Biblio

Software defined networking promises network operators to dramatically simplify network management. It provides flexibility and innovation through network programmability. With SDN, network management moves from codifying functionality in terms of low-level device configuration to building software that facilitates network management and debugging[1]. SDN provides new techniques to solve long-standing problems in networking like routing by separating the complexity of state distribution from network specification. Despite all the hype surrounding SDNs, exploiting its full potential is demanding. Security is still the major issue and a striking challenge that reduces the growth of SDNs. Moreover the introduction of various architectural components and up cycling of novel entities of SDN poses new security issues and threats. SDN is considered as major target for digital threats and cyber-attacks[2] and have more devastating effects than simple networks. Initial SDN design doesn't considered security as its part; therefore, it must be raised on the agenda. This article discusses the security solutions proposed to secure SDNs. We categorize the security solutions in the article by presenting a thematic taxonomy based on SDN architectural layers/interfaces[3], security measures and goals, simulation framework. Moreover, the literature also points out the possible attacks[2] targeting different layers/interfaces of SDNs. For securing SDNs, the potential requirements and their key enablers are also identified and presented. Also, the articles sketch the design of secure and dependable SDNs. At last, we discuss open issues and challenges of SDN security that may be rated appropriate to be handled by professionals and researchers in the future.

In view of the high demand for the security of visiting data in power system, a network data security analysis method based on DPI technology was put forward in this paper, to solve the problem of security gateway judge the legality of the network data. Considering the legitimacy of the data involves data protocol and data contents, this article will filters the data from protocol matching and content detection. Using deep packet inspection (DPI) technology to screen the protocol. Using protocol analysis to detect the contents of data. This paper implements the function that allowing secure data through the gateway and blocking threat data. The example proves that the method is more effective guarantee the safety of visiting data.

Information security deals with a large number of subjects like spoofed message detection, audio processing, video surveillance and cyber-attack detections. However the biggest threat for the homeland security is cyber-attacks. Distributed Denial of Service attack is one among them. Interconnected systems such as database server, web server, cloud computing servers etc., are now under threads from network attackers. Denial of service is common attack in the internet which causes problem for both the user and the service providers. Distributed attack sources can be used to enlarge the attack in case of Distributed Denial of Service so that the effect of the attack will be high. Distributed Denial of Service attacks aims at exhausting the communication and computational power of the network by flooding the packets through the network and making malicious traffic in the network. In order to be an effective service the DDoS attack must be detected and mitigated quickly before the legitimate user access the attacker's target. The group of systems that is used to perform the DoS attack is known as the botnets. This paper introduces the overview of the state of art in DDoS attack detection strategies.

The evolution of the Internet of Things (IoT) requires a well-defined infrastructure of systems that provides services for device abstraction and data management, and also supports the development of applications. Middleware for IoT has been recognized as the system that can provide these services and has become increasingly important for IoT in recent years. The large amount of data that flows into a middleware system demands a security architecture that ensures the protection of all layers of the system, including the communication channels and border APIs used to integrate the applications and IoT devices. However, this security architecture should be based on lightweight approaches since middleware systems are widely applied in constrained environments. Some works have already defined new solutions and adaptations to existing approaches in order to mitigate IoT middleware security problems. In this sense, this article discusses the role of lightweight approaches to the standardization of a security architecture for IoT middleware systems. This article also analyzes concepts and existing works, and presents some important IoT middleware challenges that may be addressed by emerging lightweight security approaches in order to achieve the consolidation of a standard security architecture and the mitigation of the security problems found in IoT middleware systems.

Currently, different forms of ransomware are increasingly threatening Internet users. Modern ransomware encrypts important user data, and it is only possible to recover it once a ransom has been paid. In this article we show how software-defined networking can be utilized to improve ransomware mitigation. In more detail, we analyze the behavior of popular ransomware - CryptoWall - and, based on this knowledge, propose two real-time mitigation methods. Then we describe the design of an SDN-based system, implemented using OpenFlow, that facilitates a timely reaction to this threat, and is a crucial factor in the case of crypto ransomware. What is important is that such a design does not significantly affect overall network performance. Experimental results confirm that the proposed approach is feasible and efficient.

The increasing complexity of cyber-attacks necessitates the design of more efficient hardware architectures for real-time Intrusion Detection Systems (IDSs). String matching is the main performance-demanding component of an IDS. An effective technique to design high-performance string matching engines is to partition the target set of strings into multiple subgroups and to use a parallel string matching hardware unit for each subgroup. This paper introduces a novel pattern grouping algorithm for heterogeneous bit-split string matching architectures. The proposed algorithm presents a reliable method to estimate the correlation between strings. The correlation factors are then used to find a preferred group for each string in a seed growing approach. Experimental results demonstrate that the proposed algorithm achieves an average of 41% reduction in memory consumption compared to the best existing approach found in the literature, while offering orders of magnitude faster execution time compared to an exhaustive search.

Distributed Denial of Service attacks against high-profile targets have become more frequent in recent years. In response to such massive attacks, several architectures have adopted proxies to introduce layers of indirection between end users and target services and reduce the impact of a DDoS attack by migrating users to new proxies and shuffling clients across proxies so as to isolate malicious clients. However, the reactive nature of these solutions presents weaknesses that we leveraged to develop a new attack - the proxy harvesting attack - which enables malicious clients to collect information about a large number of proxies before launching a DDoS attack. We show that current solutions are vulnerable to this attack, and propose a moving target defense technique consisting in periodically and proactively replacing one or more proxies and remapping clients to proxies. Our primary goal is to disrupt the attacker's reconnaissance effort. Additionally, to mitigate ongoing attacks, we propose a new client-to-proxy assignment strategy to isolate compromised clients, thereby reducing the impact of attacks. We validate our approach both theoretically and through simulation, and show that the proposed solution can effectively limit the number of proxies an attacker can discover and isolate malicious clients.

Internet of Things(IoT) is the next big boom in the networking field. The vision of IoT is to connect daily used objects (which have the ability of sensing and actuation) to the Internet. This may or may or may not involve human. IoT field is still maturing and has many open issues. We build up on the security issues. As the devices have low computational power and low memory the existing security mechanisms (which are a necessity) should also be optimized accordingly or a clean slate approach needs to be followed. This is a survey paper to focus on the security aspects of IoT. We further also discuss the open challenges in this field.

Prior remote attestation may not be suitable to scale to the proliferation of IoT device swarms. To this end, we propose a cooperative remote attestation scheme, which validates the security state and verifies the system integrity with the cooperation of neighbor devices. The efficiency of the proposed mechanism is analyzed as a cryptographic protocol and then discussed in terms of security and scalability.

A trap set to detect attempts at unauthorized use of information systems. But setting up these honeypots and keep these guzzling electricity 24X7 is rather expensive. Plus there is always a risk of a skillful hacker or a deadly malware may break through this and compromise the whole system. Honeypot name suggest, a pot that contents full of honey to allure beers, but in networks Scenario honeypot is valuable tool that helps to allure attackers. It helps to detect and analyze malicious activity over your network. However honeypots used for commercial organization do not share data and large honeypot gives read only data. We propose an Arm based device having all capability of honeypots to allure attackers. Current honeypots are based on large Network but we are trying to make s device which have the capabilities to establish in small network and cost effective. This research helps us to make a device based on arm board and CCFIS Software to allure attackers which is easy to install and cost effective. CCFIS Sensor helps us to Capture malware and Analysis the attack. In this we did reverse Engineering of honeypots to know about how it captures malware. During reverse engineering we know about pros and cons of honeypots that are mitigated in CCFIS Sensor. After Completion of device we compared honeypots and CCFIS Sensor to check the effectiveness of device.

Server honey pots are computer systems that hide in a network capturing attack packets. As the name goes, server honey pots are installed in server machines running a set of services. Enterprises and government organisations deploy these honey pots to know the extent of attacks on their network. Since, most of the recent attacks are advanced persistent attacks there is much research work going on in building better peripheral security measures. In this paper, the authors have deployed several honey pots in a virtualized environment to gather traces of malicious activities. The network infrastructure is resilient and provides much information about hacker's activities. It is cost-effective and can be easily deployed in any organisation without specialized hardware.

In this paper we present an approach to implement security as a Virtualized Network Function (VNF) that is implemented within a Software-Defined Infrastructure (SDI). We present a scalable, flexible, and seamless design for a Deep Packet Inspection (DPI) system for network intrusion detection and prevention. We discuss how our design introduces significant reductions in both capital and operational expenses (CAPEX and OPEX). As proof of concept, we describe an implementation for a modular security solution that uses the SAVI SDI testbed to first detect and then block an attack or to re-direct it to a honey-pot for further analysis. We discuss our testing methodology and provide measurement results for the test cases where an application faces various security attacks.

Botnets are considered one of the most dangerous species of network-based attack today because they involve the use of very large coordinated groups of hosts simultaneously. The behavioral analysis of computer networks is at the basis of the modern botnet detection methods, in order to intercept traffic generated by malwares for which signatures do not exist yet. Defining a pattern of features to be placed at the basis of behavioral analysis, puts the emphasis on the quantity and quality of information to be caught and used to mark data streams as normal or abnormal. The problem is even more evident if we consider extensive computer networks or clouds. With the present paper we intend to show how heuristics applied to large-scale proxy logs, considering a typical phase of the life cycle of botnets such as the search for C&C Servers through AGDs (Algorithmically Generated Domains), may provide effective and extremely rapid results. The present work will introduce some novel paradigms. The first is that some of the elements of the supply chain of botnets could be completed without any interaction with the Internet, mostly in presence of wide computer networks and/or clouds. The second is that behind a large number of workstations there are usually "human beings" and it is unlikely that their behaviors will cause marked changes in the interaction with the Internet in a fairly narrow time frame. Finally, AGDs can highlight, at the moment, common lexical features, detectable quickly and without using any black/white list.

Security in cloud environments is always considered an issue, due to the lack of control over leased resources. In this paper, we present a solution that offers security-as-a-service by relying on Security Service Level Agreements (Security SLAs) as a means to represent the security features to be granted. In particular, we focus on a security mechanism that is automatically configured and activated in an as-a-service fashion in order to protect cloud resources against DoS attacks. The activities reported in this paper are part of a wider work carried out in the FP7-ICT programme project SPECS, which aims at building a framework offering Security-as-a-Service using an SLA-based approach. The proposed approach founds on the adoption of SPECS Services to negotiate, to enforce and to monitor suitable security metrics, chosen by cloud customers, negotiated with the provider and included in a signed Security SLA.

Volume anomaly such as distributed denial-of-service (DDoS) has been around for ages but with advancement in technologies, they have become stronger, shorter and weapon of choice for attackers. Digital forensic analysis of intrusions using alerts generated by existing intrusion detection system (IDS) faces major challenges, especially for IDS deployed in large networks. In this paper, the concept of automatically sifting through a huge volume of alerts to distinguish the different stages of a DDoS attack is developed. The proposed novel framework is purpose-built to analyze multiple logs from the network for proactive forecast and timely detection of DDoS attacks, through a combined approach of Shannon-entropy concept and clustering algorithm of relevant feature variables. Experimental studies on a cyber-range simulation dataset from the project industrial partners show that the technique is able to distinguish precursor alerts for DDoS attacks, as well as the attack itself with a very low false positive rate (FPR) of 22.5%. Application of this technique greatly assists security experts in network analysis to combat DDoS attacks.

Flooding attacks are well-known security threats that can lead to a denial of service (DoS) in computer networks. These attacks consist of an excessive traffic generation, by which an attacker aim to disrupt or interrupt some services in the network. The impact of flooding attacks is not just about some nodes, it can be also the whole network. Many routing protocols are vulnerable to these attacks, especially those using reactive mechanism of route discovery, like AODV. In this paper, we propose a statistical approach to defense against RREQ flooding attacks in MANETs. Our detection mechanism can be applied on AODV-based ad hoc networks. Simulation results prove that these attacks can be detected with a low rate of false alerts.

Botnets are emerging as the most serious cyber threat among different forms of malware. Today botnets have been facilitating to launch many cybercriminal activities like DDoS, click fraud, phishing attacks etc. The main purpose of botnet is to perform massive financial threat. Many large organizations, banks and social networks became the target of bot masters. Botnets can also be leased to motivate the cybercriminal activities. Recently several researches and many efforts have been carried out to detect bot, C&C channels and bot masters. Ultimately bot maters also strengthen their activities through sophisticated techniques. Many botnet detection techniques are based on payload analysis. Most of these techniques are inefficient for encrypted C&C channels. In this paper we explore different categories of botnet and propose a detection methodology to classify bot host from the normal host by analyzing traffic flow characteristics based on time intervals instead of payload inspection. Due to that it is possible to detect botnet activity even encrypted C&C channels are used.

Denial of Service (DoS) attacks is one of the major threats and among the hardest security problems in the Internet world. Of particular concern are Distributed Denial of Service (DDoS) attacks, whose impact can be proportionally severe. With little or no advance warning, an attacker can easily exhaust the computing resources of its victim within a short period of time. In this paper, we study the impact of a UDP flood attack on TCP throughput, round-trip time, and CPU utilization for a Web Server with the new generation of Linux platform, Linux Ubuntu 13. This paper also evaluates the impact of various defense mechanisms, including Access Control Lists (ACLs), Threshold Limit, Reverse Path Forwarding (IP Verify), and Network Load Balancing. Threshold Limit is found to be the most effective defense.

Cultivation of Smart Grid refurbish with brisk and ingenious. The delinquent breed and sow mutilate in massive. This state of affair coerces security as a sapling which incessantly is to be irrigated with Research and Analysis. The Cyber Security is endowed with resiliency to the SYN flooding induced Denial of Service attack in this work. The proposed secure web server algorithm embedded in the LPC1768 processor ensures the smart resources to be precluded from the attack.

In cyberspace, availability of the resources is the key component of cyber security along with confidentiality and integrity. Distributed Denial of Service (DDoS) attack has become one of the major threats to the availability of resources in computer networks. It is a challenging problem in the Internet. In this paper, we present a detailed study of DDoS attacks on the Internet specifically the attacks due to protocols vulnerabilities in the TCP/IP model, their countermeasures and various DDoS attack mechanisms. We thoroughly review DDoS attacks defense and analyze the strengths and weaknesses of different proposed mechanisms.

Distributed Denial of Service (DoS) attacks is one of the major threats and among the hardest security problems in the Internet world. In this paper, we study the impact of a UDP flood attack on TCP throughputs, round-trip time, and CPU utilization on the latest version of Windows and Linux platforms, namely, Windows Server 2012 and Linux Ubuntu 13. This paper also evaluates several defense mechanisms including Access Control Lists (ACLs), Threshold Limit, Reverse Path Forwarding (IP Verify), and Network Load Balancing. Threshold Limit defense gave better results than the other solutions.

The issue of security has become ever more prevalent in the analysis and design of cyber-physical systems. In this paper, we analyze a consensus network in the presence of Denial-of-Service (DoS) attacks, namely attacks that prevent communication among the network agents. By introducing a notion of Persistency-of-Communication (PoC), we provide a characterization of DoS frequency and duration such that consensus is not destroyed. An example is given to substantiate the analysis.

There has been a rampant surge in compromise of consumer grade small scale routers in the last couple of years. Attackers are able to manipulate the Domain Name Space (DNS) settings of these devices hence making them capable of initiating different man-in-the-middle attacks. By this study we aim to explore and comprehend the current state of these attacks. Focusing on the Indian Autonomous System Number (ASN) space, we performed scans over 3 months to successfully find vulnerable routers and extracted the DNS information from these vulnerable routers. In this paper we present the methodology followed for scanning, a detailed analysis report of the information we were able to collect and an insight into the current trends in the attack patterns. We conclude by proposing recommendations for mitigating these attacks.

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.

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%.