Economic issues in distributed computing

textOn the Internet, one of the essential characteristics of electronic commerce is the integration of large-scale computer networks and business practices. Commercial servers are connected through open and complex communication technologies, and online consumers access the services with virtually unpredictable behavior. Both of them as well as the e-Commerce infrastructure are vulnerable to cyber attacks. Among the various network security problems, the Distributed Denial-of-Service (DDoS) attack is a unique example to illustrate the risk of commercial network applications. Using a massive junk traffic, literally anyone on the Internet can launch a DDoS attack to flood and shutdown an eCommerce website. Cooperative technological solutions for Distributed Denial-of-Service (DDoS) attacks are already available, yet organizations in the best position to implement them lack incentive to do so, and the victims of DDoS attacks cannot find effective methods to motivate the organizations. Chapter 1 discusses two components of the technological solutions to DDoS attacks: cooperative filtering and cooperative traffic smoothing by caching, and then analyzes the broken incentive chain in each of these technological solutions. As a remedy, I propose usage-based pricing and Capacity Provision Networks, which enable victims to disseminate enough incentive along attack paths to stimulate cooperation against DDoS attacks. Chapter 2 addresses possible Distributed Denial-of-Service (DDoS) attacks toward the wireless Internet including the Wireless Extended Internet, the Wireless Portal Network, and the Wireless Ad Hoc network. I propose a conceptual model for defending against DDoS attacks on the wireless Internet, which incorporates both cooperative technological solutions and economic incentive mechanisms built on usage-based fees. Cost-effectiveness is also addressed through an illustrative implementation scheme using Policy Based Networking (PBN). By investigating both technological and economic difficulties in defense of DDoS attacks which have plagued the wired Internet, our aim here is to foster further development of wireless Internet infrastructure as a more secure and efficient platform for mobile commerce. To avoid centralized resources and performance bottlenecks, online peer-to-peer communities and online social network have become increasingly popular. In particular, the recent boost of online peer-to-peer communities has led to exponential growth in sharing of user-contributed content which has brought profound changes to business and economic practices. Understanding the dynamics and sustainability of such peer-to-peer communities has important implications for business managers. In Chapter 3, I explore the structure of online sharing communities from a dynamic process perspective. I build an evolutionary game model to capture the dynamics of online peer-to-peer communities. Using online music sharing data collected from one of the IRC Channels for over five years, I empirically investigate the model which underlies the dynamics of the music sharing community. Our empirical results show strong support for the evolutionary process of the community. I find that the two major parties in the community, namely sharers and downloaders, are influencing each other in their dynamics of evolvement in the community. These dynamics reveal the mechanism through which peer-to-peer communities sustain and thrive in a constant changing environment.Information, Risk, and Operations Management (IROM

Packet filter performance monitor (anti-DDOS algorithm for hybrid topologies)

DDoS attacks are increasingly becoming a major problem. According to Arbor Networks, the largest DDoS attack reported by a respondent in 2015 was 500 Gbps. Hacker News stated that the largest DDoS attack as of March 2016 was over 600 Gbps, and the attack targeted the entire BBC website. With this increasing frequency and threat, and the average DDoS attack duration at about 16 hours, we know for certain that DDoS attacks will not be going away anytime soon. Commercial companies are not effectively providing mitigation techniques against these attacks, considering that major corporations face the same challenges. Current security appliances are not strong enough to handle the overwhelming traffic that accompanies current DDoS attacks. There is also a limited research on solutions to mitigate DDoS attacks. Therefore, there is a need for a means of mitigating DDoS attacks in order to minimize downtime. One possible solution is for organizations to implement their own architectures that are meant to mitigate DDoS attacks. In this dissertation, we present and implement an architecture that utilizes an activity monitor to change the states of firewalls based on their performance in a hybrid network. Both firewalls are connected inline. The monitor is mirrored to monitor the firewall states. The monitor reroutes traffic when one of the firewalls become overwhelmed due to a HTTP DDoS flooding attack. The monitor connects to the API of both firewalls. The communication between the rewalls and monitor is encrypted using AES, based on PyCrypto Python implementation. This dissertation is structured in three parts. The first found the weakness of the hardware firewall and determined its threshold based on spike and endurance tests. This was achieved by flooding the hardware firewall with HTTP packets until the firewall became overwhelmed and unresponsive. The second part implements the same test as the first, but targeted towards the virtual firewall. The same parameters, test factors, and determinants were used; however a different load tester was utilized. The final part was the implementation and design of the firewall performance monitor. The main goal of the dissertation is to minimize downtime when network firewalls are overwhelmed as a result of a DDoS attack

Security Engineering of Patient-Centered Health Care Information Systems in Peer-to-Peer Environments: Systematic Review

Background: Patient-centered health care information systems (PHSs) enable patients to take control and become knowledgeable about their own health, preferably in a secure environment. Current and emerging PHSs use either a centralized database, peer-to-peer (P2P) technology, or distributed ledger technology for PHS deployment. The evolving COVID-19 decentralized Bluetooth-based tracing systems are examples of disease-centric P2P PHSs. Although using P2P technology for the provision of PHSs can be flexible, scalable, resilient to a single point of failure, and inexpensive for patients, the use of health information on P2P networks poses major security issues as users must manage information security largely by themselves. Objective: This study aims to identify the inherent security issues for PHS deployment in P2P networks and how they can be overcome. In addition, this study reviews different P2P architectures and proposes a suitable architecture for P2P PHS deployment. Methods: A systematic literature review was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines. Thematic analysis was used for data analysis. We searched the following databases: IEEE Digital Library, PubMed, Science Direct, ACM Digital Library, Scopus, and Semantic Scholar. The search was conducted on articles published between 2008 and 2020. The Common Vulnerability Scoring System was used as a guide for rating security issues. Results: Our findings are consolidated into 8 key security issues associated with PHS implementation and deployment on P2P networks and 7 factors promoting them. Moreover, we propose a suitable architecture for P2P PHSs and guidelines for the provision of PHSs while maintaining information security. Conclusions: Despite the clear advantages of P2P PHSs, the absence of centralized controls and inconsistent views of the network on some P2P systems have profound adverse impacts in terms of security. The security issues identified in this study need to be addressed to increase patients\u27 intention to use PHSs on P2P networks by making them safe to use

A composable approach to design of newer techniques for large-scale denial-of-service attack attribution

Since its early days, the Internet has witnessed not only a phenomenal growth, but also a large number of security attacks, and in recent years, denial-of-service (DoS) attacks have emerged as one of the top threats. The stateless and destination-oriented Internet routing combined with the ability to harness a large number of compromised machines and the relative ease and low costs of launching such attacks has made this a hard problem to address. Additionally, the myriad requirements of scalability, incremental deployment, adequate user privacy protections, and appropriate economic incentives has further complicated the design of DDoS defense mechanisms. While the many research proposals to date have focussed differently on prevention, mitigation, or traceback of DDoS attacks, the lack of a comprehensive approach satisfying the different design criteria for successful attack attribution is indeed disturbing. Our first contribution here has been the design of a composable data model that has helped us represent the various dimensions of the attack attribution problem, particularly the performance attributes of accuracy, effectiveness, speed and overhead, as orthogonal and mutually independent design considerations. We have then designed custom optimizations along each of these dimensions, and have further integrated them into a single composite model, to provide strong performance guarantees. Thus, the proposed model has given us a single framework that can not only address the individual shortcomings of the various known attack attribution techniques, but also provide a more wholesome counter-measure against DDoS attacks. Our second contribution here has been a concrete implementation based on the proposed composable data model, having adopted a graph-theoretic approach to identify and subsequently stitch together individual edge fragments in the Internet graph to reveal the true routing path of any network data packet. The proposed approach has been analyzed through theoretical and experimental evaluation across multiple metrics, including scalability, incremental deployment, speed and efficiency of the distributed algorithm, and finally the total overhead associated with its deployment. We have thereby shown that it is realistically feasible to provide strong performance and scalability guarantees for Internet-wide attack attribution. Our third contribution here has further advanced the state of the art by directly identifying individual path fragments in the Internet graph, having adopted a distributed divide-and-conquer approach employing simple recurrence relations as individual building blocks. A detailed analysis of the proposed approach on real-life Internet topologies with respect to network storage and traffic overhead, has provided a more realistic characterization. Thus, not only does the proposed approach lend well for simplified operations at scale but can also provide robust network-wide performance and security guarantees for Internet-wide attack attribution. Our final contribution here has introduced the notion of anonymity in the overall attack attribution process to significantly broaden its scope. The highly invasive nature of wide-spread data gathering for network traceback continues to violate one of the key principles of Internet use today - the ability to stay anonymous and operate freely without retribution. In this regard, we have successfully reconciled these mutually divergent requirements to make it not only economically feasible and politically viable but also socially acceptable. This work opens up several directions for future research - analysis of existing attack attribution techniques to identify further scope for improvements, incorporation of newer attributes into the design framework of the composable data model abstraction, and finally design of newer attack attribution techniques that comprehensively integrate the various attack prevention, mitigation and traceback techniques in an efficient manner

Countering DoS Attacks With Stateless Multipath Overlays

Indirection-based overlay networks (IONs) are a promising approach for countering distributed denial of service (DDoS) attacks. Such mechanisms are based on the assumption that attackers will attack a fixed and bounded set of overlay nodes causing service disruption to a small fraction of the users. In addition, attackers cannot eaves-drop on links inside the network or otherwise gain information that can help them focus their attacks on overlay nodes that are critical for specific communication flows. We develop an analytical model and a new class of attacks that considers both simple and advanced adversaries. We show that the impact of these simple attacks on IONs can severely disrupt communications. We propose a stateless spread-spectrum paradigm to create per-packet path diversity between each pair of end-nodes using a modified ION access protocol. Our system protects end-to-end communications from DoS attacks without sacrificing strong client authentication or allowing an attacker with partial connectivity information to repeatedly disrupt communications. Through analysis, we show that an Akamai-sized overlay can withstand attacks involving over 1.3M "zombie" hosts while providing uninterrupted end-to-end connectivity. By using packet replication, the system can resist attacks that render up to 40% of the nodes inoperable. Surprisingly, our experiments on PlanetLab demonstrate that in many cases end-to-end latency decreases when packet replication is used, with a worst-case increase by a factor of 2.5. Similarly, our system imposes less than 15% performance degradation in the end-to-end throughput, even when subjected to a large DDoS attack

Shuffling Based Mechanism for DDoS Prevention on Cloud Environment

Cloud Computing has evolved as a new paradigm in which users can use on-demand services, according to their needs. However, security concerns are primary obstacles to a wider adoption of clouds. Newly born concepts that clouds introduced, such as multi-tenancy, resource sharing and outsourcing, create new challenges for the security research. DDoS (Distributed Denial of service) attack is the biggest threat to the cloud since it affects the availability of services. There are a lot of techniques proposed by various researchers to prevent DDoS attacks on a cloud infrastructure. We are using a Shuffling Based approach for preventing DDoS in the cloud environment. This approach is reactive and uses the resource elasticity of the cloud. The aim of this technique is to save the maximum number of benign clients from the attack through shuffling. For assignment of clients to the replica servers, we are using a greedy algorithm. Every time we call this algorithm, we estimate the number of malicious clients using a proposed random function for that round of shuffle. We have shown that we can save a desired percentage of benign clients from the ongoing attacks after some shuffles. To detect the attack on each server, a detector is deployed that uses an entropy-based approach for detecting DDoS. A significant deviation in entropy represents the DDoS attack. We have also performed some tests to select the suitable attributes for entropy-based DDoS detection in different type of DDoS attacks. So in our work we have worked on both detection and prevention of DDoS on cloud infrastructur

Dynamic Shifting of Virtual Network Topologies for Network Attack Prevention

Computer networks were not designed with security in mind, making research into the subject of network security vital. Virtual Networks are similar to computer networks, except the components of a Virtual Network are in software rather than hardware. With the constant threat of attacks on networks, security is always a big concern, and Virtual Networks are no different. Virtual Networks have many potential attack vectors similar to physical networks, making research into Virtual Network security of great importance. Virtual Networks, since they are composed of virtualized network components, have the ability to dynamically change topologies. In this paper, we explore Virtual Networks and their ability to quickly shift their network topology. We investigate the potential use of this flexibility to protect network resources and defend against malicious activities. To show the ability of reactively shifting a Virtual Network’s topology to se- cure a network, we create a set of four experiments, each with a different dynamic topology shift, or “dynamic defense”. These four groups of experiments are called the Server Protection, Isolated Subnet, Distributed Port Group, and Standard Port Group experiments. The Server Protection experiments involve detecting an attack against a server and shifting the server behind a protected subnet. The other three sets of experiments, called Attacker Prevention experiments, involve detecting a malicious node in the internal network and initiating a dynamic de- fense to move the attacker behind a protected subnet. Each Attacker Prevention experiment utilizes a different dynamic defense to prevent the malicious node from attacking the rest of the Virtual Network. For each experiment, we run 6 different network attacks to validate the effectiveness of the dynamic defenses. The network attacks utilized for each experiment are ICMP Flooding, TCP Syn Flooding, Smurf attack, ARP Spoofing, DNS Spoofing, and NMAP Scanning. Our validation shows that our dynamic defenses, outside of the standard port group, are very effective in stopping each attack, consistently lowering the at- tacks’ success rate significantly. The Standard Port Group was the one dynamic defense that is ineffective, though there are also a couple of experiments that could benefit from being run with more attackers and with different situations to fully understand the effectiveness of the defenses. We believe that, as Virtual Networks become more common and utilized outside of data centers, the ability to dynamically shift topology can be used for network security purposes