238 research outputs found

    On Deception-Based Protection Against Cryptographic Ransomware

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    In order to detect malicious file system activity, some commercial and academic anti-ransomware solutions implement deception-based techniques, specifically by placing decoy files among user files. While this approach raises the bar against current ransomware, as any access to a decoy file is a sign of malicious activity, the robustness of decoy strategies has not been formally analyzed and fully tested. In this paper, we analyze existing decoy strategies and discuss how they are effective in countering current ransomware by defining a set of metrics to measure their robustness. To demonstrate how ransomware can identify existing deception-based detection strategies, we have implemented a proof-of-concept anti-decoy ransomware that successfully bypasses decoys by using a decision engine with few rules. Finally, we discuss existing issues in decoy-based strategies and propose practical solutions to mitigate them

    DECEPTION BASED TECHNIQUES AGAINST RANSOMWARES: A SYSTEMATIC REVIEW

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    Ransomware is the most prevalent emerging business risk nowadays. It seriously affects business continuity and operations. According to Deloitte Cyber Security Landscape 2022, up to 4000 ransomware attacks occur daily, while the average number of days an organization takes to identify a breach is 191. Sophisticated cyber-attacks such as ransomware typically must go through multiple consecutive phases (initial foothold, network propagation, and action on objectives) before accomplishing its final objective. This study analyzed decoy-based solutions as an approach (detection, prevention, or mitigation) to overcome ransomware. A systematic literature review was conducted, in which the result has shown that deception-based techniques have given effective and significant performance against ransomware with minimal resources. It is also identified that contrary to general belief, deception techniques mainly involved in passive approaches (i.e., prevention, detection) possess other active capabilities such as ransomware traceback and obstruction (thwarting), file decryption, and decryption key recovery. Based on the literature review, several evaluation methods are also analyzed to measure the effectiveness of these deception-based techniques during the implementation process

    PayBreak: Defense against cryptographic ransomware

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    Dual-Use Research In Ransomware Attacks: A Discussion on Ransomware Defence Intelligence

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    Previous research has shown that developers rely on public platforms and repositories to produce functional but insecure code. We looked into the matter for ransomware, enquiring whether also ransomware engineers re-use the work of others and produce insecure code. By methodically reverse-engineering 128 malware executables, we have found that, out of 21 ransomware samples, 9 contain copy-paste code from public resources. Thanks to this finding, we managed to retrieve the decryption keys with which to nullify the ransomware attacks. From this fact, we recall critical cases of code disclosure in the recent history of ransomware and, arguing that ransomware are components in cyber-weapons, reflect on the dual-use nature of this research. We further discuss benefits and limits of using cyber-intelligence and counter-intelligence strategies that could be used against this threat

    An analysis of fusing advanced malware email protection logs, malware intelligence and active directory attributes as an instrument for threat intelligence

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    After more than four decades email is still the most widely used electronic communication medium today. This electronic communication medium has evolved into an electronic weapon of choice for cyber criminals ranging from the novice to the elite. As cyber criminals evolve with tools, tactics and procedures, so too are technology vendors coming forward with a variety of advanced malware protection systems. However, even if an organization adopts such a system, there is still the daily challenge of interpreting the log data and understanding the type of malicious email attack, including who the target was and what the payload was. This research examines a six month data set obtained from an advanced malware email protection system from a bank in South Africa. Extensive data fusion techniques are used to provide deeper insight into the data by blending these with malware intelligence and business context. The primary data set is fused with malware intelligence to identify the different malware families associated with the samples. Active Directory attributes such as the business cluster, department and job title of users targeted by malware are also fused into the combined data. This study provides insight into malware attacks experienced in the South African financial services sector. For example, most of the malware samples identified belonged to different types of ransomware families distributed by known botnets. However, indicators of targeted attacks were observed based on particular employees targeted with exploit code and specific strains of malware. Furthermore, a short time span between newly discovered vulnerabilities and the use of malicious code to exploit such vulnerabilities through email were observed in this study. The fused data set provided the context to answer the “who”, “what”, “where” and “when”. The proposed methodology can be applied to any organization to provide insight into the malware threats identified by advanced malware email protection systems. In addition, the fused data set provides threat intelligence that could be used to strengthen the cyber defences of an organization against cyber threats

    A cybersecurity control framework for blockchain ecosystems

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    This paper proposes a cybersecurity control framework for blockchain ecosystems, drawing from risks identified in the practitioner and academic literature. The framework identifies thirteen risks for blockchain implementations, ten common to other information systems and three risks specific to blockchains: centralization of computing power, transaction malleability, and flawed or malicious smart contracts. It also proposes controls to mitigate the risks identified; some were identified in the literature and some are new. Controls that apply to all types of information systems are adapted to the different components of the blockchain ecosystem

    Technical Analysis of Thanos Ransomware

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    Ransomware is a developing menace that encrypts users’ files and holds the decryption key hostage until the victim pays a ransom. This particular class of malware has been in charge of extortion hundreds of millions of dollars every year. Adding to the problem, generating new variations is cheap. Therefore, new malware can detect antivirus and intrusion detection systems and evade them or manifest in ways to make themselves undetectable. We must first understand the characteristics and behavior of various varieties of ransomware to create and construct effective security mechanisms to combat them. This research presents a novel dynamic and behavioral analysis of a newly discovered ransomware called Thanos. It was founded in 2020 and is building up to be the leading malware used by low-to-medium-level attackers. It is part of a new ransomware class known as RaaS (Ransomware as a Service), where attackers can customize it for their desired target audience. So far, it is more prevalent in the middle east and North Africa and has over 130 unique samples already. As part of this investigation, the Thanos ransomware is carefully being analyzed. A testbed is created in the virtual artificial environment that mimics a regular operating system and identifies malware interactions with user data. Using this testbed, we can study how ransomware generally affects our system, how it spreads, and how it continually persists to access the user’s information. We can design a new security mechanism to detect and mitigate Thanos and similar ransomware based on behavior examination results
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