Biblio

It is common to certify when a file was created in digital investigations, e.g., determining first inventors for patentable ideas in intellectual property systems to resolve disputes. Secure time-stamping schemes can be derived from blockchain-based storage to protect files from backdating/forward-dating, where a file is integrated into a transaction on a blockchain and the timestamp of the corresponding block reflects the latest time the file was created. Nevertheless, blocks' timestamps in blockchains suffer from time errors, which causes the inaccuracy of files' timestamps. In this paper, we propose an accurate blockchain-based time-stamping scheme called Chronos. In Chronos, when a file is created, the file and a sufficient number of successive blocks that are latest confirmed on blockchain are integrated into a transaction. Due to chain quality, it is computationally infeasible to pre-compute these blocks. The time when the last block was chained to the blockchain serves as the earliest creation time of the file. The time when the block including the transaction was chained indicates the latest creation time of the file. Therefore, Chronos makes the file's creation time corresponding to this time interval. Based on chain growth, Chronos derives the time when these two blocks were chained from their heights on the blockchain, which ensures the accuracy of the file's timestamp. The security and performance of Chronos are demonstrated by a comprehensive evaluation.

With the rapid development of the Internet, the dark network has also been widely used in the Internet [1]. Due to the anonymity of the dark network, many illegal elements have committed illegal crimes on the dark. It is difficult for law enforcement officials to track the identity of these cyber criminals using traditional network survey techniques based on IP addresses [2]. The threat information is mainly from the dark web forum and the dark web market. In this paper, we introduce the current mainstream dark network communication system TOR and develop a visual dark web forum post association analysis system to graphically display the relationship between various forum messages and posters, and help law enforcement officers to explore deep levels. Clues to analyze crimes in the dark network.

An emerging Internet business is residential proxy (RESIP) as a service, in which a provider utilizes the hosts within residential networks (in contrast to those running in a datacenter) to relay their customers' traffic, in an attempt to avoid server- side blocking and detection. With the prominent roles the services could play in the underground business world, little has been done to understand whether they are indeed involved in Cybercrimes and how they operate, due to the challenges in identifying their RESIPs, not to mention any in-depth analysis on them. In this paper, we report the first study on RESIPs, which sheds light on the behaviors and the ecosystem of these elusive gray services. Our research employed an infiltration framework, including our clients for RESIP services and the servers they visited, to detect 6 million RESIP IPs across 230+ countries and 52K+ ISPs. The observed addresses were analyzed and the hosts behind them were further fingerprinted using a new profiling system. Our effort led to several surprising findings about the RESIP services unknown before. Surprisingly, despite the providers' claim that the proxy hosts are willingly joined, many proxies run on likely compromised hosts including IoT devices. Through cross-matching the hosts we discovered and labeled PUP (potentially unwanted programs) logs provided by a leading IT company, we uncovered various illicit operations RESIP hosts performed, including illegal promotion, Fast fluxing, phishing, malware hosting, and others. We also reverse engi- neered RESIP services' internal infrastructures, uncovered their potential rebranding and reselling behaviors. Our research takes the first step toward understanding this new Internet service, contributing to the effective control of their security risks.

Practitioners use infrastructure as code (IaC) scripts to provision servers and development environments. While developing IaC scripts, practitioners may inadvertently introduce security smells. Security smells are recurring coding patterns that are indicative of security weakness and can potentially lead to security breaches. The goal of this paper is to help practitioners avoid insecure coding practices while developing infrastructure as code (IaC) scripts through an empirical study of security smells in IaC scripts. We apply qualitative analysis on 1,726 IaC scripts to identify seven security smells. Next, we implement and validate a static analysis tool called Security Linter for Infrastructure as Code scripts (SLIC) to identify the occurrence of each smell in 15,232 IaC scripts collected from 293 open source repositories. We identify 21,201 occurrences of security smells that include 1,326 occurrences of hard-coded passwords. We submitted bug reports for 1,000 randomly-selected security smell occurrences. We obtain 212 responses to these bug reports, of which 148 occurrences were accepted by the development teams to be fixed. We observe security smells can have a long lifetime, e.g., a hard-coded secret can persist for as long as 98 months, with a median lifetime of 20 months.

Modern operating systems for personal computers (including Linux, MAC, and Windows) provide user-level APIs for an application to access the I/O paths of another application. This design facilitates information sharing between applications, enabling applications such as screenshots. However, it also enables user-level malware to log a user's keystrokes or scrape a user's screen output. In this work, we explore a design called SwitchMan to protect a user's I/O paths against user-level malware attacks. SwitchMan assigns each user with two accounts: a regular one for normal operations and a protected one for inputting and outputting sensitive data. Each user account runs under a separate virtual terminal. Malware running under a user's regular account cannot access sensitive input/output under a user's protected account. At the heart of SwitchMan lies a secure protocol that enables automatic account switching when an application requires sensitive input/output from a user. Our performance evaluation shows that SwitchMan adds acceptable performance overhead. Our security and usability analysis suggests that SwitchMan achieves a better tradeoff between security and usability than existing solutions.

Ciphertext-policy Attributes-based Encryption (CP-ABE) is an encouraging cryptographic mechanism. It behaves an access control mechanism for data security. A ciphertext and secret key of user are dependent upon attributes. As a nature of CP-ABE, the data owner defines access policy before encrypting plaintext by his right. Therefore, CP-ABE is suitable in a real environment. In CP-ABE, the revocation issue is demanding since each attribute is shared by many users. A policy-based revolutionary CP-ABE scheme is proposed in this paper. In the proposed scheme, revocation takes place in policy level because a policy consists of threshold attributes and each policy is identified as a unique identity number. Policy revocation means that the data owner updates his policy identity number for ciphertext whenever any attribute is changed in his policy. To be a flexible updating policy control, four types of updating policy levels are identified for the data owner. Authorized user gets a secret key from a trusted authority (TA). TA updates the secret key according to the policy updating level done by the data owner. This paper tests personal health records (PHRs) and analyzes execution times among conventional CP-ABE, other enhanced CP-ABE and the proposed scheme.

GPS signals, the main origin of navigation, are not functional in indoor environments. Therefore, Wi-Fi access points have started to be increasingly used for localization and tracking inside the buildings by relying on fingerprint-based approach. However, with these types of approaches, several concerns regarding the privacy of the users have arisen. Malicious individuals can determine a clients daily habits and activities by simply analyzing their wireless signals. While there are already efforts to incorporate privacy to the existing fingerprint-based approaches, they are limited to the characteristics of the homo-morphic cryptographic schemes they employed. In this paper, we propose to enhance the performance of these approaches by exploiting another homomorphic algorithm, namely DGK, with its unique encrypted sorting capability and thus pushing most of the computations to the server side. We developed an Android app and tested our system within a Columbia University dormitory. Compared to existing systems, the results indicated that more power savings can be achieved at the client side and DGK can be a viable option with more powerful server computation capabilities.

A prioritized cyber defense remediation plan is critical for effective risk management in cyber-physical systems (CPS). The increased integration of Information Technology (IT)/Operational Technology (OT) in CPS has to lead to the need to identify the critical assets which, when affected, will impact resilience and safety. In this work, we propose a methodology for prioritized cyber risk remediation plan that balances operational resilience and economic loss (safety impacts) in CPS. We present a platform for modeling and analysis of the effect of cyber threats and random system faults on the safety of CPS that could lead to catastrophic damages. We propose to develop a data-driven attack graph and fault graph-based model to characterize the exploitability and impact of threats in CPS. We develop an operational impact assessment to quantify the damages. Finally, we propose the development of a strategic response decision capability that proposes optimal mitigation actions and policies that balances the trade-off between operational resilience (Tactical Risk) and Strategic Risk.

With the development of IoT and 5G networks, the demand for the next-generation intelligent transportation system has been growing at a rapid pace. Dynamic mapping has been considered one of the key technologies to reduce traffic accidents and congestion in the intelligent transportation system. However, as the number of vehicles keeps growing, a huge volume of mapping traffic may overload the central cloud, leading to serious performance degradation. In this paper, we propose and prototype a CUPS (control and user plane separation)-based edge computing architecture for the dynamic mapping and quantify its benefits by prototyping. There are a couple of merits of our proposal: (i) we can mitigate the overhead of the networks and central cloud because we only need to abstract and send global dynamic mapping information from the edge servers to the central cloud; (ii) we can reduce the response latency since the dynamic mapping traffic can be isolated from other data traffic by being generated and distributed from a local edge server that is deployed closer to the vehicles than the central server in cloud. The capabilities of our system have been quantified. The experimental results have shown our system achieves throughput improvement by more than four times, and response latency reduction by 67.8% compared to the conventional central cloud-based approach. Although these results are still obtained from the preliminary evaluations using our prototype system, we believe that our proposed architecture gives insight into how we utilize CUPS and edge computing to enable efficient dynamic mapping applications.

According to the information security requirements of the industrial control system and the technical features of the existing defense measures, a dynamic security control strategy based on trusted computing is proposed. According to the strategy, the Industrial Cyber-Physical System system information security solution is proposed, and the linkage verification mechanism between the internal fire control wall of the industrial control system, the intrusion detection system and the trusted connection server is provided. The information exchange of multiple network security devices is realized, which improves the comprehensive defense capability of the industrial control system, and because the trusted platform module is based on the hardware encryption, storage, and control protection mode, It overcomes the common problem that the traditional repairing and stitching technique based on pure software leads to easy breakage, and achieves the goal of significantly improving the safety of the industrial control system . At the end of the paper, the system analyzes the implementation of the proposed secure industrial control information security system based on the trustworthy calculation.

Statistics suggests, proceeding towards IoT generation, is increasing IoT devices at a drastic rate. This will be very challenging for our present-day network infrastructure to manage, this much of data. This may risk, both security and traffic collapsing. We have proposed an infrastructure with Fog Computing. The Fog layer consists two layers, using the concepts of Service oriented Architecture (SOA) and the Agent based composition model which ensures the traffic usage reduction. In order to have a robust and secured system, we have modified the Fog based agent model by replacing the SOA with secured Named Data Network (NDN) protocol. Knowing the fact that NDN has the caching layer, we are combining NDN and with Fog, as it can overcome the forwarding strategy limitation and memory constraints of NDN by the Agent Society, in the Middle layer along with Trust management.

Delivery service via ridesharing is a promising service to share travel costs and improve vehicle occupancy. Existing ridesharing systems require participating vehicles to periodically report individual private information (e.g., identity and location) to a central controller, which is a potential central point of failure, resulting in possible data leakage or tampering in case of controller break down or under attack. In this paper, we propose a Blockchain secured ridesharing delivery system, where the immutability and distributed architecture of the Blockchain can effectively prevent data tampering. However, such tamper-resistance property comes at the cost of a long confirmation delay caused by the consensus process. A Hash-oriented Practical Byzantine Fault Tolerance (PBFT) based consensus algorithm is proposed to improve the Blockchain efficiency and reduce the transaction confirmation delay from 10 minutes to 15 seconds. The Hash-oriented PBFT effectively avoids the double-spending attack and Sybil attack. Security analysis and simulation results demonstrate that the proposed Blockchain secured ridesharing delivery system offers strong security guarantees and satisfies the quality of delivery service in terms of confirmation delay and transaction throughput.

All popular browsers support browser extensions. They are small software module for customizing web browsers. It provides extra features like user interface modifications, ad blocking, cookie management and so on. As features increase, security becomes more difficult. The impact of malicious browser extensions is also enormous. More than 1 million Chrome users got affected by extensions from Chrome store itself. [1] The risk further increases with offline extension installations. The privileges browser extensions have, pave the path for many kinds of attacks. Replay attack and session hijacking are two of these attacks we are dealing here. Here we propose a defence system based on dynamic encrypted cookies to defend these attacks. We use cookies as token for continuous authentication, which protects entire communication. Static cookies are prone for session hijacking, and therefore we use dynamic cookies which are sealed with encryption. It also protects from replay attack by changing itself, making previous message obsolete. This essentially solves both of the problems.

The paper presents the results of load testing of embedded hardware platforms for Internet of Things solutions. Analyzed the available hardware. The operating systems from different manufacturers were consolidated into a single classification, and for the two most popular, load testing was performed by an external and internal wireless network adapter. Developed its own software solution based on the Python programming language. The number of wireless subscribers ranged from 7 to 14. Experimental results will be useful in deploying wireless infrastructure for small commercial and scientific wireless networks.

With the rapid development of Internet of Things (IoT), distributed denial of service (DDoS) attacks become the important security threat of the IoT. Characteristics of IoT, such as large quantities and simple function, which have easily caused the IoT devices or servers to be attacked and be turned into botnets for launching DDoS attacks. In this paper, we use software-defined networking (SDN) to develop moving target defense (MTD) architecture that increases uncertainty because of ever changing attack surface. In addition, we deploy SDN-based honeypots to mimic IoT devices, luring attackers and malwares. Finally, experimental results show that combination of MTD and SDN-based honeypots can effectively hide network asset from scanner and defend against DDoS attacks in IoT.

As the number of Internet users increases, their usage also diversifies, and it is important to prevent Identity on the Internet (Digital Identity) from being violated. Unauthorized authentication is one of the methods to infringe Digital Identity. Multi-factor authentication has been proposed as a method for preventing unauthorized authentication. However, the cryptographic authenticator required for multi-factor authentication is expensive both financially and UX-wise for the user. In this paper, we design, implement and evaluate multi-factor authentication using My Number Card provided by public personal identification service and WebUSB, which is being standardized.

This SQL injection attack is one of the common means for hackers to attack database. With the development of B/S mode application development, more and more programmers use this mode to write applications. However, due to the uneven level and experience of programmers, a considerable number of programmers do not judge the legitimacy of user input data when writing code, which makes the application security risks. Users can submit a database query code and get some data they want to know according to the results of the program. SQL injection attack belongs to one of the means of database security attack. It can be effectively protected by database security protection technology. This paper introduces the principle of SQL injection, the main form of SQL injection attack, the types of injection attack, and how to prevent SQL injection. Discussed and illustrated with examples.

With the increase in the number of cyber attacks on industrial control systems, especially in critical infrastructure facilities, the problem of comprehensive analysis of the security of such systems becomes urgent. This, in turn, requires the availability of fundamental mathematical, methodological and instrumental basis for modeling automated systems, modeling attacks on their information resources, which would allow realtime system protection analysis. The paper proposes a basis for simulating protected industrial control systems, based on the developed reference security model, and a model for attacks on information resources of automated systems. On the basis of these mathematical models, a complex model of a protected automated system was developed, which can be used to build protection systems for automated systems used in production.

DNS based domain name resolution has been known as one of the most fundamental Internet services. In the meanwhile, DNS cache poisoning attacks also have become a critical threat in the cyber world. In addition to Kaminsky attacks, the falsified data from the compromised authoritative DNS servers also have become the threats nowadays. Several solutions have been proposed in order to prevent DNS cache poisoning attacks in the literature for the former case such as DNSSEC (DNS Security Extensions), however no effective solutions have been proposed for the later case. Moreover, due to the performance issue and significant workload increase on DNS cache servers, DNSSEC has not been deployed widely yet. In this work, we propose an advanced detection method against DNS cache poisoning attacks using machine learning techniques. In the proposed method, in addition to the basic 5-tuple information of a DNS packet, we intend to add a lot of special features extracted based on the standard DNS protocols as well as the heuristic aspects such as “time related features”, “GeoIP related features” and “trigger of cached DNS data”, etc., in order to identify the DNS response packets used for cache poisoning attacks especially those from compromised authoritative DNS servers. In this paper, as a work in progress, we describe the basic idea and concept of our proposed method as well as the intended network topology of the experimental environment while the prototype implementation, training data preparation and model creation as well as the evaluations will belong to the future work.

The amount of connected devices in the industrial environment is growing continuously, due to the ongoing demands of new features like predictive maintenance. New business models require more data, collected by IIoT edge node sensors based on inexpensive and low performance Microcontroller Units (MCUs). A negative side effect of this rise of interconnections is the increased attack surface, enabled by a larger network with more network services. Attaching badly documented and cheap devices to industrial networks often without permission of the administrator even further increases the security risk. A decent method to monitor the network and detect “unwanted” devices is network scanning. Typically, this scanning procedure is executed by a computer or server in each sub-network. In this paper, we introduce network scanning and mapping as a building block to scan directly from the Industrial Internet of Things (IIoT) edge node devices. This module scans the network in a pseudo-random periodic manner to discover devices and detect changes in the network structure. Furthermore, we validate our approach in an industrial testbed to show the feasibility of this approach.

We propose a serverless computing mechanism for distributed computation based on polar codes. Serverless computing is an emerging cloud based computation model that lets users run their functions on the cloud without provisioning or managing servers. Our proposed approach is a hybrid computing framework that carries out computationally expensive tasks such as linear algebraic operations involving large-scale data using serverless computing and does the rest of the processing locally. We address the limitations and reliability issues of serverless platforms such as straggling workers using coding theory, drawing ideas from recent literature on coded computation. The proposed mechanism uses polar codes to ensure straggler-resilience in a computationally effective manner. We provide extensive evidence showing polar codes outperform other coding methods. We have designed a sequential decoder specifically for polar codes in erasure channels with full-precision input and outputs. In addition, we have extended the proposed method to the matrix multiplication case where both matrices being multiplied are coded. The proposed coded computation scheme is implemented for AWS Lambda. Experiment results are presented where the performance of the proposed coded computation technique is tested in optimization via gradient descent. Finally, we introduce the idea of partial polarization which reduces the computational burden of encoding and decoding at the expense of straggler-resilience.

Cloud storage solutions have gained momentum in recent years. However, cloud servers can not be fully trusted. Data access control have becomes one of the main impediments for further adoption. One appealing approach is to incorporate the access control into encrypted data, thus removing the need to trust the cloud servers. Among existing cryptographic solutions, Ciphertext Policy Attribute-Based Encryption (CP-ABE) is well suited for fine-grained data access control in cloud storage. As promising as it is, user revocation is a cumbersome problem that impedes its wide application. To address this issue, we design an access control system called DUR-CP-ABE, which implements identity-based User Revocation in a data owner Discretionary way. In short, the proposed solution provides the following salient features. First, user revocation enforcement is based on the discretion of the data owner, thus providing more flexibility. Second, no private key updates are needed when user revocation occurs. Third, the proposed scheme allows for group revocation of affiliated users in a batch operation. To the best of our knowledge, DUR-CP-ABE is the first CP-ABE solution to provide affiliation- based batch revocation functionality, which fits naturally into organizations' Identity and Access Management (IAM) structure. The analysis shows that the proposed access control system is provably secure and efficient in terms of computation, communi- cation and storage.

Cloud storage service makes it very convenient for people to access and share data. At the same time, the confidentiality and privacy of user data is also facing great challenges. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) scheme is widely considered to be the most suitable security access control technology for cloud storage environment. Aiming at the problem of privacy leakage caused by single-cloud CP-ABE which is commonly adopted in the current schemes, this paper proposes a privacy-preserving CP-ABE access control scheme using multi-cloud architecture. By improving the traditional CP-ABE algorithm and introducing a proxy to cut the user's private key, it can ensure that only a part of the user attribute set can be obtained by a single cloud, which effectively protects the privacy of user attributes. Meanwhile, the intermediate logical structure of the access policy tree is stored in proxy, and only the leaf node information is stored in the ciphertext, which effectively protects the privacy of the access policy. Security analysis shows that our scheme is effective against replay and man-in-the-middle attacks, as well as user collusion attack. Experimental results also demonstrates that the multi-cloud CP-ABE does not significantly increase the overhead of storage and encryption compared to the single cloud scheme, but the access control overhead decreases as the number of clouds increases. When the access policy is expressed with a AND gate structure, the decryption overhead is obviously less than that of a single cloud environment.

Wireless communications have encountered a considerable improvement and have integrated human life through various applications, mainly by the widespread of mobile ad hoc and sensor networks. A fundamental characteristic of wireless communications are in their broadcast nature, which allows accessibility of information without placing restrictions on a user's location. However, accessibility also makes wireless communications vulnerable to eavesdropping. To enhance the security of network communication, we propose a separate key generation server which is responsible for key generation using complex random algorithm. The key will remain in database in encrypted format. To prevent brute force attack, we propose various group key generation algorithms in which every group will have separate group key to verify group member's identity. The group key will be verified with the session information before decryption, so that our system will prevent attack if any attacker knows the group key. To increase the security of the system, we propose three level encryption securities: Client side encryption using AES, Server side encryption using AES, and Artificial noise generation and addition. By using this our system is free from brute force attack as we are using three level message security and complex Random key generation algorithms.

In recent years, many users have uploaded data to the cloud for easy storage and sharing with other users. At the same time, security and privacy concerns for the data are growing. Attribute-based encryption (ABE) enables both data security and access control by defining users with attributes so that only those users who have matching attributes can decrypt them. For real-world applications of ABE, revocation of users or their attributes is necessary so that revoked users can no longer decrypt the data. In actual implementations, ABE is used in hybrid with a symmetric encryption scheme such as the advanced encryption standard (AES) where data is encrypted with AES and the AES key is encrypted with ABE. The hybrid encryption scheme requires re-encryption of the data upon revocation to ensure that the revoked users can no longer decrypt that data. To re-encrypt the data, the data owner (DO) must download the data from the cloud, then decrypt, encrypt, and upload the data back to the cloud, resulting in both huge communication costs and computational burden on the DO depending on the size of the data to be re-encrypted. In this paper, we propose an attribute-based proxy re-encryption method in which data can be re-encrypted in the cloud without downloading any data by adopting both ABE and Syalim's encryption scheme. Our proposed scheme reduces the communication cost between the DO and cloud storage. Experimental results show that the proposed method reduces the communication cost by as much as one quarter compared to that of the trivial solution.