Biblio

Distributed banking platforms and services forgo centralized banks to process financial transactions. For example, M-Pesa provides distributed banking service in the developing regions so that the people without a bank account can deposit, withdraw, or transfer money. The current distributed banking systems lack the transparency in monitoring and tracking of distributed banking transactions and thus do not support auditing of distributed banking transactions for accountability. To address this issue, this paper proposes a blockchain-based distributed banking (BDB) scheme, which uses blockchain technology to leverage its built-in properties to record and track immutable transactions. BDB supports distributed financial transaction processing but is significantly different from cryptocurrencies in its design properties, simplicity, and computational efficiency. We implement a prototype of BDB using smart contract and conduct experiments to show BDB's effectiveness and performance. We further compare our prototype with the Ethereum cryptocurrency to highlight the fundamental differences and demonstrate the BDB's superior computational efficiency.

Attacks on cloud-computing services are becoming more prevalent with recent victims including Tesla, Aviva Insurance and SIM-card manufacturer Gemalto[1]. The risk posed to organisations from malicious insiders is becoming more widely known about and consequently many are now investing in hardware, software and new processes to try to detect these attacks. As for all types of attack vector, there will always be those which are not known about and those which are known about but remain exceptionally difficult to detect - particularly in a timely manner. We believe that insider attacks are of particular concern in a cloud-computing environment, and that cloud-service providers should enhance their ability to detect them by means of indirect detection. We propose a combined attack-tree and kill-chain based method for identifying multiple indirect detection measures. Specifically, the use of attack trees enables us to encapsulate all detection opportunities for insider attacks in cloud-service environments. Overlaying the attack tree on top of a kill chain in turn facilitates indirect detection opportunities higher-up the tree as well as allowing the provider to determine how far an attack has progressed once suspicious activity is detected. We demonstrate the method through consideration of a specific type of insider attack - that of attempting to capture virtual machines in transit within a cloud cluster via use of a network tap, however, the process discussed here applies equally to all cloud paradigms.

People increasingly rely on mobile devices for banking transactions or two-factor authentication (2FA) and thus trust in the security provided by the underlying operating system. Simultaneously, jailbreaks gain tremendous popularity among regular users for customizing their devices. In this paper, we show that both do not go well together: Jailbreaks remove vital security mechanisms, which are necessary to ensure a trusted environment that allows to protect sensitive data, such as login credentials and transaction numbers (TANs). We find that all but one banking app, available in the iOS App Store, can be fully compromised by trivial means without reverse-engineering, manipulating the app, or other sophisticated attacks. Even worse, 44% of the banking apps do not even try to detect jailbreaks, revealing the prevalent, errant trust in the operating system's security. This study assesses the current state of security of banking apps and pleads for more advanced defensive measures for protecting user data.

Outsourcing services to cloud server (CS) becomes popular in these years. However, the outsourced services often involve with sensitive activity and CS naturally becomes a target of varieties of attacks. Even worse, CS itself can misuse the outsourced services for illegal profit. Traditional online banking system also can make use of a cloud framework to provide economical and high-speed online services to the consumers, which makes the financial dealing easy and convenient. Most of the banking organizations provide services through passbook, ATM, mobile banking, electronic banking (e-banking) etc. Among these, the e-banking and mobile banking are more convenient and becomes essential. Therefore, it is critical to provide an efficient, reliable and more importantly, secure e-banking services to the consumers. The cloud environment is suitable paradigm to a new, small and medium scale banking organization as it eliminates the requirement for them to start with small resources and increase gradually as the service demand rises. However, security is one of the main concerns since it deals with many sensitive data of the valuable customers. In addition to this, the access of various data needs to be restricted to prevent any unauthorized transaction. Nagaraju et al. presented a framework to achieve reliability and security in public cloud based online banking using multi-factor authentication concept. Unfortunately, the login and authentication protocol of this framework is prone to impersonation attack. In this paper, we have revised the framework to avoid this attack.

Emergence of Information and Communication Technology (ICT) has facilitated its users to access electronic services through open channel like Internet. This approach of digital communication has its specific security lapses, which should be addressed properly to ensure Privacy, Integrity, Non-repudiation and Authentication (PINA) of information. During message communication, intruders may mount infringement attempts to compromise the communication. The situation becomes critical, if an user is identified by multiple identification numbers, as in that case, intruder have a wide window open to use any of its identification number to fulfill its ill intentions. To resolve this issue, author have proposed a single window based cloud service delivery model, where a smart card serves as a single interface to access multifaceted electronic services like banking, healthcare, employment, etc. To detect and prevent unauthorized access, in this paper, authors have focused on the intrusion detection system of the cloud service model during cloud banking transaction.

Forced by regulations and industry demand, banks worldwide are working to open their customers' online banking accounts to third-party services via web-based APIs. By using these so-called Open Banking APIs, third-party companies, such as FinTechs, are able to read information about and initiate payments from their users' bank accounts. Such access to financial data and resources needs to meet particularly high security requirements to protect customers. One of the most promising standards in this segment is the OpenID Financial-grade API (FAPI), currently under development in an open process by the OpenID Foundation and backed by large industry partners. The FAPI is a profile of OAuth 2.0 designed for high-risk scenarios and aiming to be secure against very strong attackers. To achieve this level of security, the FAPI employs a range of mechanisms that have been developed to harden OAuth 2.0, such as Code and Token Binding (including mTLS and OAUTB), JWS Client Assertions, and Proof Key for Code Exchange. In this paper, we perform a rigorous, systematic formal analysis of the security of the FAPI, based on an existing comprehensive model of the web infrastructure - the Web Infrastructure Model (WIM) proposed by Fett, Küsters, and Schmitz. To this end, we first develop a precise model of the FAPI in the WIM, including different profiles for read-only and read-write access, different flows, different types of clients, and different combinations of security features, capturing the complex interactions in a web-based environment. We then use our model of the FAPI to precisely define central security properties. In an attempt to prove these properties, we uncover partly severe attacks, breaking authentication, authorization, and session integrity properties. We develop mitigations against these attacks and finally are able to formally prove the security of a fixed version of the FAPI. Although financial applications are high-stakes environments, this work is the first to formally analyze and, importantly, verify an Open Banking security profile. By itself, this analysis is an important contribution to the development of the FAPI since it helps to define exact security properties and attacker models, and to avoid severe security risks before the first implementations of the standard go live. Of independent interest, we also uncover weaknesses in the aforementioned security mechanisms for hardening OAuth 2.0. We illustrate that these mechanisms do not necessarily achieve the security properties they have been designed for.

Surveillance is the monitoring of the behavior, activities or other changing information whereas security means the state of being protected from harmful activities. Nowadays proper surveillance security is considered as a challenging issue in the world and security has become a major concern from real life to virtual life. Tech-giants are implementing new solutions & techniques for better security assessment. This paper illustrates the design and implementation of a Belief Rule Based Expert System (BRBES) to overcome the uncertainty problems during bank security assessment. The proposed expert system has been developed based on generic Belief Rule Based (BRB) inference methodology using Evidential Reasoning algorithm (RIMER). Real-time security data has been taken from several banks of Bangladesh in conjunction with the expert's opinion to construct the knowledge base. This expert system provides more reliable and effective result under uncertainties which is better than any other traditional expert's prediction. Real life case studies were used for the validation of this system. Also, the outcome is compared with the real-life security system. Furthermore, the architectural design, implementation and utilization of an expert system to assess bank security under uncertainty are also discussed in this paper.

The main objective of this research work is to enhance the data storage capacity of the QR codes. By achieving the research aim, we can visualize rapid increase in application domains of QR Codes, mostly for smart cities where one needs to store bulk amount of data. Nowadays India is experiencing demonetization step taken by Prime Minister of the country and QR codes can play major role for this step. They are also helpful for cashless society as many vendors have registered themselves with different e-wallet companies like paytm, freecharge etc. These e-wallet companies have installed QR codes at cash counter of such vendors. Any time when a customer wants to pay his bills, he only needs to scan that particular QR code. Afterwards the QR code decoder application start working by taking necessary action like opening payment gateway etc. So, objective of this research study focuses on solving this issue by applying proposed methodology.