Biblio

The future of ambient assisted living (AAL) especially eHealthcare almost depends on the smart objects that are part of the Internet of things (IoT). In our AAL scenario, these objects collect and transfer real-time information about the patients to the hospital server with the help of Wireless Mesh Network (WMN). Due to the multi-hop nature of mesh networks, it is possible for an adversary to reroute the network traffic via many denial of service (DoS) attacks, and hence affect the correct functionality of the mesh routing protocol. In this paper, based on a comparative study, we choose the most suitable secure mesh routing protocol for IoT-based AAL applications. Then, we analyze the resilience of this protocol against DoS attacks. Focusing on the hello flooding attack, the protocol is simulated and analyzed in terms of data packet delivery ratio, delay, and throughput. Simulation results show that the chosen protocol is totally resilient against DoS attack and can be one of the best candidates for secure routing in IoT-based AAL applications.

Wireless Mesh Networks (WMNs) are being considered as most adequate for deployment in the Neighborhood Area Network (NAN) domain of the smart grid infrastructure because their features such as self-organizing, scalability and cost-efficiency complement the NAN requirements. To enhance the security of the WMNs, the key refreshment strategy for the Simultaneous Authentication of Equals (SAE) or the Efficient Mesh Security Association (EMSA) protocols is an efficient way to make the network more resilient against the cyber-attacks. However, a security vulnerability is discovered in the EMSA protocol when using the key refreshment strategy. The first message of the Mesh Key Holder Security Handshake (MKHSH) can be forged and replayed back in the next cycles of the key refreshment leading to a Denial of Service (DoS) attack. In this paper, a simple one-way hash function based scheme is proposed to prevent the unprotected message from being replayed together with an enhancement to the key refreshment scheme to improve the resilience of the MKHSH. The Protocol Composition Logic (PCL) is used to verify the logical correctness of the proposed scheme, while the Process Analysis Toolkit (PAT) is used to evaluate the security functionality against the malicious attacks.

Due to the growing advancement of crime ware services, the computer and network security becomes a crucial issue. Detecting sensitive data exfiltration is a principal component of each information protection strategy. In this research, a Multi-Level Data Exfiltration Detection (MLDED) system that can handle different types of insider data leakage threats with staircase difficulty levels and their implications for the organization environment has been proposed, implemented and tested. The proposed system detects exfiltration of data outside an organization information system, where the main goal is to use the detection results of a MLDED system for digital forensic purposes. MLDED system consists of three major levels Hashing, Keywords Extraction and Labeling. However, it is considered only for certain type of documents such as plain ASCII text and PDF files. In response to the challenging issue of identifying insider threats, a forensic readiness data exfiltration system is designed that is capable of detecting and identifying sensitive information leaks. The results show that the proposed system has an overall detection accuracy of 98.93%.

Since security is increasingly the principal concern in the conception and implementation of software systems, it is very important that the security mechanisms are designed so as to protect the computer systems against cyber attacks. An Intrusion Tolerance Systems play a crucial role in maintaining the service continuity and enhancing the security compared with the traditional security. In this paper, we propose to combine a preventive maintenance with existing intrusion tolerance system to improve the system security. We use a semi-Markov process to model the system behavior. We quantitatively analyze the system security using the measures such as system availability, Mean Time To Security Failure and cost. The numerical analysis is presented to show the feasibility of the proposed approach.

Cyber crime investigation is the integration of two technologies named theoretical methodology and second practical tools. First is the theoretical digital forensic methodology that encompasses the steps to investigate the cyber crime. And second technology is the practically development of the digital forensic tool which sequentially and systematically analyze digital devices to extract the evidence to prove the crime. This paper explores the development of digital forensic framework, combine the advantages of past twenty five forensic models and generate a algorithm to create a new digital forensic model. The proposed model provides the following advantages, a standardized method for investigation, the theory of model can be directly convert into tool, a history lookup facility, cost and time minimization, applicable to any type of digital crime investigation.

Today, by widely spread of information technology (IT) usage, E-commerce security and its related legislations are very critical issue in information technology and court law. There is a consensus that security matters are the significant foundation of e-commerce, electronic consumers, and firms' privacy. While e-commerce networks need a policy for security privacy, they should be prepared for a simple consumer friendly infrastructure. Hence it is necessary to review the theoretical models for revision. In This theory review, we embody a number of former articles that cover security of e-commerce and legislation ambit at the individual level by assessing five criteria. Whether data of articles provide an effective strategy for secure-protection challenges in e-commerce and e-consumers. Whether provisions clearly remedy precedents or they need to flourish? This paper focuses on analyzing the former discussion regarding e-commerce security and existence legislation toward cyber-crime activity of e-commerce the article also purports recommendation for subsequent research which is indicate that through secure factors of e-commerce we are able to fill the vacuum of its legislation.

With the growth of the Internet, web applications are becoming very popular in the user communities. However, the presence of security vulnerabilities in the source code of these applications is raising cyber crime rate rapidly. It is required to detect and mitigate these vulnerabilities before their exploitation in the execution environment. Recently, Open Web Application Security Project (OWASP) and Common Vulnerabilities and Exposures (CWE) reported Cross-Site Scripting (XSS) as one of the most serious vulnerabilities in the web applications. Though many vulnerability detection approaches have been proposed in the past, existing detection approaches have the limitations in terms of false positive and false negative results. This paper proposes a context-sensitive approach based on static taint analysis and pattern matching techniques to detect and mitigate the XSS vulnerabilities in the source code of web applications. The proposed approach has been implemented in a prototype tool and evaluated on a public data set of 9408 samples. Experimental results show that proposed approach based tool outperforms over existing popular open source tools in the detection of XSS vulnerabilities.

Governments needs reliable data on crime in order to both devise adequate policies, and allocate the correct revenues so that the measures are cost-effective, i.e., The money spent in prevention, detection, and handling of security incidents is balanced with a decrease in losses from offences. The analysis of the actual scenario of government actions in cyber security shows that the availability of multiple contrasting figures on the impact of cyber-attacks is holding back the adoption of policies for cyber space as their cost-effectiveness cannot be clearly assessed. The most relevant literature on the topic is reviewed to highlight the research gaps and to determine the related future research issues that need addressing to provide a solid ground for future legislative and regulatory actions at national and international levels.

The development of internet comes with the other domain that is cyber-crime. The record and intelligently can be exposed to a user of illegal activity so that it has become important to make the technology reliable. Phishing techniques include domain of email messages. Phishing emails have hosted such a phishing website, where a click on the URL or the malware code as executing some actions to perform is socially engineered messages. Lexically analyzing the URLs can enhance the performance and help to differentiate between the original email and the phishing URL. As assessed in this study, in addition to textual analysis of phishing URL, email classification is successful and results in a highly precise anti phishing.

The rise of malware attack and data leakage is putting the Internet at a higher risk. Digital forensic examiners responsible for cyber security incident need to continually update their processes, knowledge and tools due to changing technology. These attack activities can be investigated by means of Digital Triage Forensics (DTF) methodologies. DTF is a procedural model for the crime scene investigation of digital forensic applications. It takes place as a way of gathering quick intelligence, and presents methods of conducting pre/post-blast investigations. A DTF framework of Window malware forensic toolkit is further proposed. It is also based on ISO/IEC 27037: 2012 - guidelines for specific activities in the handling of digital evidence. The argument is made for a careful use of digital forensic investigations to improve the overall quality of expert examiners. This solution may improve the speed and quality of pre/post-blast investigations. By considering how triage solutions are being implemented into digital investigations, this study presents a critical analysis of malware forensics. The analysis serves as feedback for integrating digital forensic considerations, and specifies directions for further standardization efforts.

In this paper, a new method for quantitative evaluation of the security of cyber-physical systems (CPSs) is proposed. The proposed method models the different classes of adversarial attacks against CPSs, including cross-domain attacks, i.e., cyber-to-cyber and cyber-to-physical attacks. It also takes the secondary consequences of attacks on CPSs into consideration. The intrusion process of attackers has been modeled using attack graph and the consequence estimation process of the attack has been investigated using process model. The security attributes and the special parameters involved in the security analysis of CPSs, have been identified and considered. The quantitative evaluation has been done using the probability of attacks, time-to-shutdown of the system and security risks. The validation phase of the proposed model is performed as a case study by applying it to a boiling water power plant and estimating the suitable security measures.

Language vector space models (VSMs) have recently proven to be effective across a variety of tasks. In VSMs, each word in a corpus is represented as a real-valued vector. These vectors can be used as features in many applications in machine learning and natural language processing. In this paper, we study the effect of vector space representations in cyber security. In particular, we consider a passive traffic analysis attack (Website Fingerprinting) that threatens users' navigation privacy on the web. By using anonymous communication, Internet users (such as online activists) may wish to hide the destination of web pages they access for different reasons such as avoiding tyrant governments. Traditional website fingerprinting studies collect packets from the users' network and extract features that are used by machine learning techniques to reveal the destination of certain web pages. In this work, we propose the packet to vector (P2V) approach where we model website fingerprinting attack using word vector representations. We show how the suggested model outperforms previous website fingerprinting works.

Denial-of-Service (DoS) attacks pose a threat to any service provider on the internet. While traditional DoS flooding attacks require the attacker to control at least as much resources as the service provider in order to be effective, so-called low-rate DoS attacks can exploit weaknesses in careless design to effectively deny a service using minimal amounts of network traffic. This paper investigates one such weakness found within version 2.2 of the popular Apache HTTP Server software. The weakness concerns how the server handles the persistent connection feature in HTTP 1.1. An attack simulator exploiting this weakness has been developed and shown to be effective. The attack was then studied with spectral analysis for the purpose of examining how well the attack could be detected. Similar to other papers on spectral analysis of low-rate DoS attacks, the results show that disproportionate amounts of energy in the lower frequencies can be detected when the attack is present. However, by randomizing the attack pattern, an attacker can efficiently reduce this disproportion to a degree where it might be impossible to correctly identify an attack in a real world scenario.

The Polish Power System is becoming increasingly more dependent on Information and Communication Technologies which results in its exposure to cyberattacks, including the evolved and highly sophisticated threats such as Advanced Persistent Threats or Distributed Denial of Service attacks. The most exposed components are SCADA systems in substations and Distributed Control Systems in power plants. When addressing this situation the usual cyber security technologies are prerequisite, but not sufficient. With the rapidly evolving cyber threat landscape the use of partnerships and information sharing has become critical. However due to several anonymity concerns the relevant stakeholders may become reluctant to exchange sensitive information about security incidents. In the paper a multi-agent architecture is presented for the Polish Power System which addresses the anonymity concerns.

Cyber-attacks have been evolved in a way to be more sophisticated by employing combinations of attack methodologies with greater impacts. For instance, Advanced Persistent Threats (APTs) employ a set of stealthy hacking processes running over a long period of time, making it much hard to detect. With this trend, the importance of big-data security analytics has taken greater attention since identifying such latest attacks requires large-scale data processing and analysis. In this paper, we present SEAS-MR (Security Event Aggregation System over MapReduce) that facilitates scalable security event aggregation for comprehensive situation analysis. The introduced system provides the following three core functions: (i) periodic aggregation, (ii) on-demand aggregation, and (iii) query support for effective analysis. We describe our design and implementation of the system over MapReduce and high-level query languages, and report our experimental results collected through extensive settings on a Hadoop cluster for performance evaluation and design impacts.

Taiwan has become the frontline in an emerging cyberspace battle. Cyberattacks from different countries are constantly reported during past decades. The incident of Advanced Persistent Threat (APT) is analyzed from the golden triangle components (people, process and technology) to ensure the application of digital forensics. This study presents a novel People-Process-Technology-Strategy (PPTS) model by implementing a triage investigative step to identify evidence dynamics in digital data and essential information in auditing logs. The result of this study is expected to improve APT investigation. The investigation scenario of this proposed methodology is illustrated by applying to some APT incidents in Taiwan.

Industrial Control Systems (ICS) which among others are comprised of Supervisory Control and Data Acquisition (SCADA) and Distributed Control Systems (DCS) are used to control industrial processes. ICS have now been connected to other Information Technology (IT) systems and have as a result become vulnerable to Advanced Persistent Threats (APT). APTs are targeted attacks that use zero-day attacks to attack systems. Current ICS security mechanisms fail to deter APTs from infiltrating ICS. An analysis of possible solutions to deter APTs was done. This paper proposes the use of Artificial Immune Systems to secure ICS from APTs.

Advanced Persistent Threat (APT), unlike traditional hacking attempts, carries out specific attacks on a specific target to illegally collect information and data from it. These targeted attacks use special-crafted malware and infrequent activity to avoid detection, so that hackers can retain control over target systems unnoticed for long periods of time. In order to detect these stealthy activities, a large-volume of traffic data generated in a period of time has to be analyzed. We proposed a scalable solution, Ctracer to detect stealthy command and control channel in a large-volume of traffic data. APT uses multiple command and control (C&C) channel and change them frequently to avoid detection, but there are common signatures in those C&C sessions. By identifying common network signature, Ctracer is able to group the C&C sessions. Therefore, we can detect an APT and all the C&C session used in an APT attack. The Ctracer is evaluated in a large enterprise for four months, twenty C&C servers, three APT attacks are reported. After investigated by the enterprise's Security Operations Center (SOC), the forensic report shows that there is specific enterprise targeted APT cases and not ever discovered for over 120 days.

The dynamic nature of the Web 2.0 and the heavy obfuscation of web-based attacks complicate the job of the traditional protection systems such as Firewalls, Anti-virus solutions, and IDS systems. It has been witnessed that using ready-made toolkits, cyber-criminals can launch sophisticated attacks such as cross-site scripting (XSS), cross-site request forgery (CSRF) and botnets to name a few. In recent years, cyber-criminals have targeted legitimate websites and social networks to inject malicious scripts that compromise the security of the visitors of such websites. This involves performing actions using the victim browser without his/her permission. This poses the need to develop effective mechanisms for protecting against Web 2.0 attacks that mainly target the end-user. In this paper, we address the above challenges from information flow control perspective by developing a framework that restricts the flow of information on the client-side to legitimate channels. The proposed model tracks sensitive information flow and prevents information leakage from happening. The proposed model when applied to the context of client-side web-based attacks is expected to provide a more secure browsing environment for the end-user.

The convergence of the Internet and mobile computing enables personalised access to online services anywhere and anytime. This potent access capability creates opportunities for new business models which stimulates vigorous investment and rapid innovation. Unfortunately, this innovation also produces new vulnerabilities and threats, and the new business models also create incentives for attacks, because criminals will always follow the money. Unless the new threats are balanced with appropriate countermeasures, growth in the Internet and mobile services will encounter painful setbacks. Security and trust are two fundamental factors for sustainable development of identity management in online markets and communities. The aim of this study is to present an overview of the central aspects of identity management in the Internet and mobile computing with respect to security and trust.

With the rapid advancement in technology and the growing complexities in the interaction of these technologies and networks, it is even more important for countries and organizations to gain sustainable security advantage. Security advantage refers to the ability to manage and respond to threats and vulnerabilities with a proactive security posture. This is accomplished through effectively planning, managing, responding to and recovering from threats and vulnerabilities. However not many organizations and even countries, especially in the developing world, have been able to equip themselves with the necessary and sufficient know-how or ability to integrate knowledge and capabilities to achieve security advantage within their environment. Having a structured set of requirements or indicators to aid in progressively attaining different levels of maturity and capabilities is one important method to determine the state of cybersecurity readiness. The research introduces the Cybersecurity Capability Maturity Model (CM2), a 6-step process of progressive development of cybersecurity maturity and knowledge integration that ranges from a state of limited awareness and application of security controls to pervasive optimization of the protection of critical assets.
 

Control system networks are increasingly being connected to enterprise level networks. These connections leave critical industrial controls systems vulnerable to cyber-attacks. Most of the effort in protecting these cyber-physical systems (CPS) from attacks has been in securing the networks using information security techniques. Effort has also been applied to increasing the protection and reliability of the control system against random hardware and software failures. However, the inability of information security techniques to protect against all intrusions means that the control system must be resilient to various signal attacks for which new analysis methods need to be developed. In this paper, sensor signal attacks are analyzed for observer-based controlled systems. The threat surface for sensor signal attacks is subdivided into denial of service, finite energy, and bounded attacks. In particular, the error signals between states of attack free systems and systems subject to these attacks are quantified. Optimal sensor and actuator signal attacks for the finite and infinite horizon linear quadratic (LQ) control in terms of maximizing the corresponding cost functions are computed. The closed-loop systems under optimal signal attacks are provided. Finally, an illustrative numerical example using a power generation network is provided together with distributed LQ controllers.

Due to cyber security is an important issue of the cloud computing. Insider threat becomes more and more important for cyber security, it is also much more complex issue. But till now, there is no equivalent to a vulnerability scanner for insider threat. We survey and discuss the history of research on insider threat analysis to know system dynamics is the best method to mitigate insider threat from people, process, and technology. In the paper, we present a system dynamics method to model insider threat. We suggest some concludes for future research who are interested in insider threat issue The study.

Recently, threat of previously unknown cyber-attacks are increasing because existing security systems are not able to detect them. Past cyber-attacks had simple purposes of leaking personal information by attacking the PC or destroying the system. However, the goal of recent hacking attacks has changed from leaking information and destruction of services to attacking large-scale systems such as critical infrastructures and state agencies. In the other words, existing defence technologies to counter these attacks are based on pattern matching methods which are very limited. Because of this fact, in the event of new and previously unknown attacks, detection rate becomes very low and false negative increases. To defend against these unknown attacks, which cannot be detected with existing technology, we propose a new model based on big data analysis techniques that can extract information from a variety of sources to detect future attacks. We expect our model to be the basis of the future Advanced Persistent Threat(APT) detection and prevention system implementations.

Electrical Distribution Networks face new challenges by the Smart Grid deployment. The required metering infrastructures add new vulnerabilities that need to be taken into account in order to achieve Smart Grid functionalities without considerable reliability trade-off. In this paper, a qualitative assessment of the cyber attack impact on the Advanced Metering Infrastructure (AMI) is initially attempted. Attack simulations have been conducted on a realistic Grid topology. The simulated network consisted of Smart Meters, routers and utility servers. Finally, the impact of Denial-of-Service and Distributed Denial-of-Service (DoS/DDoS) attacks on distribution system reliability is discussed through a qualitative analysis of reliability indices.