Biblio

The PyPI ecosystem has indexed millions of Python libraries to allow developers to automatically download and install dependencies of their projects based on the specified version constraints. Despite the convenience brought by automation, version constraints in Python projects can easily conflict, resulting in build failures. We refer to such conflicts as Dependency Conflict (DC) issues. Although DC issues are common in Python projects, developers lack tool support to gain a comprehensive knowledge for diagnosing the root causes of these issues. In this paper, we conducted an empirical study on 235 real-world DC issues. We studied the manifestation patterns and fixing strategies of these issues and found several key factors that can lead to DC issues and their regressions. Based on our findings, we designed and implemented Watchman, a technique to continuously monitor dependency conflicts for the PyPI ecosystem. In our evaluation, Watchman analyzed PyPI snapshots between 11 Jul 2019 and 16 Aug 2019, and found 117 potential DC issues. We reported these issues to the developers of the corresponding projects. So far, 63 issues have been confirmed, 38 of which have been quickly fixed by applying our suggested patches.

The inforrmation age continues to transform the mechanics of integrating electric power devices and systems, from coordinated operations based purely on the physics of electric power engineering to an increasing blend of power with information and communication technology. Integrating electric system components is not just about attaching wires. It requires the connection of computer-based automation systems to associated sensing and communication equipment. The architectural impacts are significant. Well-considered and commonly held concepts, principles, and organizational structures continue to emerge to address the complexity of the integrated operational challenges that drive our society to expect more flexibility in configuring the electric power system, while simultaneously achieving greater efficiency, reliability, and resilience. Architectural concepts, such as modularity and composability, contribute to the creation of structures that enable the connection of power system equipment characterized by clearly defined interfaces consisting of physical and cyberlinks. The result of successful electric power system component connection is interoperation: the discipline that drives integration to be simple and reliable.

The online advertising ecosystem is built upon the massive data collection of ad networks to learn the properties of users for targeted ad deliveries. Existing efforts have investigated the privacy leakage behaviors of mobile ad networks. However, there lacks a large-scale measurement study to evaluate the scale of privacy leakage through mobile ads. In this work, we present a study of the potential privacy leakage in location-based mobile advertising services based on a large-scale measurement. We first introduce a threat model in the mobile ad ecosystem, and then design a measurement system to perform extensive threat measurements and assessments. To counteract the privacy leakage threats, we design and implement an adaptive location obfuscation mechanism, which can be used to obfuscate location data in real-time while minimizing the impact to mobile ad businesses.

The online advertising ecosystem is built upon the massive data collection of ad networks to learn the properties of users for targeted ad deliveries. Existing efforts have investigated the privacy leakage behaviors of mobile ad networks. However, there lacks a large-scale measurement study to evaluate the scale of privacy leakage through mobile ads. In this work, we present a study of the potential privacy leakage in location-based mobile advertising services based on a large-scale measurement. We first introduce a threat model in the mobile ad ecosystem, and then design a measurement system to perform extensive threat measurements and assessments. To counteract the privacy leakage threats, we design and implement an adaptive location obfuscation mechanism, which can be used to obfuscate location data in real-time while minimizing the impact to mobile ad businesses.

Certificate Transparency (CT) is an emerging system for enabling the rapid discovery of malicious or misissued certificates. Initially standardized in 2013, CT is now finally beginning to see widespread support. Although CT provides desirable security benefits, web browsers cannot begin requiring all websites to support CT at once, due to the risk of breaking large numbers of websites. We discuss challenges for deployment, analyze the adoption of CT on the web, and measure the error rates experienced by users of the Google Chrome web browser. We find that CT has so far been widely adopted with minimal breakage and warnings. Security researchers often struggle with the tradeoff between security and user frustration: rolling out new security requirements often causes breakage. We view CT as a case study for deploying ecosystem-wide change while trying to minimize end user impact. We discuss the design properties of CT that made its success possible, as well as draw lessons from its risks and pitfalls that could be avoided in future large-scale security deployments.

Phishing attacks have reached record volumes in recent years. Simultaneously, modern phishing websites are growing in sophistication by employing diverse cloaking techniques to avoid detection by security infrastructure. In this paper, we present PhishFarm: a scalable framework for methodically testing the resilience of anti-phishing entities and browser blacklists to attackers' evasion efforts. We use PhishFarm to deploy 2,380 live phishing sites (on new, unique, and previously-unseen .com domains) each using one of six different HTTP request filters based on real phishing kits. We reported subsets of these sites to 10 distinct anti-phishing entities and measured both the occurrence and timeliness of native blacklisting in major web browsers to gauge the effectiveness of protection ultimately extended to victim users and organizations. Our experiments revealed shortcomings in current infrastructure, which allows some phishing sites to go unnoticed by the security community while remaining accessible to victims. We found that simple cloaking techniques representative of real-world attacks- including those based on geolocation, device type, or JavaScript- were effective in reducing the likelihood of blacklisting by over 55% on average. We also discovered that blacklisting did not function as intended in popular mobile browsers (Chrome, Safari, and Firefox), which left users of these browsers particularly vulnerable to phishing attacks. Following disclosure of our findings, anti-phishing entities are now better able to detect and mitigate several cloaking techniques (including those that target mobile users), and blacklisting has also become more consistent between desktop and mobile platforms- but work remains to be done by anti-phishing entities to ensure users are adequately protected. Our PhishFarm framework is designed for continuous monitoring of the ecosystem and can be extended to test future state-of-the-art evasion techniques used by malicious websites.

SSL certificates are a core component of the public key infrastructure that underpins encrypted communication in the Internet. In this paper, we report the results of a longitudinal study of the characteristics of SSL certificate chains presented to clients during secure web (HTTPS) connection setup. Our data set consists of 23B SSL certificate chains collected from a global panel consisting of over 2M residential client machines over a period of 6 months. The data informing our analyses provide perspective on the entire chain of trust, including root certificates, across a wide distribution of client machines. We identify over 35M unique certificate chains with diverse relationships at all levels of the PKI hierarchy. We report on the characteristics of valid certificates, which make up 99.7% of the total corpus. We also examine invalid certificate chains, finding that 93% of them contain an untrusted root certificate and we find they have shorter average chain length than their valid counterparts. Finally, we examine two unintended but prevalent behaviors in our data: the deprecation of root certificates and secure traffic interception. Our results support aspects of prior, scan-based studies on certificate characteristics but contradict other findings, highlighting the importance of the residential client-side perspective.

Personally Identifiable Information (PII) is often used to perform authentication and acts as a gateway to personal and organizational information. One weak link in the architecture of identity management services is sufficient to cause exposure and risk identity. Recently, we have witnessed a shift in identity management solutions with the growth of blockchain. Blockchain-the decentralized ledger system-provides a unique answer addressing security and privacy with its embedded immutability. In a blockchain-based identity solution, the user is given the control of his/her identity by storing personal information on his/her device and having the choice of identity verification document used later to create blockchain attestations. Yet, the blockchain technology alone is not enough to produce a better identity solution. The user cannot make informed decisions as to which identity verification document to choose if he/she is not presented with tangible guidelines. In the absence of scientifically created practical guidelines, these solutions and the choices they offer may become overwhelming and even defeat the purpose of providing a more secure identity solution.We analyze different PII options given to users for authentication on current blockchain-based solutions. Based on our Identity Ecosystem model, we evaluate these options and their risk and liability of exposure. Powered by real world data of about 6,000 identity theft and fraud stories, our model recommends some authentication choices and discourages others. Our work paves the way for a truly effective identity solution based on blockchain by helping users make informed decisions and motivating blockchain identity solution providers to introduce better options to their users.

In past, several Certificate Authority (CA) compromise and subsequent mis-issue of certificate raise the importance of certificate transparency and dynamic trust management for certificates. Certificate Transparency (CT) provides transparency for issued certificates, thus enabling corrective measure for a mis-issued certificate by a CA. However, CT and existing mechanisms cannot convey the dynamic trust state for a certificate. To address this weakness, we propose Smart Contract-assisted PKI (SCP) - a smart contract based PKI extension - to manage dynamic trust network for PKI. SCP enables distributed trust in PKI, provides a protocol for managing dynamic trust, assures trust state of a certificate, and provides a better trust experience for end-users.

The Internet of Things (IoT) market is growing rapidly, allowing continuous evolution of new technologies. Alongside this development, most IoT devices are easy to compromise, as security is often not a prioritized characteristic. This paper proposes a novel IoT Security Model (IoTSM) that can be used by organizations to formulate and implement a strategy for developing end-to-end IoT security. IoTSM is grounded by the Software Assurance Maturity Model (SAMM) framework, however it expands it with new security practices and empirical data gathered from IoT practitioners. Moreover, we generalize the model into a conceptual framework. This approach allows the formal analysis for security in general and evaluates an organization's security practices. Overall, our proposed approach can help researchers, practitioners, and IoT organizations, to discourse about IoT security from an end-to-end perspective.

A popular form of software reuse is the use of open source software libraries hosted on centralized code repositories, such as Maven or npm. Developers only need to declare dependencies to external libraries, and automated tools make them available to the workspace of the project. Recent incidents, such as the Equifax data breach and the leftpad package removal, demonstrate the difficulty in assessing the severity, impact and spread of bugs in dependency networks. While dependency checkers are being adapted as a counter measure, they only provide indicative information. To remedy this situation, we propose a fine-grained dependency network that goes beyond packages and into call graphs. The result is a versioned ecosystem-level call graph. In this paper, we outline the process to construct the proposed graph and present a preliminary evaluation of a security issue from a core package to an affected client application.

Over the years cybercriminals have misused the Domain Name System (DNS) - a critical component of the Internet - to gain profit. Despite this persisting trend, little empirical information about the security of Top-Level Domains (TLDs) and of the overall 'health' of the DNS ecosystem exists. In this paper, we present security metrics for this ecosystem and measure the operational values of such metrics using three representative phishing and malware datasets. We benchmark entire TLDs against the rest of the market. We explicitly distinguish these metrics from the idea of measuring security performance, because the measured values are driven by multiple factors, not just by the performance of the particular market player. We consider two types of security metrics: occurrence of abuse and persistence of abuse. In conjunction, they provide a good understanding of the overall health of a TLD. We demonstrate that attackers abuse a variety of free services with good reputation, affecting not only the reputation of those services, but of entire TLDs. We find that, when normalized by size, old TLDs like .com host more bad content than new generic TLDs. We propose a statistical regression model to analyze how the different properties of TLD intermediaries relate to abuse counts. We find that next to TLD size, abuse is positively associated with domain pricing (i.e. registries who provide free domain registrations witness more abuse). Last but not least, we observe a negative relation between the DNSSEC deployment rate and the count of phishing domains.

Over the years cybercriminals have misused the Domain Name System (DNS) - a critical component of the Internet - to gain profit. Despite this persisting trend, little empirical information about the security of Top-Level Domains (TLDs) and of the overall 'health' of the DNS ecosystem exists. In this paper, we present security metrics for this ecosystem and measure the operational values of such metrics using three representative phishing and malware datasets. We benchmark entire TLDs against the rest of the market. We explicitly distinguish these metrics from the idea of measuring security performance, because the measured values are driven by multiple factors, not just by the performance of the particular market player. We consider two types of security metrics: occurrence of abuse and persistence of abuse. In conjunction, they provide a good understanding of the overall health of a TLD. We demonstrate that attackers abuse a variety of free services with good reputation, affecting not only the reputation of those services, but of entire TLDs. We find that, when normalized by size, old TLDs like .com host more bad content than new generic TLDs. We propose a statistical regression model to analyze how the different properties of TLD intermediaries relate to abuse counts. We find that next to TLD size, abuse is positively associated with domain pricing (i.e. registries who provide free domain registrations witness more abuse). Last but not least, we observe a negative relation between the DNSSEC deployment rate and the count of phishing domains.

Bitcoin, a peer-to-peer payment system and digital currency, is often involved in illicit activities such as scamming, ransomware attacks, illegal goods trading, and thievery. At the time of writing, the Bitcoin ecosystem has not yet been mapped and as such there is no estimate of the share of illicit activities. This paper provides the first estimation of the portion of cyber-criminal entities in the Bitcoin ecosystem. Our dataset consists of 854 observations categorised into 12 classes (out of which 5 are cybercrime-related) and a total of 100,000 uncategorised observations. The dataset was obtained from the data provider who applied three types of clustering of Bitcoin transactions to categorise entities: co-spend, intelligence-based, and behaviour-based. Thirteen supervised learning classifiers were then tested, of which four prevailed with a cross-validation accuracy of 77.38%, 76.47%, 78.46%, 80.76% respectively. From the top four classifiers, Bagging and Gradient Boosting classifiers were selected based on their weighted average and per class precision on the cybercrime-related categories. Both models were used to classify 100,000 uncategorised entities, showing that the share of cybercrime-related is 29.81% according to Bagging, and 10.95% according to Gradient Boosting with number of entities as the metric. With regard to the number of addresses and current coins held by this type of entities, the results are: 5.79% and 10.02% according to Bagging; and 3.16% and 1.45% according to Gradient Boosting.

In the past couple of years Cloud Computing has become an eminent part of the IT industry. As a result of its economic benefits more and more people are heading towards Cloud adoption. In present times there are numerous Cloud Service providers (CSP) allowing customers to host their applications and data onto Cloud. However Cloud Security continues to be the biggest obstacle in Cloud adoption and thereby prevents customers from accessing its services. Various techniques have been implemented by provides in order to mitigate risks pertaining to Cloud security. In this paper, we present a Hybrid Cryptographic System (HCS) that combines the benefits of both symmetric and asymmetric encryption thus resulting in a secure Cloud environment. The paper focuses on creating a secure Cloud ecosystem wherein we make use of multi-factor authentication along with multiple levels of hashing and encryption. The proposed system along with the algorithm are simulated using the CloudSim simulator. To this end, we illustrate the working of our proposed system along with the simulated results.

In contrast to electronic travel documents (e.g. ePassports), the standardisation of breeder documents (e.g. birth certificates), regarding harmonisation of content and contained security features is in statu nascendi. Due to the fact that breeder documents can be used as an evidence of identity and enable the application for electronic travel documents, they pose the weakest link in the identity life cycle and represent a security gap for identity management. In this work, we present a cost efficient way to enhance the long-term security of breeder documents by utilizing blockchain technology. A conceptual architecture to enhance breeder document long-term security and an introduction of the concept's constituting system components is presented. Our investigations provide evidence that the Bitcoin blockchain is most suitable for breeder document long-term security.

We introduce Active Dependency Mapping (ADM), a method for establishing dependency relations among a set of interdependent services. The approach is to artificially degrade network performance to infer which assets on the network support a particular process. Artificial degradation of the network environment could be transparent to users; run continuously it could identify dependencies that are rare or occur only at certain timescales. A useful byproduct of this dependency analysis is a quantitative assessment of the resilience and robustness of the system. This technique is intriguing for hardening both enterprise networks and cyber physical systems. We present a proof-of-concept experiment executed on a real-world set of interrelated software services. We assess the efficacy of the approach, discuss current limitations, and suggest options for future development of ADM.

All over the world, objects are increasingly connected in networks such as the Industrial Internet of Things. Interconnections, intercommunications and interactions are driving the development of an entirely new whole in the form of the Industrial Internet of Things. Communication and interaction are the norm both for separate components, such as cyber-physical systems, and for the functioning of the system as a whole. This new whole can be likened to a natural ecosystem where the process of homeostasis ensures the stability and security of the whole. Components of such an industrial ecosystem, or even an industrial ecosystem as a whole, are increasingly targeted by cyber attacks. Such attacks not only threaten the functioning of one or multiple components, they also constitute a threat to the functioning of the new whole. General systems theory can offer a scientific framework for the development of measures to improve the security and stability of both separate components and the new whole.

The QR codes have gained wide popularity in mobile marketing and advertising campaigns. However, the hidden security threat on the involved information system might endanger QR codes' success, and this issue has not been adequately addressed. In this paper we propose to examine the life cycle of a redesigned QR code ecosystem to identify the possible security risks. On top of this examination, we further propose standard changes to enhance security through a digital signature mechanism.