Forensic accounting gained importance due to increasing number of financial frauds and scams. This new area in accounting encompasses accounting, auditing, and investigative skills, thus emerged to detect frauds. They...Forensic accounting gained importance due to increasing number of financial frauds and scams. This new area in accounting encompasses accounting, auditing, and investigative skills, thus emerged to detect frauds. They involve themselves in different areas like employee-related frauds, settlement and arbitrations, etc.. A forensic accountant has a financial sixth sense. Despite the fact that forensic accounting can bridge the gap between conventional accounting and auditing, this profession has not been able to gain the needed momentum due to some hassles. This paper tries to shed light on the theoretical concept, nature, practice, need, role of forensic accounting in preventing fraud, and the practical difficulties faced by forensic accountants. The study is based on information collected from interviewing practicing forensic accounting in India during 2011-12. The paper was able to assess the importance and rising scope of forensic accounting as a job. It also understood the practical difficulties they faced like lack of organized databases in Indian scenario which makes it difficult to access all needed information. Expectation level of the clients is very high and at times even unreasonable. This paper fulfills an identified need to study the important rising field of forensic accounting in India.展开更多
Information security often involves the development and application of so</span><span style="font-family:Verdana;">phisticated software to protect sensitive information stored in corporate</sp...Information security often involves the development and application of so</span><span style="font-family:Verdana;">phisticated software to protect sensitive information stored in corporate</span><span style="font-family:Verdana;"> computers. Yet, in this example of corporate espionage, a clever person, a cellphone and some readily available software were all it took to crack through one company’s advanced security barriers. By reading this article it is hoped that employees at all levels of an organization’s hierarchy will become more aware of—and recognize—how: 1) bits and pieces of seemingly harmless and easy-to-acquire information can be used for sinister purposes;2) building rapport and trust with a person can make them more likely to become unknowing co-conspirators in a devious undertaking;and 3) how one must be constantly alert not to give out information without carefully considering the authenticity and justification of the source requesting it.展开更多
Ethereum's high attention,rich business,certain anonymity,and untraceability have attracted a group of attackers.Cybercrime on it has become increasingly rampant,among which scam behavior is convenient,cryptic,ant...Ethereum's high attention,rich business,certain anonymity,and untraceability have attracted a group of attackers.Cybercrime on it has become increasingly rampant,among which scam behavior is convenient,cryptic,antagonistic and resulting in large economic losses.So we consider the scam behavior on Ethereum and investigate it at the node interaction level.Based on the life cycle and risk identification points we found,we propose an automatic detection model named Aparecium.First,a graph generation method which focus on the scam life cycle is adopted to mitigate the sparsity of the scam behaviors.Second,the life cycle patterns are delicate modeled because of the crypticity and antagonism of Ethereum scam behaviors.Conducting experiments in the wild Ethereum datasets,we prove Aparecium is effective which the precision,recall and F1-score achieve at 0.977,0.957 and 0.967 respectively.展开更多
The recent surge of Ethereum in prominence has made it an attractive target for various kinds of crypto crimes.Phishing scams,for example,are an increasingly prevalent cybercrime in which malicious users attempt to st...The recent surge of Ethereum in prominence has made it an attractive target for various kinds of crypto crimes.Phishing scams,for example,are an increasingly prevalent cybercrime in which malicious users attempt to steal funds from a user’s crypto wallet.This research investigates the effects of network architectural features as well as the temporal aspects of user activities on the performance of detecting phishing users on the Ethereum transaction network.We employ traditional machine learning algorithms to evaluate our model on real-world Ethereum transaction data.The experimental results demonstrate that our proposed features identify phishing accounts efficiently and outperform the baseline models by 4%in Recall and 5%in F1-score.展开更多
The“Bitcoin Generator Scam”(BGS)is a cyberattack in which scammers promise to provide victims with free cryptocurrencies in exchange for a small mining fee.In this paper,we present a data-driven system to detect,tra...The“Bitcoin Generator Scam”(BGS)is a cyberattack in which scammers promise to provide victims with free cryptocurrencies in exchange for a small mining fee.In this paper,we present a data-driven system to detect,track,and analyze the BGS.It works as follows:we first formulate search queries related to BGS and use search engines to find potential instances of the scam.We then use a crawler to access these pages and a classifier to differentiate actual scam instances from benign pages.Last,we automatically monitor the BGS instances to extract the cryptocurrency addresses used in the scam.A unique feature of our system is that it proactively searches for and detects the scam pages.Thus,we can find addresses that have not yet received any transactions.Our data collection project spanned 16 months,from November 2019 to February 2021.We uncovered more than 8,000 cryptocurrency addresses directly associated with the scam,hosted on over 1,000 domains.Overall,these addresses have received around 8.7 million USD,with an average of 49.24 USD per transaction.Over 70%of the active addresses that we are capturing are detected before they receive any transactions,that is,before anyone is victimized.We also present some post-processing analysis of the dataset that we have captured to aggregate attacks that can be reasonably confidently linked to the same attacker or group.Our system is one of the first academic feeds to the APWG eCrime Exchange database.It has been actively and automatically feeding the database since November 2020.展开更多
On June 19,2017,the Shenzhen Intermediate People's Court opened its second hearing on Liu Qjanzhen,an unemployed 57-year-old villager from Jiangsu province--or,as his victim Zheng Xueju knew him,the "Qjanlong...On June 19,2017,the Shenzhen Intermediate People's Court opened its second hearing on Liu Qjanzhen,an unemployed 57-year-old villager from Jiangsu province--or,as his victim Zheng Xueju knew him,the "Qjanlong Emperor," the still-surviving inheritor of multiple Qjng family fortunes and sound investment opportunity.展开更多
文摘Forensic accounting gained importance due to increasing number of financial frauds and scams. This new area in accounting encompasses accounting, auditing, and investigative skills, thus emerged to detect frauds. They involve themselves in different areas like employee-related frauds, settlement and arbitrations, etc.. A forensic accountant has a financial sixth sense. Despite the fact that forensic accounting can bridge the gap between conventional accounting and auditing, this profession has not been able to gain the needed momentum due to some hassles. This paper tries to shed light on the theoretical concept, nature, practice, need, role of forensic accounting in preventing fraud, and the practical difficulties faced by forensic accountants. The study is based on information collected from interviewing practicing forensic accounting in India during 2011-12. The paper was able to assess the importance and rising scope of forensic accounting as a job. It also understood the practical difficulties they faced like lack of organized databases in Indian scenario which makes it difficult to access all needed information. Expectation level of the clients is very high and at times even unreasonable. This paper fulfills an identified need to study the important rising field of forensic accounting in India.
文摘Information security often involves the development and application of so</span><span style="font-family:Verdana;">phisticated software to protect sensitive information stored in corporate</span><span style="font-family:Verdana;"> computers. Yet, in this example of corporate espionage, a clever person, a cellphone and some readily available software were all it took to crack through one company’s advanced security barriers. By reading this article it is hoped that employees at all levels of an organization’s hierarchy will become more aware of—and recognize—how: 1) bits and pieces of seemingly harmless and easy-to-acquire information can be used for sinister purposes;2) building rapport and trust with a person can make them more likely to become unknowing co-conspirators in a devious undertaking;and 3) how one must be constantly alert not to give out information without carefully considering the authenticity and justification of the source requesting it.
基金This research is supported by National Key Research and Development Program of China(No.2021YFF0307203,No.2019QY1300)Youth Innovation Promotion Association CAS(No.2021156)+1 种基金the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDC02040100)National Natural Science Foundation of China(No.61802404)。
文摘Ethereum's high attention,rich business,certain anonymity,and untraceability have attracted a group of attackers.Cybercrime on it has become increasingly rampant,among which scam behavior is convenient,cryptic,antagonistic and resulting in large economic losses.So we consider the scam behavior on Ethereum and investigate it at the node interaction level.Based on the life cycle and risk identification points we found,we propose an automatic detection model named Aparecium.First,a graph generation method which focus on the scam life cycle is adopted to mitigate the sparsity of the scam behaviors.Second,the life cycle patterns are delicate modeled because of the crypticity and antagonism of Ethereum scam behaviors.Conducting experiments in the wild Ethereum datasets,we prove Aparecium is effective which the precision,recall and F1-score achieve at 0.977,0.957 and 0.967 respectively.
基金the project(sanction order no.1/2021-22(GIA))funded by the National Informatics Centre,MeitY,Government of India.
文摘The recent surge of Ethereum in prominence has made it an attractive target for various kinds of crypto crimes.Phishing scams,for example,are an increasingly prevalent cybercrime in which malicious users attempt to steal funds from a user’s crypto wallet.This research investigates the effects of network architectural features as well as the temporal aspects of user activities on the performance of detecting phishing users on the Ethereum transaction network.We employ traditional machine learning algorithms to evaluate our model on real-world Ethereum transaction data.The experimental results demonstrate that our proposed features identify phishing accounts efficiently and outperform the baseline models by 4%in Recall and 5%in F1-score.
基金This work was supported in part by Canada's Natural Sciences and Engineering Research Council(grant number“CRDPJ 539938-19”)and IBM Centre for Advanced Studies(CAS)Canada(grant number“1059”).
文摘The“Bitcoin Generator Scam”(BGS)is a cyberattack in which scammers promise to provide victims with free cryptocurrencies in exchange for a small mining fee.In this paper,we present a data-driven system to detect,track,and analyze the BGS.It works as follows:we first formulate search queries related to BGS and use search engines to find potential instances of the scam.We then use a crawler to access these pages and a classifier to differentiate actual scam instances from benign pages.Last,we automatically monitor the BGS instances to extract the cryptocurrency addresses used in the scam.A unique feature of our system is that it proactively searches for and detects the scam pages.Thus,we can find addresses that have not yet received any transactions.Our data collection project spanned 16 months,from November 2019 to February 2021.We uncovered more than 8,000 cryptocurrency addresses directly associated with the scam,hosted on over 1,000 domains.Overall,these addresses have received around 8.7 million USD,with an average of 49.24 USD per transaction.Over 70%of the active addresses that we are capturing are detected before they receive any transactions,that is,before anyone is victimized.We also present some post-processing analysis of the dataset that we have captured to aggregate attacks that can be reasonably confidently linked to the same attacker or group.Our system is one of the first academic feeds to the APWG eCrime Exchange database.It has been actively and automatically feeding the database since November 2020.
文摘On June 19,2017,the Shenzhen Intermediate People's Court opened its second hearing on Liu Qjanzhen,an unemployed 57-year-old villager from Jiangsu province--or,as his victim Zheng Xueju knew him,the "Qjanlong Emperor," the still-surviving inheritor of multiple Qjng family fortunes and sound investment opportunity.
