5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, K...
5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, K...
5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, K...
5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, K...
5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, K...
5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, K...
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A Reliable Password-based User Authentication Scheme for Web-based Human Genome Database System

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A Reliable Password-based User Authentication Scheme for Web-based Human Genome Database System

  1. 1. 5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, Korea A Reliable Password-based User Authentication Scheme for Web-based Human Genome Database System Wei-Hsin Chen Zhen-Yu Wu1, Feipei Lai1,2,3, Yin-Hsiu Chien4, Wu- Graduate Institute of Biomedical Electronic and Liang Hwu4 1 Bioinfomatics Department of Computer Science and Information National Taiwan University Engineering 2 Taipei, Taiwan Graduate Institute of Biomedical Electronic and d97945014@ntu.edu.tw Bioinfomatics 3 Department of Electrical Engineering 4 Department of Medical Genetics National Taiwan University and Hospital Taipei, TaiwanAbstract—With the initial completion of Human Genome Project, Taiwan University Hospital. Here physicians help to examinethe post-genomic era is coming. Although the genome map of the genetic deficiencies of patients. They use the sequencehuman has been decoded, the roles that each segment of alignment tool- BLAST [3], to align the suspected DNAsequences acts are not totally discovered. On the other hand, with sequences, investigate the causes and pathogenic mechanismsthe rapid expansion of sequence information, the issues of data of the genetic diseases.compilation and data storage are increasingly important.Recently, a “Web-based Human Genome Database System” is Recently, a “Web–based Human Genome Databaseimplemented in National Taiwan University Hospital. The System” (WHGDS) is implemented in National Taiwanachievement of this system is that it integrates the modules of University Hospital (NTUH). The achievement of this systemsequence alignment and data compression on genome. For goals is that it integrates the modules of sequence alignment and dataof secure accessing this system over insecure networks, protocols compression. By embedding with the NCBI alignment program,of user authentication become more important. They are able to blastall, it automatically aligns the uploaded sequences andensure the security of data transmission and users’ searches for the corresponding genomic positions. Besides, thecommunication. In this paper, a password-based user system encodes the differences between sequences, effectivelyauthentication scheme, because of its convenience, efficiency, and compresses them and decreases the demand of storage spaces.property of simplicity for human memory, is proposed for the At the same time, it offers a protected way to access thesystem. personalized database. Also, users can quickly access the interesting data by inputting the keywords of specimen number, Keywords- Web-based Human Genome Database System; userauthentication; password; human memory. GI and sequence position, etc. This system provides the following two major features: I. INTRODUCTION First, it integrates the components of NCBI BLAST tools together with RepBase and RefSeq database, offers an auto- The term “DNA sequencing” refers to a technique used to aligning mechanism for those sequences uploaded by users.determine the orders of nucleotides- adenine, guanine, cytosine, Second, the system compresses those sequences by encodingand thymine, in a DNA sequence. In many biological the mismatches, which effectively decreases the demand ofapplications, the composition of sequence need to be known storage space.because it tells what kind of genetic information that is carried.For example, scientists investigate the sequence of DNA to As the sequence data accumulating day by day, the issuesdetermine whether there are functional segments such as genes, for data storage and data compilation become more and moreas well as to analyze those genes that carry genetic mutations. important. The goal of this study is to construct a secure web-Knowledge of the DNA sequencing has become indispensable based human genome database system to help the users storefor basic biological process, as well as genetic diagnosis and and mange those sequence data.forensic research [1]. Sanger biochemistry [2] is the primarytechnique used for DNA sequencing since the early 1990s. The security issue for the WHGDS becomes a significant concern. Speaking specifically, the most concerned security DNA sequencing is applied for the purpose of genetic issue is how to ensure information privacy and security duringdiagnosis in the Department of Medical Genetics of National transmission through the insecure networks. Relevant user ISBN: 978-1-4577-0872-5 (c) 2011 IEEE 227
  2. 2. 5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, Koreaauthentication schemes or secret-key distribution protocols are represent the exact sequences of individual’s genome. Othergenerally used to solve this kind of problem because these works such as the exploitation of single nucleotideprotocols are regarded as the primary safeguards in network polymorphism (SNP) and the analysis of variation for repeatelectronic applications [4-9]. Among these protocols, the copy-number are still in process. Knowledge of HGP withpassword-based mechanism is the most widely employed these works can help the genetic diagnosis, forensicmethod because of its efficiency [10]. Under such mechanism, identification and other biological research.each user is allowed to select his password and keep in mindwithout any additional assistant device for the further B. Genome Databaseauthentication process. The term “genome database” refers a database to store the Unfortunately, most of these schemes are proven to be genome-associated data. They are utilized in many applicationsunable to resist off-line password guessing attacks [11-15]. such as the analysis of genetic diseases, genetic finger-printingAdversary can correctly guess the password of a specific user for criminology, and genetic genealogy. There are many publicby brute force attacks through intercepted information or self- genome databases and genome search engines through thegenerated parameters. Endless possible problems are then internet. For examples, Genbank [17] incorporates DNApresented with the hacking of the password. For example, the sequences from all available public sources, primarily throughmalicious attacker may masquerade as a server to communicate the direct submission of sequence data from individualwith other users or impersonate as the user to log into a server laboratories and from large-scale sequencing projects. Theto acquire services. Therefore, we would like to propose a Ensembl [18] provides a bioinformatics framework to organizesecure and efficient password-based scheme suitable for the biology around the sequences of large genomes. It is aWHGDS. comprehensive source of stable automatic annotation of the human genome sequences. DDBJ (DNA Data Bank of Japan) The rest of this paper is organized as follows. Section 2 processes and publishes the massive amounts of data submittedintroduces the web-based human genome database system in mainly by Japanese genome projects and sequencing teams.NTUH. Section 3 illustrates the proposed password-based user It’s emphasized that the cooperation between data producingauthentication scheme. Security analyses are done in Section 4. teams and the data bank is crucial in carrying out theseComparisons are given in Section 5, and finally, conclusions processes smoothly [19]. In this paper, a genome associatedare drawn in Section 6. database- RefSeq [20], is used to help construct the customized human genome database system. II. INTRODUCTION OF WEB-BASED HUMAN GENOME DATABASE SYSTEM C. System ArchitecutreA. Human Genome Project With the rapid development of sequencing attained withDNA sequencing technology, the research of human genomebecome possible. The Human Genome Project (HGP) was aninternational cooperative project with the major goal todetermine the sequences which make up the human genomefrom both a physical and functional perspective. This projectbegan in 1990 promoted by James D. Watson at the U.S.National Institutes of Health. An initial draft of human genomewas released in 2000. Later, a more complete one is publishedin 2003, with further research still being reported. A parallelproject was performed outside of government by the CeleraCorporation [16]. As parts of the HGP, parallel sequencing wasdone for other organisms such as bacterium E. coli and mouse.These help to improve the technology for sequencing and helpthe explanation of human genes. The objective of this projectcan be summarized as follows [3]. Figure 1. System architecture of WHGDS 1) Identify all the genes in human genome and exploittheir functions. This system is mainly composed by five parts: 2) Determine the sequences of the 3 billion base pairs that 1) The web server: it offers the accessment for sequencingmake up the human genome. files uploading, file management, and genomic sequence 3) Properly store these related data in databases. management. 4) Improve tools for data analysis. 2) Sequence converter: it invokes blastall program to 5) Address the “ethical, legal, and social issues (ELSI)” perform the alignment works for uploaded sequences againstthat arise from this project. It should be noticed that all humans have their unique the reference sequences in RefSeq database.genomic sequence. Those sequences depicted by HGP do not 3) RefSeq and RepBase: they provide the standard human sequences and the repetitive element sequences, respectively. Identify applicable sponsor/s here. If no sponsors, delete this text box.(sponsors) ISBN: 978-1-4577-0872-5 (c) 2011 IEEE 228
  3. 3. 5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, Korea 4) Alignment database and genome database: The Second, the mismatch information is saved for dataalignment database contains the alignment results output by compression. The distance with the next mismatch, theMega BLAST (in compressed format). The genome database is mismatch type, different nucleotides are recorded and thenthe combination of the sequence data if there are some parts combined together as (differential length, mismatch type, nucleotide). There are three kinds of mismatch type- insertion,overlapped. deletion, replacement. It should be noted that the mismatch 5) Sequence assembler: it is responsible for the data type- deletion, has no “nucleotide” pattern behind it. Thedecompression and sequence assembly process. former example is recorded as:D. Sequence Conversion (3, Replacement, T), (4, Deletion), (5, Insertion, C), (1, In this section, the conversion process for uploaded Insertion, G)…sequences is introduced. The discussion is split into several To further transform these mismatches, Fibonacci codes areparts including sequence pre-processing, sequence aligning and applied to encode each “differential length”, and 2 bits aresequence post-processing. The processing flow is described as appended to encode each “mismatch type” andthe following: each ”nucleotide”. Fibonacci codes [20] are utilized as an 1) Sequence Preprocessing alternative to Huffman codes when the probability distribution The uploaded sequences are in raw format and need to be of the latter is not clear. It’s simple, fast and robust to be usedconverted to FASTA format to be recognized by blastall. A to encode the series of positive integers. Each integer itsequence in FASTA begins with a single-line description, encodes is ended with “11”, which can be recognized as thefollowed by lines of sequence information. The description line separator when decoding. Hence, the mentioned mismatchesbegins with a greater-than (“>“) symbol in the first word. By are illustrated in Fig. 2.the way, it is suggested that “batch search” of BLAST is more (3,Replacement,T) (4,Deletion) (5,Insertion,C) (1,Insertion,G) (587,Replacement,A)efficient because the entire collection of reference sequencesonly need to be scanned by once. For this reason, we Differential length: Fibonacci codingconcatenate the multiple sequences into a single FASTA file, Mismatch type Replacement: 00 Insertion: 01 Deletion: 10 Nucleotide A: 00 T: 01 C: 10 G: 11one after another with no blank lines in between sequences. 2) Sequence Aligning (0011,00,01) (1011,10) (00011,01,10) (11,01,11) (00101000101011,00,00) After the conversion of sequences by FASTA, the sequenceconverter automatically invokes a program– blastall, to executethe alignment work. blastall has some parameters that can be 00110001101110000110110110111001010001010110000arranged to fulfill the various purposes for alignment. Thealignment algorithm- Mega BLAST is chosen. Fig. 3 shows the Figure 2. The encoded examplesequence aligning process executed by blastall. First, therepetitive element database- RepBase is applied to mask the Fibonacci coding is simpler and faster than other entropyhuman repetitive segments occurred in the uploaded sequences. coding methods such as Huffman codes or Arithmetic encoding.This masking effectively speeds up the search process. Second, For the same purpose to be simple and fast, we use 2 bits tothe RefSeq database is provided to address the alignment work. encode each “mismatch type.” After the compressionThose uploaded sequences are aligned with the reference completed, we store them together with the data extracted fromsequences and then mapped to the corresponding genomic the XML-report (i.e. GI, template, positions, etc.) into thepositions. alignment database. 3) Sequence Postprocessing In this stage, a XML-parser is designed to extract the E. Sequence Retrieveinteresting information in XML report, and then transmit these The alignment database stores the alignment data ofdata into alignment database. Because the alignment results uploaded sequences. The users can retrieve these data to checkoccupy a large amount of storage spaces, these data should be whether they are correct or not. While these data are infurther compressed. Here a compression algorithm is proposed compressed format, they need to be decompressed beforeto address this issue. First, let us consider the following displayed. The retrieving procedure is stated in this section.alignment. a) fastcmd C A T C T G - G A G T C G T … fastacmd is a program provided by NCBI to get the | | | | | | | | | | interesting segments from the huge pool of sequences. At first, the system gets the information about GI, template and C A G C T G A G A G T - - T … positions form alignment database. Then it invokes fastacmd to The upper part is the uploaded sequence and the lower part retrieve the corresponding segment of reference sequenceis the reference sequence. The symbol ‘|’ in the middle according to the provided information.indicates that the upper nucleotide and lower nucleotide are b) Sequence Assemblymatched. Therefore, the others indicate that the base pair ismismatched between the uploaded and reference sequences. While the information about GI, template and positions are retrieved, the mismatches data also regained. These ISBN: 978-1-4577-0872-5 (c) 2011 IEEE 229
  4. 4. 5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, Koreamismatches are in compressed format and they need to be well protection against the analysis attack of smart cards so asdecompressed for further assembly. After the reference to prevent other users to catch the values.sequence is acquired by fastacmd, those mismatches areappended on the reference one by the way reverse to the Step 3: S returns pwi and the smart card to Ui through acompression process. Finally, the original sequence and its secure channel.alignment are obtained with the reference sequence. Eachsequence is retrieved by the same method and the users can B. Login Phasechoose the interesting parts for further stored to the genome When user Ui wants to log into the remote server S, hedatabase. firstly inserts his smart card into a terminal and then keys in his identification IDi along with his password pwi . The smart cardF. Genome Combination will execute the following steps automatically: Those examined sequences are picked by the users then Compute a dynamic ID for user Ui at time T. CIDi = h(pwi )stored to genome database. The difference between alignment h(Ni y T) h(y || IDi), where T is the timestamp of Ui ’sdatabase and genome database is that the latter stores the computer.jointed sequences and these sequences can be further modifiedby the users, but the alignment database only stores the Send h(y || IDi), CIDi, Ni, k and T to server S through auploaded sequences aligned by Mega BLAST. Furthermore, common channel.those sequences in alignment database may overlap but thissituation will not occur in genome database. C. Verification Phase When server S receives the login request (h(y || IDi), CIDi, III. PROPOSED AUTHENTICATION SCHEME Ni, k, T) at time T, server S does the verification as follows: In this section, we would like to propose a password-based Check the validity of the time interval. If T* - T ΔT holds,authentication scheme. This scheme is composed of four S accepts the login request of Ui; otherwise, the login request isphases. They are the registration phase, the login phase, the rejected.verification phase, and the password change phase. Below isthe detailed description of this proposal. Compute y = c – k / x. Before describing the details of the proposal, the notation Compute h(pwi ) = CIDi h(Ni y T) h(y || IDi).defined and used in this scheme is shown in Table 1. Compute IDi = Ni h(x || h(y || IDi)) h(pwi), and then hash the value with y to form h(y || IDi). TABLE I. NOTATION DEFINED AND USED IN THE SCHEME Verify whether h(y || IDi) is equivalent to h(y || IDi). If it is, S accepts the login request of Ui; otherwise, the login request is U the user rejected. Then S computes a = h(h(pwi ) y T). Pw the password of user U Send (a, T) to Ui for a mutual authentication processing. ID the identity of user U When user Ui receives the reply message (a, T) from S the remote server server S at time T, Ui does the verification as follows: h( ) a public one-way hash function Check whether T* - T ΔT holds. If it does, user Ui will a bit-wise XOR operation accept the reply message and go on to the next step; otherwise, he refuses the reply message.A. Registration Phase Compute a = h(h(pwi) y T). Suppose user Ui wants to register to a remote server S.Then he proposes a registration request so as to get his Verify whether a is equivalent to a. If they are equivalent,password and his smart card from the server as follows. user Ui confirms that server S is valid. Step 1: Ui sends his own identification IDi to S. Compute session key sk = h(h(T y)). Step 2: S computes Ni = h(pwi ) h(x || h(y || IDi)) IDi, D. Password Change Phase where || is a bit concatenation operator, x is the secret of the remote server, pwi is the password of When user Ui wants to change his password, he inserts his Ui chosen by S, and y is a secret number selected by smart card into a terminal device. He firstly keys in his old the remote server and stored into each registered password pwi and then follows his new password pwnew. The user’s smart card. smart card will execute the following steps: S generates the secret constant value c = xy + k, where k is Compute Ni* = Ni h(pwi) h(pwnew).a value for Ui and is computed by c - xy. Step 1: Replace the original Ni with this new one, Ni*, and S personalizes Ui’s smart card which included with the then the password is changed.parameters [h( ), Ni, y, k]. All parameters should be provided a ISBN: 978-1-4577-0872-5 (c) 2011 IEEE 230
  5. 5. 5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, KoreaE. Security Analysis assuring data integrity and security during transmission. A password-based user authentication scheme for the Safeguarding confidential data from revelation, modification,integrated WHGDS is effective when it can assure the system’s or deletion during its transmission is the major concern in thissecurity in terms of password protection, data transmission, stage.user masquerading and system spoofing. In other words, the A session key is used in our scheme to protect thescheme can resist various malicious attacks, including stolen- confidential data from being revealed, modified, or deletedverifier attacks, on-line and off-line password guessing attacks, during its transmission. The session key is generated viareplay attacks, and server spoofing attacks. In this section, we hashing two numbers y and T after the verification process. Allwill analyze each in details and show how the proposed scheme of the confidential data are encrypted by the session key, whichsatisfies with the above-mentioned security criteria. means that without the session key, no attacker can eavesdrop, modify, or delete the transmitting data.F. Password Protection Furthermore, the session key in our scheme will be invalid Here the passwords play a very important role for each user, whenever the communication between the user and thesuch as a doctor, a nurse, a patient, or a scholar, for logging integrated system server goes to the end. This means the keyinto the remote server. Assuring the security of a password is will have expired its period of usage and cannot be used anythe most crucial key-point in our security analysis. Thus, we more so that it is revoked. When the user enters the systemwould like to prove that our password authentication scheme again, a new session key will be generated for him to encryptcan withstand two kinds of attacks aimed at passwords. They his information during the current communication process.are the stolen-verifier attack, and the password guessing attack. Therefore, there will be much difficulty for anyone to calculateThe password guessing attack can further be classified into on- any of the probable previous session keys despite using all hisline and off-line attacks. known information. Stolen-verifier attacks mean that some machinated insiders Therefore, unless the user shares his session key on purposeof a remote server are able to steal or modify the users’ with the third party, our scheme shows the ability to achievelegitimate passwords or update the password-verification tables the requirement of data transmission security with the help ofstored in the server’s database. This attack would not succeed the session key.in our scheme because the password of a user isinstantaneously generated and verified by the server, who uses H. User Masquerading Detectionits secret values c and x upon the login phase. No passwords orverification tables have to be kept in the server’s database; While the password authentication is being processed,therefore, the insiders would not be able to steal or modify the conspiring attackers may impersonate the identities of thepasswords. medical staff, patients, or researchers in order to pass the authentication phase and gain the right to access the data in the An on-line password guessing attack means that an attacker WHGDS. To prevent the disclosure of users’ privacy, protocolscontinuously guesses a possible password and tries to log into a are necessary to fend off replay attacks. A replay attack is aremote server until he is successful. In our scheme, such kind of network attack in which a valid data transmission isattacks can be detectable. If an adversary attempts to identify repeated maliciously. This kind of attack is generally done bythe password of Ui, he is supposed to use every guessed some machinated adversary, who intercepts the data andpassword to obtain the corresponding CIDi in the login phase. transmits it repeatedly. In our scheme, we employ the conceptHowever, the probability of guessing the correct password is of a timestamp to avoid such attacks. When server S or user Uionly 2-k, where k is the length of the selected password. receives a message, he firstly calculates the difference betweenGenerally, if a guess is wrong, server S can detect easily that the current time T* and transmitted time T. And then he willthere is an adversary trying to acquire services illegally. check whether the difference is smaller than ΔT . If it is, thenTherefore, on-line password guessing attacks cannot succeed. the message is valid; otherwise, the message may be re-sent. An off-line password guessing attack means that an attacker Therefore, the replay attack is fruitless.can employ some intercepted information to guess the Actually, the password in our scheme is protected by thepassword of a specific user by brute force attacks. Take a cryptographic hash function, and thus an attacker is unable toglance on our scheme. The secret parameters such as x and y generate and interpret authentication messages correctlyare protected by the cryptographic hash function and are not without the knowledge of a user’s password. It is obviouslyrevealed to anyone; thus, this kind of attack will not work. impossible for a person in our scheme to masquerade as aNow, assume that an adversary has obtained the following legitimate user to log into an integrated system server andparameters (h(y || IDi), CIDi, Ni, T) in the login phase. However, acquire system services.without y, he cannot compute h(pwi ) = CIDi h(Ni y T)h(y || IDi). Similarly, it is also unable for him to calculate h(pwi ) I. Server Spoofing Detection= Ni h(x || h(y || IDi)) IDi without x and IDi. Therefore,off-line password guessing attacks can be withstood. Similar to Section C, the attack by someone masquerading as the server to cheat other users is another security concern. An attacker may masquerade the identity of the system to carryG. Data Transmission Security out illegal, imperceptible authentication behavior, and After a user logs into the system successfully, another consequently obtain the private information of some usercrucial security issue upon authentication arises, which is ISBN: 978-1-4577-0872-5 (c) 2011 IEEE 231
  6. 6. 5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), 31 May -3 June 2011, Daejeon, Koreathrough the transmitted data. This is known as server spoofing environments. This authentication scheme will be realized andattacks: someone masquerades as the server to cheat other validated soon.users. There is one possible way to let a conspiring attacker ACKNOWLEDGMENTsuccessfully spoof the other users in such schemes. When the The authors would like to acknowledge the fund from theattacker obtains the secret values x of a remote system, he can Microsoft Corporation and the helps from their staff.impersonate the server. In our scheme, however, the secretvalues c and x are never transmitted via a common network REFERENCESchannel and are stored on the server computer’s hard drivewhich only the administrator has the right to control and access; [1] “DNA sequencing,” http://genomics.org/index.php/DNA_sequencingso it is impossible for anyone to acquire them. Therefore, the [2] F. Sanger, G. M. Air, B. G. Barrell, et. al., “Nucleotide sequence of bacteriophage phi X174 DNA,” Nature, vol. 265, no. 5596, pp. 687-695,server spoofing attacks will be detected and prevented. 1977. [3] Human Genome Project Information,”J. Comparison http://www.ornl.gov/sci/techresources/Human_Genome/home.shtml To display how our proposed password-based user [4] E. Ball, D.W. Chadwick, and D. 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