malicious inside network users exist hidden inside the organization;these users intentionally or unintentionally misuse the privileges of the organization to obtain sensitive information from the company.The existing approaches on insider threat detection mostly focus on monitoring,detecting,and preventing any malicious behavior generated by users within an organization’s system while ignoring the imbalanced ground-truth insider threat data impact on security.To this end,to be able to detect insider threats more effectively,a data processing tool was developed to process the detected user activity to generate information-use events,and formulated a Data Adjustment(DA)strategy to adjust the weight of the minority and majority samples.Then,an efficient ensemble strategy was utilized,which applied the extreme gradient boosting(XGBoost)model combined with the DA strategy to detect anomalous behavior.The CERT dataset was used for an insider threat to evaluate our approach,which was a real-world dataset with artificially injected insider threat events.The results demonstrated that the proposed approach can effectively detect insider threats,with an accuracy rate of 99.51%and an average recall rate of 98.16%.Compared with other classifiers,the detection performance is improved by 8.76%.
文摘Purpose: This study takes advantage of newly released journal metrics to investigate whether local journals with more qualified boards have lower acceptance rates, based on data from 219 Turkish national journals and 2,367 editorial board members.Design/methodology/approach: This study argues that journal editors can signal their scholarly quality by publishing in reputable journals. Conversely, editors publishing inside articles in affiliated national journals would send negative signals. The research predicts that high(low) quality editorial boards will conduct more(less) selective evaluation and their journals will have lower(higher) acceptance rates. Based on the publication strategy of editors, four measures of board quality are defined: Number of board inside publications per editor(INSIDER), number of board Social Sciences Citation Index publications per editor(SSCI), inside-to-SSCI article ratio(ISRA), and board citation per editor(CITATION). Predictions are tested by correlation and regression analysis.Findings: Low-quality board proxies(INSIDER, ISRA) are positively, and high-quality board proxies(SSCI, CITATION) are negatively associated with acceptance rates. Further, we find that receiving a larger number of submissions, greater women representation on boards, and Web of Science and Scopus(WOSS) coverage are associated with lower acceptance rates. Acceptance rates for journals range from 12% to 91%, with an average of 54% and a median of 53%. Law journals have significantly higher average acceptance rate(68%) than other journals, while WOSS journals have the lowest(43%). Findings indicate some of the highest acceptance rates in Social Sciences literature, including competitive Business and Economics journals that traditionally have low acceptance rates. Limitations: Research relies on local context to define publication strategy of editors. Findings may not be generalizable to mainstream journals and core science countries where emphasis on research quality is stronger and editorial selection is based on scientific merit.Practical implications: Results offer useful insights into editorial management of national journals and allow us to make sense of local editorial practices. The importance of scientific merit for selection to national journal editorial boards is particularly highlighted for sound editorial evaluation of submitted manuscripts.Originality/value: This is the first attempt to document a significant relation between acceptance rates and editorial board publication behavior.
基金This research was funded by Scientific Research Deanship,Albaha University,under the Grant Number:[24/1440].
文摘As nearly half of the incidents in enterprise security have been triggered by insiders,it is important to deploy a more intelligent defense system to assist enterprises in pinpointing and resolving the incidents caused by insiders or malicious software(malware)in real-time.Failing to do so may cause a serious loss of reputation as well as business.At the same time,modern network traffic has dynamic patterns,high complexity,and large volumes that make it more difficult to detect malware early.The ability to learn tasks sequentially is crucial to the development of artificial intelligence.Existing neurogenetic computation models with deep-learning techniques are able to detect complex patterns;however,the models have limitations,including catastrophic forgetfulness,and require intensive computational resources.As defense systems using deep-learning models require more time to learn new traffic patterns,they cannot perform fully online(on-the-fly)learning.Hence,an intelligent attack/malware detection system with on-the-fly learning capability is required.For this paper,a memory-prediction framework was adopted,and a simplified single cell assembled sequential hierarchical memory(s.SCASHM)model instead of the hierarchical temporal memory(HTM)model is proposed to speed up learning convergence to achieve onthe-fly learning.The s.SCASHM consists of a Single Neuronal Cell(SNC)model and a simplified Sequential Hierarchical Superset(SHS)platform.The s.SCASHMis implemented as the prediction engine of a user behavior analysis tool to detect insider attacks/anomalies.The experimental results show that the proposed memory model can predict users’traffic behavior with accuracy level ranging from 72%to 83%while performing on-the-fly learning.
文摘The security problems of wireless sensor networks (WSN) have attracted people’s wide attention. In this paper, after we have summarized the existing security problems and solutions in WSN, we find that the insider attack to WSN is hard to solve. Insider attack is different from outsider attack, because it can’t be solved by the traditional encryption and message authentication. Therefore, a reliable secure routing protocol should be proposed in order to defense the insider attack. In this paper, we focus on insider selective forwarding attack. The existing detection mechanisms, such as watchdog, multipath retreat, neighbor-based monitoring and so on, have both advantages and disadvantages. According to their characteristics, we proposed a secure routing protocol based on monitor node and trust mechanism. The reputation value is made up with packet forwarding rate and node’s residual energy. So this detection and routing mechanism is universal because it can take account of both the safety and lifetime of network. Finally, we use OPNET simulation to verify the performance of our algorithm.
文摘Purpose:This study investigated the publication behaviour of 573 chief editors managing 432 Social Sciences journals in Turkey.Direct inquiries into editorial qualifications are rare,and this research aims to shed light on editors’scientific leadership capabilities.Design/methodology/approach:This study contrasts insider publication behaviour in national journals with international articles in journals indexed by the Web of Science(WOS)and Scopus.It argues that editors demonstrating a consistent ability to publish in competitive WOS and Scopus indexed journals signal high qualifications,while editors with persistent insider behaviour and strong local orientation signal low qualification.Scientific leadership capability is measured by first-authored publications.Correlation and various regression tests are conducted to identify significant determinants of publication behaviour.Findings:International publications are rare and concentrated on a few individuals,while insider publications are endemic and constitute nearly 40%of all national articles.Editors publish 3.2 insider papers and 8.1 national papers for every SSCI article.62%(58%)of the editors have no SSCI(Scopus)article,53%(63%)do not have a single lead-authored WOS(Scopus)article,and 89%publish at least one insider paper.Only a minority consistently publish in international journals;a fifth of the editors have three or more SSCI publications,and a quarter have three or more Scopus articles.Editors with foreign Ph.D.degrees are the most qualified and internationally oriented,whereas non-mobile editors are the most underqualified and underperform other editors by every measure.Illustrating the overall lack of qualification,nearly half of the professor editors and the majority of the WOS and Scopus indexed journal editors have no record of SSCI or Scopus publications.Research limitations:This research relies on local settings that encourage national publications at the expense of international journals.Findings should be evaluated in light of this setting and bearing in mind that narrow localities are more prone to peer favouritism.Practical implications:Incompetent and nepotistic editors pose an imminent threat to Turkish national literature.A lasting solution would likely include the dismissal and replacement of unqualified editors,as well as delisting and closure of dozens of journals that operate in questionable ways and serve little scientific purpose.Originality/value:To my knowledge,this is the first study to document the publication behaviour of national journal chief editors.
基金Analiza impactului incertitudinilor actuale asupra mediului economic,ediția 2022,No.750/19.05.2022(en:Analysis of the impact of current uncertainties on the economic environment,2022 edition,No.750/19.05.2022).Recipient:Cosmin-Octavian CEPOI,PhD.
文摘Using data from the Bucharest Stock Exchange,we examine the factors influencing the probability of informed trading(PIN)during February—October 2020,a COVID-19 pandemic period.Based on an unconditional quantile regression approach,we show that PIN exhibit asymmetric dependency with liquidity and trading costs.Furthermore,building a customized database that contains all insider transactions on the Bucharest Stock Exchange,we reveal that these types of orders monotonically increase the infor-mation asymmetry from the 50th to the 90th quantile throughout the PIN distribution.Finally,we bring strong empirical evidence associating the level of information asym-metry to the level of fake news related to the COVID-19 pandemic.This novel result suggests that during episodes when the level of PIN is medium to high(between 15 and 50%),any COVID-19 related news classified as misinformation released during the lockdown period,is discouraging informed traders to place buy or sell orders condi-tioned by their private information.
基金the China Postdoctoral Science Foundation(No.2015M571546)the National Natural Science Foundation of China(No.73120107002)
文摘Previous empirical evidence on the liquidity effect to the lockup expiration is mixed. A sample from Chinese listed firms is adopted and contributes to better understand this effect in emerging markets. The spread and illiquidity significantly increases around lockup expiration in China. Furthermore, the liquidity reaction to firms' disclosure quality is explicitly related. The results confirm that higher disclosure quality is significantly associated with lower abnormal spread and illiquidity impact. The effect of lockup expiration shares on liquidity proxies differs in firm disclosure quality. Identifying the factors affecting liquidity around such events may help regulators develop policies to provide investors with greater confidence in their investments.
文摘A model of continuous-time insider trading in which a risk-neutral in-sider possesses two imperfect correlated signals of a risky asset is studied.By conditional expectation theory and filtering theory,we first establish three lemmas:normal corre-lation,equivalent pricing and equivalent profit,which can guarantee to turn our model into a model with insider knowing full information.Then we investigate the impact of the two correlated signals on the market equilibrium consisting of optimal insider trading strategy and semi-strong pricing rule.It shows that in the equilibrium,(1)the market depth is constant over time;(2)if the two noisy signals are not linerly correlated,then all private information of the insider is incorporated into prices in the end while the whole information on the asset value can not incorporated into prices in the end;(3)if the two noisy signals are linear correlated such that the insider can infer the whole information of the asset value,then our model turns into a model with insider knowing full information;(4)if the two noisy signals are the same then the total ex ant profit of the insider is increasing with the noise decreasing,while down to O as the noise going up to infinity;(5)if the two noisy signals are not linear correlated then with one noisy signal fixed,the total ex ante profit of the insider is single-peaked with a unique minimum with respect to the other noisy signal value,and furthermore as the noisy value going to O it gets its maximum,the profit in the case that the real value is observed.
文摘Cloud computing is a high network infrastructure where users,owners,third users,authorized users,and customers can access and store their information quickly.The use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing efficiently.This cloud is nowadays highly affected by internal threats of the user.Sensitive applications such as banking,hospital,and business are more likely affected by real user threats.An intruder is presented as a user and set as a member of the network.After becoming an insider in the network,they will try to attack or steal sensitive data during information sharing or conversation.The major issue in today's technological development is identifying the insider threat in the cloud network.When data are lost,compromising cloud users is difficult.Privacy and security are not ensured,and then,the usage of the cloud is not trusted.Several solutions are available for the external security of the cloud network.However,insider or internal threats need to be addressed.In this research work,we focus on a solution for identifying an insider attack using the artificial intelligence technique.An insider attack is possible by using nodes of weak users’systems.They will log in using a weak user id,connect to a network,and pretend to be a trusted node.Then,they can easily attack and hack information as an insider,and identifying them is very difficult.These types of attacks need intelligent solutions.A machine learning approach is widely used for security issues.To date,the existing lags can classify the attackers accurately.This information hijacking process is very absurd,which motivates young researchers to provide a solution for internal threats.In our proposed work,we track the attackers using a user interaction behavior pattern and deep learning technique.The usage of mouse movements and clicks and keystrokes of the real user is stored in a database.The deep belief neural network is designed using a restricted Boltzmann machine(RBM)so that the layer of RBM communicates with the previous and subsequent layers.The result is evaluated using a Cooja simulator based on the cloud environment.The accuracy and F-measure are highly improved compared with when using the existing long short-term memory and support vector machine.
基金This work was supported by the Research Program through the National Research Foundation of Korea,NRF-2022R1F1A1073375。
文摘Unlike external attacks,insider threats arise from legitimate users who belong to the organization.These individuals may be a potential threat for hostile behavior depending on their motives.For insider detection,many intrusion detection systems learn and prevent known scenarios,but because malicious behavior has similar patterns to normal behavior,in reality,these systems can be evaded.Furthermore,because insider threats share a feature space similar to normal behavior,identifying them by detecting anomalies has limitations.This study proposes an improved anomaly detection methodology for insider threats that occur in cybersecurity in which a discrete wavelet transformation technique is applied to classify normal vs.malicious users.The discrete wavelet transformation technique easily discovers new patterns or decomposes synthesized data,making it possible to distinguish between shared characteristics.To verify the efficacy of the proposed methodology,experiments were conducted in which normal users and malicious users were classified based on insider threat scenarios provided in Carnegie Mellon University’s Computer Emergency Response Team(CERT)dataset.The experimental results indicate that the proposed methodology with discrete wavelet transformation reduced the false-positive rate by 82%to 98%compared to the case with no wavelet applied.Thus,the proposed methodology has high potential for application to similar feature spaces.
文摘Most of the articles about insider trading assume that there is only one risky asset in the market. On the basis of these papers, this thesis is mainly divided into three parts to study the situation of multiple risky assets in the market. In the first part, the situation of multiple risky assets in the market when two transactions are in progress is studied and then, the equilibrium when the market requires the internal traders to disclose the trading volume after each transaction is analyzed. In the second part, the equilibrium of multi-period based on the two phases of transaction is derived. The third part is the summary of the paper.
