11,392 research outputs found
It's more than just money: The real-world harms from ransomware attacks
As cyber-attacks continue to increase in frequency and sophistication,
organisations must be better prepared to face the reality of an incident. Any
organisational plan that intends to be successful at managing security risks
must clearly understand the harm (i.e., negative impact) and the various
parties affected in the aftermath of an attack. To this end, this article
conducts a novel exploration into the multitude of real-world harms that can
arise from cyber-attacks, with a particular focus on ransomware incidents given
their current prominence. This exploration also leads to the proposal of a new,
robust methodology for modelling harms from such incidents. We draw on
publicly-available case data on high-profile ransomware incidents to examine
the types of harm that emerge at various stages after a ransomware attack and
how harms (e.g., an offline enterprise server) may trigger other negative,
potentially more substantial impacts for stakeholders (e.g., the inability for
a customer to access their social welfare benefits or bank account). Prominent
findings from our analysis include the identification of a notable set of
social/human harms beyond the business itself (and beyond the financial payment
of a ransom) and a complex web of harms that emerge after attacks regardless of
the industry sector. We also observed that deciphering the full extent and
sequence of harms can be a challenging undertaking because of the lack of
complete data available. This paper consequently argues for more transparency
on ransomware harms, as it would lead to a better understanding of the
realities of these incidents to the benefit of organisations and society more
generally.Comment: 17th International Symposium on Human Aspects of Information Security
& Assurance (HAISA 2023
Challenges in the Design and Implementation of IoT Testbeds in Smart-Cities : A Systematic Review
Advancements in wireless communication and the increased accessibility to low-cost sensing and data processing IoT technologies have increased the research and development of urban monitoring systems. Most smart city research projects rely on deploying proprietary IoT testbeds for indoor and outdoor data collection. Such testbeds typically rely on a three-tier architecture composed of the Endpoint, the Edge, and the Cloud. Managing the system's operation whilst considering the security and privacy challenges that emerge, such as data privacy controls, network security, and security updates on the devices, is challenging. This work presents a systematic study of the challenges of developing, deploying and managing urban monitoring testbeds, as experienced in a series of urban monitoring research projects, followed by an analysis of the relevant literature. By identifying the challenges in the various projects and organising them under the V-model development lifecycle levels, we provide a reference guide for future projects. Understanding the challenges early on will facilitate current and future smart-cities IoT research projects to reduce implementation time and deliver secure and resilient testbeds
Evaluation Methodologies in Software Protection Research
Man-at-the-end (MATE) attackers have full control over the system on which
the attacked software runs, and try to break the confidentiality or integrity
of assets embedded in the software. Both companies and malware authors want to
prevent such attacks. This has driven an arms race between attackers and
defenders, resulting in a plethora of different protection and analysis
methods. However, it remains difficult to measure the strength of protections
because MATE attackers can reach their goals in many different ways and a
universally accepted evaluation methodology does not exist. This survey
systematically reviews the evaluation methodologies of papers on obfuscation, a
major class of protections against MATE attacks. For 572 papers, we collected
113 aspects of their evaluation methodologies, ranging from sample set types
and sizes, over sample treatment, to performed measurements. We provide
detailed insights into how the academic state of the art evaluates both the
protections and analyses thereon. In summary, there is a clear need for better
evaluation methodologies. We identify nine challenges for software protection
evaluations, which represent threats to the validity, reproducibility, and
interpretation of research results in the context of MATE attacks
Eunomia: Enabling User-specified Fine-Grained Search in Symbolically Executing WebAssembly Binaries
Although existing techniques have proposed automated approaches to alleviate
the path explosion problem of symbolic execution, users still need to optimize
symbolic execution by applying various searching strategies carefully. As
existing approaches mainly support only coarse-grained global searching
strategies, they cannot efficiently traverse through complex code structures.
In this paper, we propose Eunomia, a symbolic execution technique that allows
users to specify local domain knowledge to enable fine-grained search. In
Eunomia, we design an expressive DSL, Aes, that lets users precisely pinpoint
local searching strategies to different parts of the target program. To further
optimize local searching strategies, we design an interval-based algorithm that
automatically isolates the context of variables for different local searching
strategies, avoiding conflicts between local searching strategies for the same
variable. We implement Eunomia as a symbolic execution platform targeting
WebAssembly, which enables us to analyze applications written in various
languages (like C and Go) but can be compiled into WebAssembly. To the best of
our knowledge, Eunomia is the first symbolic execution engine that supports the
full features of the WebAssembly runtime. We evaluate Eunomia with a dedicated
microbenchmark suite for symbolic execution and six real-world applications.
Our evaluation shows that Eunomia accelerates bug detection in real-world
applications by up to three orders of magnitude. According to the results of a
comprehensive user study, users can significantly improve the efficiency and
effectiveness of symbolic execution by writing a simple and intuitive Aes
script. Besides verifying six known real-world bugs, Eunomia also detected two
new zero-day bugs in a popular open-source project, Collections-C.Comment: Accepted by ACM SIGSOFT International Symposium on Software Testing
and Analysis (ISSTA) 202
EFFECTIVE PATCH MANAGEMENT AND GOVERNMENT SYSTEMS
This thesis establishes the importance of patch management and its role in the reduction of exploitable vulnerabilities and the increased security of government information systems (IS). As technology continues to evolve, cybersecurity has become a leading concern. The vast increase in computer usage and technological advancements have provided many benefits to organizations in both the private and public sectors. The need to protect ISs against cyber-attacks has grown at the same rate. Cybersecurity is not a new concept but its applicability continues to be a problematic concept or hindrance to incorporate into both legacy and new ISs across government and private entities. Government ISs tend to be more susceptible to cyber-attacks. Resiliency at the conception of an IS is imperative and maintaining that resiliency is key to sustaining the security posture of any IS. The primary goal of government ISs is to provide new capabilities and resources to the warfighter. New ISs rely heavily on the use of software and its ability to be upgraded or modified. Legacy systems often utilize outdated software. Both types of systems require maintenance throughout the lifecycle. Many government ISs operate out-of-date software versions or are not patched on a routine basis to ensure ISs are not exposed to vulnerabilities. Patch management is an important practice that can prevent the exposure to cyber-attacks the exploitation of known vulnerabilities and improve the cyber hygiene of ISs.Civilian, Department of the NavyCivilian, Department of the NavyApproved for public release. Distribution is unlimited
CAMEL: Communicative Agents for "Mind" Exploration of Large Scale Language Model Society
The rapid advancement of conversational and chat-based language models has
led to remarkable progress in complex task-solving. However, their success
heavily relies on human input to guide the conversation, which can be
challenging and time-consuming. This paper explores the potential of building
scalable techniques to facilitate autonomous cooperation among communicative
agents and provide insight into their "cognitive" processes. To address the
challenges of achieving autonomous cooperation, we propose a novel
communicative agent framework named role-playing. Our approach involves using
inception prompting to guide chat agents toward task completion while
maintaining consistency with human intentions. We showcase how role-playing can
be used to generate conversational data for studying the behaviors and
capabilities of chat agents, providing a valuable resource for investigating
conversational language models. Our contributions include introducing a novel
communicative agent framework, offering a scalable approach for studying the
cooperative behaviors and capabilities of multi-agent systems, and
open-sourcing our library to support research on communicative agents and
beyond. The GitHub repository of this project is made publicly available on:
https://github.com/lightaime/camel
Detecting Anomalous Microflows in IoT Volumetric Attacks via Dynamic Monitoring of MUD Activity
IoT networks are increasingly becoming target of sophisticated new
cyber-attacks. Anomaly-based detection methods are promising in finding new
attacks, but there are certain practical challenges like false-positive alarms,
hard to explain, and difficult to scale cost-effectively. The IETF recent
standard called Manufacturer Usage Description (MUD) seems promising to limit
the attack surface on IoT devices by formally specifying their intended network
behavior. In this paper, we use SDN to enforce and monitor the expected
behaviors of each IoT device, and train one-class classifier models to detect
volumetric attacks.
Our specific contributions are fourfold. (1) We develop a multi-level
inferencing model to dynamically detect anomalous patterns in network activity
of MUD-compliant traffic flows via SDN telemetry, followed by packet inspection
of anomalous flows. This provides enhanced fine-grained visibility into
distributed and direct attacks, allowing us to precisely isolate volumetric
attacks with microflow (5-tuple) resolution. (2) We collect traffic traces
(benign and a variety of volumetric attacks) from network behavior of IoT
devices in our lab, generate labeled datasets, and make them available to the
public. (3) We prototype a full working system (modules are released as
open-source), demonstrates its efficacy in detecting volumetric attacks on
several consumer IoT devices with high accuracy while maintaining low false
positives, and provides insights into cost and performance of our system. (4)
We demonstrate how our models scale in environments with a large number of
connected IoTs (with datasets collected from a network of IP cameras in our
university campus) by considering various training strategies (per device unit
versus per device type), and balancing the accuracy of prediction against the
cost of models in terms of size and training time.Comment: 18 pages, 13 figure
Blockchain Technology: Disruptor or Enhnancer to the Accounting and Auditing Profession
The unique features of blockchain technology (BCT) - peer-to-peer network, distribution ledger, consensus decision-making, transparency, immutability, auditability, and cryptographic security - coupled with the success enjoyed by Bitcoin and other cryptocurrencies have encouraged many to assume that the technology would revolutionise virtually all aspects of business. A growing body of scholarship suggests that BCT would disrupt the accounting and auditing fields by changing accounting practices, disintermediating auditors, and eliminating financial fraud. BCT disrupts audits (Lombard et al.,2021), reduces the role of audit firms (Yermack 2017), undermines accountants' roles with software developers and miners (Fortin & Pimentel 2022); eliminates many management functions, transforms businesses (Tapscott & Tapscott, 2017), facilitates a triple-entry accounting system (Cai, 2021), and prevents fraudulent transactions (Dai, et al., 2017; Rakshit et al., 2022). Despite these speculations, scholars have acknowledged that the application of BCT in the accounting and assurance industry is underexplored and many existing studies are said to lack engagement with practitioners (Dai & Vasarhelyi, 2017; Lombardi et al., 2021; Schmitz & Leoni, 2019).
This study empirically explored whether BCT disrupts or enhances accounting and auditing fields. It also explored the relevance of audit in a BCT environment and the effectiveness of the BCT mechanism for fraud prevention and detection. The study further examined which technical skillsets accountants and auditors require in a BCT environment, and explored the incentives, barriers, and unintended consequences of the adoption of BCT in the accounting and auditing professions. The current COVID-19 environment was also investigated in terms of whether the pandemic has improved BCT adoption or not.
A qualitative exploratory study used semi-structured interviews to engage practitioners from blockchain start-ups, IT experts, financial analysts, accountants, auditors, academics, organisational leaders, consultants, and editors who understood the technology. With the aid of NVIVO qualitative analysis software, the views of 44 participants from 13 countries: New Zealand, Australia, United States, United Kingdom, Canada, Germany, Italy, Ireland, Hong Kong, India, Pakistan, United Arab Emirates, and South Africa were analysed.
The Technological, Organisational, and Environmental (TOE) framework with consequences of innovation context was adopted for this study. This expanded TOE framework was used as the theoretical lens to understand the disruption of BCT and its adoption in the accounting and auditing fields. Four clear patterns emerged. First, BCT is an emerging tool that accountants and auditors use mainly to analyse financial records because technology cannot disintermediate auditors from the financial system. Second, the technology can detect anomalies but cannot prevent financial fraud. Third, BCT has not been adopted by any organisation for financial reporting and accounting purposes, and accountants and auditors do not require new skillsets or an understanding of the BCT programming language to be able to operate in a BCT domain. Fourth, the advent of COVID-19 has not substantially enhanced the adoption of BCT. Additionally, this study highlights the incentives, barriers, and unintended consequences of adopting BCT as financial technology (FinTech). These findings shed light on important questions about BCT disrupting and disintermediating auditors, the extent of adoption in the accounting industry, preventing fraud and anomalies, and underscores the notion that blockchain, as an emerging technology, currently does not appear to be substantially disrupting the accounting and auditing profession.
This study makes methodological, theoretical, and practical contributions. At the methodological level, the study adopted the social constructivist-interpretivism paradigm with an exploratory qualitative method to engage and understand BCT as a disruptive innovation in the accounting industry. The engagement with practitioners from diverse fields, professions, and different countries provides a distinctive and innovative contribution to methodological and practical knowledge. At the theoretical level, the findings contribute to the literature by offering an integrated conceptual TOE framework. The framework offers a reference for practitioners, academics and policymakers seeking to appraise comprehensive factors influencing BCT adoption and its likely unintended consequences. The findings suggest that, at present, no organisations are using BCT for financial reporting and accounting systems. This study contributes to practice by highlighting the differences between initial expectations and practical applications of what BCT can do in the accounting and auditing fields. The study could not find any empirical evidence that BCT will disrupt audits, eliminate the roles of auditors in a financial system, and prevent and detect financial fraud. Also, there was no significant evidence that accountants and auditors required higher-level skillsets and an understanding of BCT programming language to be able to use the technology. Future research should consider the implications of an external audit firm as a node in a BCT network on the internal audit functions. It is equally important to critically examine the relevance of including programming languages or codes in the curriculum of undergraduate accounting students. Future research could also empirically evaluate if a BCT-enabled triple-entry system could prevent financial statements and management fraud
- …