Biblio

This article proposes a method for determining the intruder type in the systems of physical protection of objects. An intruder trying to enter the territory, buildings or premises of the facility has to overcome typical engineering reinforcement elements of building structures. Elements of building structures are equipped with addressable alarm sensors. The intruder type is proposed to be determined according to its equipment by comparing the time of actually overcoming the building structure elements with the expert estimates. The time to overcome the elements of building structures is estimated by the time between successive responses of the security alarm address sensors. The intruder's awareness of the protection object is proposed to be assessed by tracking the route of its movement on the object using address sensors. Determining the intruder type according to the data of the security alarm systems can be used for the in-process tactics control of the security group actions.

As a new service-oriented computing paradigm, cloud computing facilitates users to share and use resources. However, due to the dynamic and openness of its operating environment, only relying on traditional identity authentication technology can no longer fully meet the security requirements of cloud computing. The trust evaluation of user behavior has become the key to improve the security of cloud computing. Therefore, in view of some problems existing in our current research on user behavior trust, this paper optimizes and improves the construction of the evaluation index system and the calculation of trust value, and proposes a cloud end-user behavior trust evaluation model based on sliding window. Finally, the model is proved to be scientific and effective by simulation experiments, which has certain significance for the security protection of cloud resources.

As malware detection algorithms and methods become more sophisticated, malware authors adopt equally sophisticated evasion mechanisms to defeat them. Anecdotal evidence claims Living-Off-The-Land (LotL) techniques are one of the major evasion techniques used in many malware attacks. These techniques leverage binaries already present in the system to conduct malicious actions. We present the first large-scale systematic investigation of the use of these techniques by malware on Windows systems.In this paper, we analyse how common the use of these native system binaries is across several malware datasets, containing a total of 31,805,549 samples. We identify an average 9.41% prevalence. Our results show that the use of LotL techniques is prolific, particularly in Advanced Persistent Threat (APT) malware samples where the prevalence is 26.26%, over twice that of commodity malware.To illustrate the evasive potential of LotL techniques, we test the usage of LotL techniques against several fully patched Windows systems in a local sandboxed environment and show that there is a generalised detection gap in 10 of the most popular anti-virus products.

Windows Communication Foundation (WCF) is a communication framework for building connected, service-oriented applications, initially released by Microsoft as part of.NET Framework, but now open source. The WCF message-based communication is a very popular solution used for sending asynchronous messages from one service endpoint to another. Because WCF provides many functionalities it has a large-consuming development model and often the security measures implemented in applications are not proper. In this study we propose a methodology for offensive security analysis of an WCF endpoint or service, from red team perspective. A step by step approach, empirical information, and detailed analysis report of WCF vulnerabilities are presented. We conclude by proposing recommendations for mitigating attacks and securing endpoints.

Industrial Control System (ICS) transmits control and monitoring data between devices in an industrial environment that includes smart grids, water and gas distribution, or traffic control. Unlike traditional internet communication, ICS traffic is stable, periodical, and with regular communication patterns that can be described using statistical modeling. By observing selected features of ICS transmission, e.g., packet direction and inter-arrival times, we can create a statistical profile of the communication based on distribution of features learned from the normal ICS traffic. This paper demonstrates that using statistical modeling, we can detect various anomalies caused by irregular transmissions, device or link failures, and also cyber attacks like packet injection, scanning, or denial of service (DoS). The paper shows how a statistical model is automatically created from a training dataset. We present two types of statistical profiles: the master-oriented profile for one-to-many communication and the peer-to-peer profile that describes traffic between two ICS devices. The proposed approach is fast and easy to implement as a part of an intrusion detection system (IDS) or an anomaly detection (AD) module. The proof-of-concept is demonstrated on two industrial protocols: IEC 60870-5-104 (aka IEC 104) and IEC 61850 (Goose).

Code-reuse techniques have emerged as a way to defeat the control-flow defenses that prevent the injection and execution of new code, as they allow an adversary to hijack the control flow of a victim program without injected code. A well-known code-reuse attack technique is Return-OrientedProgramming (ROP), which considers and links together (relatively short) code snippets, named ROP gadgets, already present in the victim’s memory address space through a controlled use of the stack values of the victim program. Although ROP attacks are known to be Turing-complete, there are still open question such as the quantification of the executional power of an adversary, which is determined by whatever code exists in the memory of a victim program, and whether an adversary can build a ROP chain, made up of ROP gadgets, for any kind of algorithm. To fill these gaps, in this paper we first define a virtual language, dubbed ROPLANG, that defines a set of operations (specifically, arithmetic, assignment, dereference, logical, and branching operations) which are mapped to ROP gadgets. We then use it to evaluate the executional power of an adversary in Windows 7 and Windows 10, in both 32- and 64-bit versions. In addition, we have developed ROP3, a tool that accepts a set of program files and a ROP chain described with our language and returns the code snippets that make up the ROP chain. Our results show that there are enough ROP gadgets to simulate any virtual operation and that branching operations are the less frequent ones. As expected, our results also indicate that the larger a program file is, the more likely to find ROP gadgets within it for every virtual operation.

This paper shows how the Xtensa architecture can be attacked with Return-Oriented-Programming (ROP). The presented techniques include possibilities for both supported Application Binary Interfaces (ABIs). Especially for the windowed ABI a powerful mechanism is presented that not only allows to jump to gadgets but also to manipulate registers without relying on specific gadgets. This paper purely focuses on how the properties of the architecture itself can be exploited to chain gadgets and not on specific attacks or a gadget catalog.

Windows is one of the popular operating systems in use today, while Universal Serial Bus (USB) is one of the mechanisms used by many people with practical plug and play functions. USB has long been used as a vector of attacks on computers. One method of attack is Keylogger. The Keylogger can take advantage of existing vulnerabilities in the Windows 10 operating system attacks carried out in the form of recording computer keystroke activity without the victim knowing. In this research, an attack will be carried out by running a Powershell Script using BadUSB to be able to activate the Keylogger program. The script is embedded in the Arduino Pro Micro device. The results obtained in the Keyboard Injection Attack research using Arduino Pro Micro were successfully carried out with an average time needed to run the keylogger is 7.474 seconds with a computer connected to the internet. The results of the keylogger will be sent to the attacker via email.

Increased use of secure chat and voice/ video apps has transformed the social life. While the benefits and facilitations are seemingly limitless, so are the asscoiacted vulnerabilities and threats. Besides ensuring confidentiality requirements for common users, known facts of non-readable contents over the network make these apps more attractive for criminals. Though access to contents of cryptograhically secure sessions is not possible, network forensics of secure apps can provide interesting information which can be of great help during criminal invetigations. In this paper, we presented a novel framework of profiling the secure chat and voice/ video calling apps which can be employed to extract hidden patterns about the app, information of involved parties, activities of chatting, voice/ video calls, status indications and notifications while having no information of communication protocol of the app and its security architecture. Signatures of any secure app can be developed though our framework and can become base of a large scale solution. Our methodology is considered very important for different cases of criminal investigations and bussiness intelligence solutions for service provider networks. Our results are applicable to any mobile platform of iOS, android and windows.

This article shows the analogy between natural language texts and quantum-like systems on the example of the Bell test calculating. The applicability of the well-known Bell test for texts in Russian is investigated. The possibility of using this test for the text separation on the topics corresponding to the user query in information retrieval system is shown.

The need for data exchange and storage is currently increasing. The increased need for data exchange and storage also increases the need for data exchange devices and media. One of the most commonly used media exchanges and data storage is the USB Flash Drive. USB Flash Drive are widely used because they are easy to carry and have a fairly large storage. Unfortunately, this increased need is not directly proportional to an increase in awareness of device security, both for USB flash drive devices and computer devices that are used as primary storage devices. This research shows the threats that can arise from the use of USB Flash Drive devices. The threat that is used in this research is the fork bomb implemented on an Arduino Pro Micro device that is converted to a USB Flash drive. The purpose of the Fork Bomb is to damage the memory performance of the affected devices. As a result, memory performance to execute the process will slow down. The use of a USB Flash drive as an attack vector with the fork bomb method causes users to not be able to access the operating system that was attacked. The results obtained indicate that the USB Flash Drive can be used as a medium of Fork Bomb attack on the Windows operating system.

Confidentiality, authentication, privacy and integrity are the pillars of securing data. The most generic way of providing security is setting up passwords and usernames collectively known as login credentials. Operating systems use different techniques to ensure security of login credentials yet brute force attacks and dictionary attacks along with various other types which leads to success in passing or cracking passwords.The objective of proposed HS model is to enhance the protection of SAM file used by Windows Registry so that the system is preserved from intruders.

The traditional smart-home is designed to integrate the concept of the Internet of Things(IoT) into our home environment, and to improve the comfort of home. It connects electrical products and household goods to the network, and then monitors and controls them. However, this paper takes home safety as the main axis of research. It combines the past concept of smart-home and technology of machine learning to improve the whole system of smart-home. Through systematic self-learning, it automatically figure out whether it is normal or abnormal, and reports to remind building occupants safety. At the same time, it saves the cost of human resources preservation. This paper make a set of rules table as the basic criteria first, and then classify a part of data which collected by traditional Internet of Things of smart-home by manual way, which includes the opening and closing of doors and windows, the starting and stopping of motors, the connection and interruption of the system, and the time of sending each data to label, then use Support Vector Machine(SVM) algorithm to classify and build models, and then train it. The executed model is applied to our smart-home system. Finally, we verify the Accuracy of anomaly reporting in our system.

Malware authors attempt to obfuscate and hide their code in its static and dynamic states. This paper provides a novel approach to aid analysis by intercepting and capturing malware artifacts and providing dynamic control of process flow. Capturing malware artifacts allows an analyst to more quickly and comprehensively understand malware behavior and obfuscation techniques and doing so interactively allows multiple code paths to be explored. The faster that malware can be analyzed the quicker the systems and data compromised by it can be determined and its infection stopped. This research proposes an instantiation of an interactive malware analysis and artifact capture tool.

To be applicable to high user request workloads, web caching strategies benefit from low implementation and update effort. In this regard, the Least Recently Used (LRU) replacement principle is a simple and widely-used method. Despite its popularity, LRU has deficits in the achieved hit rate performance and cannot consider transport and network optimization criteria for selecting content to be cached. As a result, many alternatives have been proposed in the literature, which improve the cache performance at the cost of higher complexity. In this work, we evaluate the implementation complexity and runtime performance of LRU, Least Frequently Used (LFU), and score based strategies in the class of fast O(1) updates with constant effort per request. We implement Window LFU (W-LFU) within this class and show that O(1) update effort can be achieved. We further compare fast update schemes of Score Gated LRU and new Score Gated Polling (SGP). SGP is simpler than LRU and provides full flexibility for arbitrary score assessment per data object as information basis for performance optimization regarding network cost and quality measures.

Robotics and the Internet of Things (IoT) are enveloping our society at an exponential rate due to lessening costs and better availability of hardware and software. Additionally, Cloud Robotics and Robot Operating System (ROS) can offset onboard processing power. However, strong and fundamental security practices have not been applied to fully protect these systems., partially negating the benefits of IoT. Researchers are therefore tasked with finding ways of securing communications and systems. Since security and convenience are oftentimes at odds, securing many heterogeneous components without compromising performance can be daunting. Protecting systems from attacks and ensuring that connections and instructions are from approved devices, all while maintaining the performance is imperative. This paper focuses on the development of security best practices and a mesh framework with an open-source, multipoint-to-multipoint virtual private network (VPN) that can tie Linux, Windows, IOS., and Android devices into one secure fabric, with heterogeneous mobile robotic platforms running ROSPY in a secure cloud robotics infrastructure.

Finding identical digital objects (or artifacts) during a forensic analysis is commonly achieved by means of cryptographic hashing functions, such as MD5, SHA1, or SHA-256, to name a few. However, these functions suffer from the avalanche effect property, which guarantees that if an input is changed slightly the output changes significantly. Hence, these functions are unsuitable for typical digital forensics scenarios where a forensics memory image from a likely compromised machine shall be analyzed. This memory image file contains a snapshot of processes (instances of executable files) which were up on execution when the dumping process was done. However, processes are relocated at memory and contain dynamic data that depend on the current execution and environmental conditions. Therefore, the comparison of cryptographic hash values of different processes from the same executable file will be negative. Bytewise approximation matching algorithms may help in these scenarios, since they provide a similarity measurement in the range [0,1] between similar inputs instead of a yes/no answer (in the range 0,1). In this paper, we introduce ProcessFuzzyHash, a Volatility plugin that enables us to compute approximation hash values of processes contained in a Windows memory dump.

Microsoft BitLocker full-disk encryption has been widely implemented at Lehigh University since 2014 on both laptop and desktop computers. This retrospective review will summarize BitLocker's selection factors, initial testing, mass deployment, and important lessons learned. Additionally, this review will also discuss the university's transition to Windows 10 and how it positively impacted the use of BitLocker.

As one of the most commonly used protocols in VPN technology, IPsec has many advantages. However, certain difficulties are posed to the audit work by the protection of in-formation. In this paper, we propose an audit method via man-in-the-middle mechanism, and design a prototype system with DPDK technology. Experiments are implemented in an IPv4 network environment, using default configuration of IPsec VPN configured with known PSK, on operating systems such as windows 7, windows 10, Android and iOS. Experimental results show that the prototype system can obtain the effect of content auditing well without affecting the normal communication between IPsec VPN users.

Organizations face the issue of how to best allocate their security resources. Thus, they need an accurate method for assessing how many new vulnerabilities will be reported for the operating systems (OSs) they use in a given time period. Our approach consists of clustering vulnerabilities by leveraging the text information within vulnerability records, and then simulating the mean value function of vulnerabilities by relaxing the monotonic intensity function assumption, which is prevalent among the studies that use software reliability models (SRMs) and nonhomogeneous Poisson process (NHPP) in modeling. We applied our approach to the vulnerabilities of four OSs: Windows, Mac, IOS, and Linux. For the OSs analyzed in terms of curve fitting and prediction capability, our results, compared to a power-law model without clustering issued from a family of SRMs, are more accurate in all cases we analyzed.

Due to the increasing threat of network attacks, Firewall has become crucial elements in network security, and have been widely deployed in most businesses and institutions for securing private networks. The function of a firewall is to examine each packet that passes through it and decide whether to letting them pass or halting them based on preconfigured rules and policies, so firewall now is the first defense line against cyber attacks. However most of people doesn't know how firewall works, and the most users of windows operating system doesn't know how to use the windows embedded firewall. This paper explains how firewall works, firewalls types, and all you need to know about firewall policies, then presents a novel application (QudsWall) developed by authors that manages windows embedded firewall and make it easy to use.

Summary form only given. In this presentation, several issues regarding operating system security will be investigated. The general problems of OS security are to be addressed. We also discuss why we should consider the security aspects of the OS, and when a secure OS is needed. We delve into the topic of secure OS design as well focusing on covert channel analysis. The specific operating systems under consideration include Windows and Android.