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1 |
A semi-automated forensic investigation model for online social networks
یک مدل تحقیقات پزشکی قانونی نیمه خودکار برای شبکه های اجتماعی آنلاین-2020 Investigating the online social network profiles of victims, suspects, and witnesses are now part of al- most every legal investigation, either it involves a criminal offense, financial fraud, or domestic lawsuit. However, investigating online social networks (OSN) is a technically complicated process that becomes more challenging due to the legal issues of privacy and authentication. Completely manual investigative methods are not feasible for OSN investigations due to the immense size and heterogeneity of social net- works. However, the existing models for digital forensic investigation are not supporting automated or semi-automated forensic investigation processes. Furthermore, they are not addressing the fundamental differences and specific requirements of online social networks. The model presented in this work incor- porates the robust features of standard investigation models and proposes a digital forensic investigation process model that explicitly addresses the necessities of OSN investigations. This work is addressing the issues of automating the forensic collection and analysis processes, defining crime scene boundaries, and outlining reasonable iterative collection procedures in online social network forensic investigation. This work is evaluated using a case study and is compared with existing practices and standards. Keywords: Forensic investigation model | Online social networks | Formal theory | Automated forensic processes | Forensic collection | Iterative process model |
مقاله انگلیسی |
2 |
Socioscope: I know who you are, a robo, human caller or service number
جامعه شناسی: من می دانم شما چه کسی هستید ، یک روبو ، تماس گیرنده انسانی یا شماره خدمات-2020 Telephony technologies (mobile, VoIP, and fixed) have potentially improved the way we communicate
in our daily life and have been widely adopted for business and personal communications. At the
same time, scammers, criminals, and fraudsters have also find the telephony network an attractive
and affordable medium to target end-users with the advertisement, marketing of legal and illegal
products, and bombard them with the huge volume of unwanted calls. These calls would not only
trick call recipients into disclosing their private information such as credit card numbers, PIN code
which can be used for financial fraud but also causes a lot of displeasure because of continuous ringing.
The fraudsters, political campaigners can also use telephony systems to spread malicious information
(hate political or religious messages) in real-time through audio or text messages, which have serious
political and social consequences if malicious callers are not mitigated in a quick time. In this context,
the identification of malicious callers would not only minimize telephony fraud but would also bring
peace to the lives of individuals. One way to classifies users as a spammer or legitimate is to get
feedback from the call recipients about their recent interactions with the caller, but these systems
not only bring inconvenience to callees but also require changes in the system design. The call detail
records extensively log the activities of users and can be used to categorize them as the spammer and
non-spammer. In this paper, we utilize the information from the call detailed records and proposed a
spam detection framework for the telephone network that identifies malicious callers by utilizing the
social behavioral features of users within the network. To this extent, we first model the behavior of
the users as the directed social graph and then analyze different features of the social graph i.e. the
Relationship Network and Call patterns of users towards their peers. We then used these features along
with the decision tree to classify callers into three classes i.e. human, spammer and call center. We
analyzed the call record data-set consisting of more than 2 million users. We have conducted a detailed
evaluation of our framework which demonstrates its effectiveness by achieving acceptable detection
accuracy and extremely low false-positive rate. The performance results show that the spammers and
call center numbers not only have a large number of non-repetitive calls but also have a large number
of short duration calls. Similarly, on the other hand, the legitimate callers have a good number of
repetitive calls and most of them interacted for a relatively long duration. Keywords: Social network analysis | Telephone spam detection | Robocalls | Telephone call records | Telemarketers | User characterization |
مقاله انگلیسی |
3 |
Big data techniques in auditing research and practice: Current trends and future opportunities
تکنیک های داده های بزرگ در حسابرسی تحقیق و عمل: روند فعلی و فرصت های آینده-2018 This paper analyses the use of big data techniques in auditing, and finds that the practice is not as
widespread as it is in other related fields. We first introduce contemporary big data techniques to
promote understanding of their potential application. Next, we review existing research on big
data in accounting and finance. In addition to auditing, our analysis shows that existing research
extends across three other genealogies: financial distress modelling, financial fraud modelling,
and stock market prediction and quantitative modelling. Auditing is lagging behind the other
research streams in the use of valuable big data techniques. A possible explanation is that au
ditors are reluctant to use techniques that are far ahead of those adopted by their clients, but we
refute this argument. We call for more research and a greater alignment to practice. We also
outline future opportunities for auditing in the context of real-time information and in colla
borative platforms and peer-to-peer marketplaces.
Keywords: Auditing ، Big data ، Data analytics ، Statistical techniques |
مقاله انگلیسی |
4 |
Managerial myopia and the mortgage meltdown
نزدیک بینی مدیریتی و گداختگی رهنی-2018 Prominent policy makers assert that managerial short-termism was at the root of the subprime crisis of 2007–2009. Prior scholarly research, however, largely rejects this assertion. Using a more comprehensive measure of Chief Executive Officer (CEO) incentives for short-termism, we uncover evidence that short-termism indeed played a role. Firms whose CEOs were contractually allowed to sell or exercise more of their stock and options holdings sooner had more subprime exposure, a higher probability of financial distress, and lower risk-adjusted stock returns during the crisis, as well as higher fines and settlements for subprime-related fraud.
keywords: Financial crisis |Subprime mortgages |Financial fraud |CEO incentives |CEO pay |
مقاله انگلیسی |
5 |
Intelligent financial fraud detection: A comprehensive review
تشخیص تقلب مالی هوشمند: مرور جامع-2016 Financial fraud is an issue with far reaching consequences in the finance industry, government, corporate sectors, and for ordinary consumers. Increasing dependence on new
technologies such as cloud and mobile computing in recent years has compounded the
problem. Traditional methods involving manual detection are not only time consuming, expensive and inaccurate, but in the age of big data they are also impractical. Not surprisingly,
financial institutions have turned to automated processes using statistical and computational methods. This paper presents a comprehensive review of financial fraud detection
research using such data mining methods, with a particular focus on computational intelligence (CI)-based techniques. Over fifty scientific literature, primarily spanning the period
2004–2014, were analysed in this study; literature that reported empirical studies focussing specifically on CI-based financial fraud detection were considered in particular. Research
gap was identified as none of the existing review articles addresses the association among
fraud types, CI-based detection algorithms and their performance, as reported in the literature. We have presented a comprehensive classification as well as analysis of existing
fraud detection literature based on key aspects such as detection algorithm used, fraud type
investigated, and performance of the detection methods for specific financial fraud types.
Some of the key issues and challenges associated with the current practices and potential
future direction of research have also been identified.
Keywords: Financial fraud detection | Computational intelligence | Data mining Anomaly detection | Classification |
مقاله انگلیسی |
6 |
تشخیص تقلب مالی هوشمند : مرور جامع
سال انتشار: 2016 - تعداد صفحات فایل pdf انگلیسی: 20 - تعداد صفحات فایل doc فارسی: 44 کلاهبرداری مالی مسالهای است که در صنعت مالی ، دولت ، بخشهای شرکت و برای مصرف کنندگان عادی به پیامدهای بسیار گسترده ای رسیدهاست . افزایش وابستگی به فنآوریهای جدید از قبیل رایانش ابری و محاسبات همراه در سالهای اخیر ، روشهای مربوط به تشخیص دستی را پیچیدهتر کرده و نه تنها زمان گیر ، گرانقیمت و نادرست است ، بلکه در عصر دادههای بزرگ نیز غیرعملی است . تعجبی ندارد که موسسات مالی با استفاده از روشهای آماری و محاسباتی به فرآیندهای خودکار تبدیل شدهاند . این مقاله یک بررسی جامع از تحقیقات ردیابی کلاهبرداری مالی با استفاده از چنین روشهای داده کاوی ، با تمرکز ویژه بر تکنیکهای مبتنی بر هوش محاسباتیCI نشان میدهد . بیش از پنجاه ادبیات علمی که در درجه اول از سالهای ۲۰۰۴ تا ۲۰۱۴ انجام شد ، در این مطالعه تحلیل شدند ؛ ادبیاتی که مطالعات تجربی را گزارش کردند ، به طور خاص بر تشخیص تقلب مالی مبتنی بر CI تمرکز داشتند . همانطور که در مقالات گزارش شد ، یک شکاف تحقیقاتی شناسایی شد به طوری که هیچ یک از مقالات بررسی موجود ارتباط بین انواع کلاهبرداری ، الگوریتم تشخیص مبتنی بر هوش رقابتی و عملکرد آنها را مورد خطاب قرار نمیدهند . ما یک طبقهبندی جامع و همچنین تجزیه و تحلیل مقالات کشف تقلب موجود بر مبنای جنبههای کلیدی مانند الگوریتم تشخیص بکار گرفتهشده ، نوع کلاهبرداری ، و عملکرد روشهای تشخیص انواع تقلب مالی خاص را ارائه کردهایم . برخی از موضوعات کلیدی و چالشهای مربوط به شیوههای کنونی و مسیر بالقوه آینده تحقیق نیز شناسایی شدهاند .
واژه های کلیدی: تشخیص تقلب مالی | هوش محاسباتی | داده کاوی | تشخیص ناهنجاری | طبقهبندی |
مقاله ترجمه شده |
7 |
A Copayment Auditing Scheme for Financial Misreporting
یک طرح حسابرسی مشترک انجام برای گزارشدهی نادرست مالی-2015 This paper proposes a copayment scheme to prevent collusion in auditing contracts, offering as a
solution to financial misreporting. In the copayment scheme, both the client firm and a third party,
such as PCAOB, are asked to share the auditing fee. The key feature of the copayment scheme is that
the third party's expenses should be funded by the client firm. We demonstrate that the participation
of a third party can create an endogenous collusion cost to the client firm, to such an extent that in the
equilibrium, the client firm will not make any offer of bribery. Most importantly, the total equilibrium
auditing fee is the same as in the bribery-free contract. This result makes an important contribution to
the literature in addressing the issues of financial frauds and collusion between the auditor and the
client firm within a principal-agent model.
Keywords: Financial misreport; Auditing contract; Bribery |
مقاله انگلیسی |